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Research Examples of Developmental Psychology
When you are studying developmental psychology , you’re studying how people grow and develop, all the way from childbirth to the end of their lifespan. What are examples of developmental psychology? It could be anything within a range of subject matters that are related to human growth. Not just psychological behavior, but anything from thoughts and emotions , cognitive and linguistic development, to decision making and motivation, moral and even physical development like motor skills.
Research examples of developmental psychology
Over the years we’ve come across many examples of research in developmental psychology , often done with various behavioral research tools. Looking for topics for developmental psychology research paper? We’ve put together an overview of research examples in developmental psychology that were published on the Behavioral Research Blog.
Table of contents
- Infant Stage
- Adolescent Stage
- Adult Stage
Examples of developmental psychology: Infant stage
The infant stage is the time from birth until children are (roughly) two years old. A time that has been well studied by researchers, as changes are rapid and these first years in life are considered fundamental in our development.
Early Infant behavior development of hand preference
In learning about objects and their parts, transporting objects to new locations, and sharing objects with others, the hands are essential. Infants discover how to control each hand and how to use the hands together.
There are many reasons to study the development of hand preference in infants, as it can provide clues about motor skills or any developmental disorders. A team of researchers was particularly interested in asymmetric bimanual actions and presented “Unimanual to bimanual: Tracking the development of handedness from 6 to 24 months”.
Read the full post here: Early Infant behavior development of hand preference
In the Noldus Webinar 'How emotions are made in Baby FaceReader' , we will tell you about emotions, how they are 'made' and how this relates to facial expression analysis in FaceReader with a focus on Baby FaceReader. Curious? Join the webinar on Thursday 21 April 2022!
Observing and analyzing repetitive movements in infants to detect autism
In the first year of life, an infant learns how to use his or her arms, legs, mouth, hands, and fingers by repeating movements over and over again. They discover a wealth of possibilities. However, an increased frequency of repetitive movements has been widely described in neurodevelopmental disorders as well.
To examine if a specific repertoire of repetitive movements was present in children with autism, researchers used home videos to code the behaviors of the infants.
Continue reading: Observing and analyzing repetitive movements in infants to detect autism
Gaze behavior in infants
Infant siblings of children with or without ASD participated in a study to determine whether gaze behavior, showed during a test with an unfamiliar examiner, could predict gaze behavior in a more naturalistic context.
To measure the cognitive functioning of the infants, the Mullen Scales of Early Learning was filled in at each visit by an examiner. Meanwhile, infant gaze to the examiner’s face was recorded.
Read the full post here: A closer look at eye contact
Developing social communication and the role of mimicry
Children learn from interacting with others, especially their parents. For example, reproducing the emotions that others express is part of that. Copying facial expressions is one of the great milestones in the social development of a child.
Still, little is known about the mechanisms controlling the early development of emotional mimicry. Therefore, a research team of the University of Amsterdam conducted a study to investigate infant emotional mimicry, parent-infant mutual attention, and parent dispositional affective empathy.
Read more about this study here: The role of mimicry in the development of social communication
Download the free White paper to learn more about the software tools available for infant studies.
- Video observations to capture behaviors
- Coding behaviors accurately
- Unobtrusive emotion analysis
Adolescence is the period of transition between childhood and adulthood. It is a time for rapid cognitive development. When entering adolescence children are going through many changes at the same time: both physical and intellectual, as well as their personality and social skills that are developing. We’ve published several articles about studies into the adolescent stage.
Direct observations help develop effective interventions in adolescence
In a study by a team of researchers from Arizona State University, John Hopkins School of Medicine in Baltimore, Maryland, and the Oregon Research Institute, family and friendship dynamics in adolescence were observed in order to develop more personalized interventions that prevent problem behaviors and adjustment issues.
Continue reading about effective interventions in adolescence .
Dealing with depression in adolescence
In adolescence, the ability to regulate emotions is heavily challenged by numerous biological, social, and psychological changes. How are adolescents’ emotions socialized by mothers and close friends? A study by a team of researchers from Canada and The Netherlands focused on dealing with depression in adolescence.
Continue reading: Understanding adolescent emotions
Studying conflict interactions between mothers and adolescents
Adolescence is a developmental phase with many physical, neurodevelopmental, psychological, and social changes. It is common for conflicts to arise between adolescents and their parents. However, severe conflicts can have negative effects on adolescent development. What can parents do to prevent escalating conflicts ?
This free white paper informs you how on to facilitate a parent-child study and how to set up your experiment.
- Perform tests in a lab or in-home
- Collect data with video
- Design a coding scheme
Read 5 more examples of research in adolescence here >>
Research examples in developmental psychology research: Adult stage
Adult development encompasses the changes that occur in biological and psychological domains of human life from the end of adolescence until the end of one's life 1 . When studying adult development, many researchers tend to focus on aging and health.
Some study eating behavior in residential care homes which enables them to take environmental factors into account. Others focus on family relations and communication and try to facilitate and improve contact between parents and children living a distance apart. Some examples of developmental psychology research in the adult stage of life.
How to measure couple communication patterns
Communication between husbands and wives is often discussed on TV, in magazines, and is frequently a topic of discussion amongst friends. Additionally, it is also a popular research theme. Effective husband-wife communication can benefit a relationship. But are there specific behaviors which need enforcing and are they the same for every couple?
Read more: How to measure couple communication patterns
Flow is a state in which a person is fully involved in an activity, decreasing self-consciousness and sense of time. This process requires a person to be extremely focused, as well as exactly have the skills to master a task. Several researchers have developed methods of measuring flow.
Find out more: Measuring flow
Curious what emotions your face shows? Upload a photo here, and our FaceReader software will test it for emotionality.
- Enter a url or browse for an image
- Use passport photo like pictures
- Make sure that the pictures you upload are the best they can be
Do your emotions and moods change as you get older?
Are emotions affected differently for younger than for older people? Researchers used FaceReader to complement self-assessments and objectify mood changes to answer this question . They exposed participants to film segments to induce four basic emotions: anger, disgust, happiness, and sadness.
Behavior and emotions of older adults
It's important to develop user-friendly products and services to assist older people in daily activities and improve their quality of life. Therefore researchers wanted to find out if TV footage could motivate older persons to start being more active? Being active can improve the overall health of a person (65+ but of course also 65-!).
Read the full blog post on research projects on behavior and emotions of older adults .
On-site observational studies with older persons
In certain cases, observations for your study are best performed on-site. There are many examples of observational studies with older age groups, conducted at home or at a healthcare facility. We've highlighted two examples of on-site observational studies with older persons .
Robots helping people with dementia
Behavioral and psychological problems affect most individuals with dementia at some point during the progression of the disorder. Researchers explored if the use of a robotic seal as a therapeutic tool would influence the emotional and behavioral symptoms of dementia.
Find out more about this large study on robotic pets here !
Find out how The Observer XT is used in a wide range of studies and how it can elevate your research!
- Free white papers and case studies
- Customer success stories
- Recent blog posts
More topics in developmental psychology
Of course there are many more topics in developmental psychology. An overview of the research topics can include:
- Cognitive development: Piaget's theory, information processing, and language development
- Social and emotional development: attachment theory, moral development, self-concept and identity formation
- Physical development: motor skills, sensory development, growth and maturation
- Perceptual development: visual perception, object permanence, perceptual constancy
- Personality development: nature vs. nurture debate, temperament, self-esteem and resilience
- Contextual factors in development: the role of culture, family, peers, media and technology
- Adolescent development: puberty, identity formation, moral reasoning and decision-making
- Lifespan development: aging, retirement, end-of-life issues
- Education and development: learning theories, early childhood education, motivation and engagement in school
- Neurodevelopmental disorders: ADHD, autism , or dyslexia.
These articles might interest you as well:
- How to study human behavior
- Learn about people's behavior by observing them
- Examples of human behavior research
- Behavioral coding: What and how
- Five studies showing the power of multi-modal data in behavioral research
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Developmental Psychology Commons ™
Based on downloads in June 2023
Generation Z'S Positive And Negative Attributes And The Impact On Empathy After A Community-Based Learning Experience , Amanda Nicole Moscrip University of North Florida
Generation Z'S Positive And Negative Attributes And The Impact On Empathy After A Community-Based Learning Experience , Amanda Nicole Moscrip
Unf graduate theses and dissertations.
Generation Z, also known as the iGeneration, iGenners, GenZ, and Generation Now, consists of those born in the mid-1990s through the late 2010s. Historical events important for this generation have influenced their perception of safety as well as how they interact with others. As compared to previous generations, technological advances (i.e., Smartphones, social media) changed how GenZ communicates, socializes, and receives information. Unique experiences and attributes influenced Generation Z’s empathy because living through these events and seeing their impact changes how they can understand and take the perspective of others. The relation between three factors was examined across University students …
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Exploring How Student Athletes Balance Athletic, Academic, And Personal Needs Through Learned Needs Theory. , Michael E. Rutledge II Louisiana State University
Exploring How Student Athletes Balance Athletic, Academic, And Personal Needs Through Learned Needs Theory. , Michael E. Rutledge Ii
Journal of research initiatives.
The attempt to balance the requirements of athletic and academic demands prompts extensive research agendas from higher education and athletic stakeholders to examine how extrinsic and socio-environmental factors affect the desired outcomes of student athletes. Reputable motivation literature describes needs as the starting point of motivation and influences behaviors embedded within cultural and systematic structures. Thus, the purpose of this study is to understand how sport participation influences athletic and academic performance through Learned Needs Theory (LNT). This study provides insight to processes of motivation that contribute to knowledge, practical implications, and research that translates to research-based approaches to increase …
The Impact Of Social Media On The Self-Esteem Of Youth 10–17 Years Old: A Review Of The Literature , Jasmine M. Daniels National Louis University
The Impact Of Social Media On The Self-Esteem Of Youth 10–17 Years Old: A Review Of The Literature , Jasmine M. Daniels
The world of technology has expanded quickly and vastly since its inception. The creation of social media sites and applications has changed the ways in which youth interact, connect, and share with one another. As the number of social media sites and applications increases, so does their use by adolescents. During adolescence, youth are undergoing the process of identity development and self-esteem is an important part of this development. During this developmental period, adolescents’ self-esteem is likely to be affected by the feedback they receive online through social media sites. There is limited research available that specifically evaluated the impact …
The Evolution Of Disney Princesses And Their Effect On Body Image, Gender Roles, And The Portrayal Of Love , Rachael Michelle Johnson James Madison University
The Evolution Of Disney Princesses And Their Effect On Body Image, Gender Roles, And The Portrayal Of Love , Rachael Michelle Johnson
Educational specialist, 2009-2019.
The media plays an essential role in determining people’s schemas of the real world, assumptions about cultural ideals, and perceptions surrounding body image, gender roles, and the idealization of love (Behm-Morawitz & Mastro, 2008; Herbozo, Tantleff-Dunn, Gokee-Larose, & Thompson, 2004). Children in particular are vulnerable to these messages due to their high consumption of media and their cognitive development (Agarwal & Dhanasekaran, 2012; Herbozo et al., 2004). Disney is one the most powerful aspects in children’s media and their princess phenomenon plays an essential role in perpetuating stereotypes by having their heroines embody submissiveness, being young and thin, and attracting …
The Developmental Effects On The Daughter Of An Absent Father Throughout Her Lifespan , Carlee Castetter Merrimack College
The Developmental Effects On The Daughter Of An Absent Father Throughout Her Lifespan , Carlee Castetter
Honors senior capstone projects.
Fatherless households are becoming increasingly common throughout the United States. As a result, more and more children are growing up without the support of both parents, and this may be causing developmental consequences. While there has been significant research conducted on the effect of absent fathers on children in general, there has been far less research regarding girls specifically. As discovered in this paper, girls are often impacted differently than boys when it comes to growing up without a father. The current research paper aims to discover just exactly how girls are impacted by this lack of a parent throughout …
Effect Of Parenting Styles On Children's Emotional And Behavioral Problems Among Different Ethnicities Of Muslim Children In The U.S. , Noor A. Rosli Marquette University
Effect Of Parenting Styles On Children's Emotional And Behavioral Problems Among Different Ethnicities Of Muslim Children In The U.S. , Noor A. Rosli
Dissertations (1934 -).
Parenting styles create different social environments in the lives of children within the home. Many studies have investigated the effects of parenting style on children's emotional development and behavior (Liem, Cavell, & Lustig, 2010; Pezzella, 2010; Schaffer, Clark, & Jeglic, 2009; Steward & Bond, 2002; Timpano, Keough, Mahaffey, Schmidt, & Abramowitz, 2010) as well as differences in parenting across cultures (Keels, 2009; Paulussen-Hoogeboom, Stams, Hermanns, Peetsma, &Wittenboer, 2008). Limited research has been conducted on parenting style and religion, however, and especially in Muslim families, and among Muslim American families in particular. There is also a lack of research that focuses …
The Effect Of Social Media On The Physical, Social Emotional, And Cognitive Development Of Adolescents , Aaron Bryant Merrimack College
The Effect Of Social Media On The Physical, Social Emotional, And Cognitive Development Of Adolescents , Aaron Bryant
This paper explores the possible problems that the usage of social media can have on the physical, social emotional, and cognitive development of adolescents. Adolescence is such a crucial and vulnerable stage in development, where teenagers begin to form their own identity and create meaningful relationships, but social media can have a profound effect on areas of their development. Social media offers new opportunities and challenges for adolescents more today as a generation than ever before. Issues regarding body image, academic achievement, and self-esteem and the connection to social media usage is reported. The issue of cyberbullying and its connection …
Parental Influences On Children’S Decisions Making , Karinna Anne Rodriguez University of North Florida
Parental Influences On Children’S Decisions Making , Karinna Anne Rodriguez
There is currently not enough research that focuses on parental influences on children’s development of decision making in early childhood. During early childhood children are primarily situated in the family context and are likely learning about decision making through their interactions with parents. Previous research has suggested children begin to develop complex decisions-making skills in early childhood. Complex decision-making includes the ability to consider the future and social benefits for the self and others. Future-oriented decisions requires the difficult task of deliberating between sacrificing an instant reward for a larger reward in the future, while social-oriented decisions require the consideration …
Using Toys To Support Infant-Toddler Learning And Development , Gabriel Guyton Bank Street College of Education
Using Toys To Support Infant-Toddler Learning And Development , Gabriel Guyton
All faculty and staff papers and presentations.
Being mindful of the basic principles of child development and the role of play, teachers can intentionally select toys to meet young children's unique needs and interests, supporting learning.
The Importance Of Nutrition For Development In Early Childhood , Kaitlyn Sue Suha California State University - San Bernardino
The Importance Of Nutrition For Development In Early Childhood , Kaitlyn Sue Suha
Electronic theses, projects, and dissertations.
Understanding which foods contain the necessary vitamins and nutrients for a child’s health, and which ones are lacking, can decrease the likelihood of children developing nutritional deficiencies and promote their overall developmental health. It is important for parents of young children to have an understanding of nutrition and the effect that poor nutrition can have. this project presented information sessions to parents to educate them further about these important topics through four weekly online workshops. Participants were asked to complete a pre- and post-session survey. Survey results scores indicated that participants reported an increase in knowledge and understanding in regards …
All Articles in Developmental Psychology
3,920 full-text articles. Page 1 of 162 .
The Non-Standardization Of Attention Deficit Hyperactive Disorder: A Call To Action , Gabriel L.S Gomez 2024 Eastern Kentucky University
The Non-Standardization Of Attention Deficit Hyperactive Disorder: A Call To Action , Gabriel L.S Gomez
Psychology doctoral specialization projects.
Attention Deficit Hyperactive Disorder (ADHD) is one of the most diagnosed disorders in adults and children, yet there is no standardized method to assess for ADHD. The similarity of symptoms shared across other disorders (comorbidity) makes the assessment of ADHD a very delicate process. This is not aided by the fact that the assessment of ADHD is not standardized. This allows individuals able to assess for ADHD to give a test or a combination of tests that they find fitting. This in turn brings into question the quality of testing and disagreement in diagnosing across fields. Lastly, ADHD-focused measures typically …
Student-Athlete Mental Health: University Of Montana Case Study , Abigail M. Sherwood 2024 University of Montana
Student-Athlete Mental Health: University Of Montana Case Study , Abigail M. Sherwood
Undergraduate theses, professional papers, and capstone artifacts.
Research suggests that Division I college-student athletes experience higher levels of stress and other behavioral health issues than their non-athlete counterparts, with up to 20% of them suffering from depression (Sudano et al., 2017). Two studies on student athletes’ well-being conducted in 2020, reported that athletes continue to report higher levels of mental health concerns (Johnson, 2022). Since the fall of 2020, rates of mental exhaustion, depression, and anxiety have improved minimally with rates remaining 1.5 to two times higher than reported before the COVID-19 pandemic (Johnson, 2022). Naomi Osaka withdrawing from the French Open in 2021 and Simone Biles …
Predictors Of Canadians’ Psychological Well-Being In Retirement: A Mixed Methods Approach , Jessica Miller 2024 Wilfrid Laurier University
Predictors Of Canadians’ Psychological Well-Being In Retirement: A Mixed Methods Approach , Jessica Miller
Theses and dissertations (comprehensive).
In prior decades, retirement research focused on the negative effects of the life transition—such as negative psychological well-being caused by factors such as difficulties adjusting to retirement, feelings of a role loss, or the financial effects of retirement. However, there is considerable agreement across recent research studies that post-retirement years are marked by positive psychological well-being due to a variety of factors. For example, retirees often spend more time in roles (such as volunteer positions) that provide life satisfaction. The present study uses both quantitative and qualitative methods to examine factors related to well-being in retirement among individuals living in …
Repeated Treatment With 5-Ht1a And 5-Ht1b Receptor Agonists: Evidence Of Tolerance And Behavioral Sensitization , Jordan Taylor 2023 California State University, San Bernardino
Repeated Treatment With 5-Ht1a And 5-Ht1b Receptor Agonists: Evidence Of Tolerance And Behavioral Sensitization , Jordan Taylor
Serotonin has been found to regulate several cognitive and physiological functions, and its role in depression and other neuropsychiatric disorders has been a focus of research. More specifically, a wealth of research regarding serotonin focuses on serotonergic medications in the treatment of neuropsychiatric disorders, such as depression and anxiety, and stimulates the 5-HT 1A and 5-HT 1B receptors. Within the last decade, there has been an increase in prescriptions of psychotropic medication for children, however, the efficacy and adverse effects of these drugs have not been evaluated in younger populations. While antidepressants reduce symptoms of depression in adults, they are …
Not All Numbers Were Created Equal: Evidence The Number One Is Unique , Jenna L. Croteau 2023 University of Massachusetts Amherst
Not All Numbers Were Created Equal: Evidence The Number One Is Unique , Jenna L. Croteau
Universally across modern cultures children acquire the meaning of the words one, two, and three in order. While much research has focused on how children acquire this knowledge and what this knowledge represents, the question of why children learn numbers in order has been comparatively neglected. To address this question , a non-verbal anticipatory looking task was implemented. In this task, 35 14- to 23-month-old infants were assessed on their ability to form implicit category structures for the numbers one, two, and three. We hypothesized that children would be able to form the implicit category structure for the number one …
The Ritual Of Therapeutic Artmaking In Long-Term Care , Melinda Heinz Dr., Elissa Wenthe, Alexis Schramel 2023 Upper Iowa University
The Ritual Of Therapeutic Artmaking In Long-Term Care , Melinda Heinz Dr., Elissa Wenthe, Alexis Schramel
International journal of lifelong learning in art education.
The transition to long-term care settings can be difficult for residents and feelings of loneliness, depression, and anxiety are not uncommon in these environments. However, participating in therapeutic artmaking rituals creates opportunities for residents to process their feelings, experience states of flow and mindfulness, engage with others, and focus on their own psychological growth. In long-term care, the physical needs of residents are often prioritized, but psychosocial needs also require attention. For this project, therapeutic artmaking rituals were created at a long-term care facility in three levels of care over 12 months. Older adults engaged with clay, paint, raw fiber, …
The Effectiveness Of Computerized Neurofeedback As An Accompanying Or Alternative Therapeutic Intervention For Pharmacological Treatment In Improving Attention And Other Symptoms For Children With Attention Deficit Hyperactivity Disorder (Adhd) , Eqbal Z. Darandari PhD, Nouf F. Alsultan 2023 King Saud University
The Effectiveness Of Computerized Neurofeedback As An Accompanying Or Alternative Therapeutic Intervention For Pharmacological Treatment In Improving Attention And Other Symptoms For Children With Attention Deficit Hyperactivity Disorder (Adhd) , Eqbal Z. Darandari Phd, Nouf F. Alsultan
International journal for research in education.
This study aimed to investigate the effectiveness of a treatment program using computerized neuro-feedback in improving attention for children with attention deficit hyperactivity disorder (ADHD). To achieve the aim of the study, the computerized neurofeedback program was applied to (56) children diagnosed with (ADHD), aged between (7-11) years. They were distributed into four groups: the first group was subjected to combined intervention (neurofeedback & pharmacological treatment), the second group was subjected to (neurofeedback only), while the third group was exposed to the intervention using (pharmacological treatment only), and the fourth group was (not exposed to any intervention). Test of Variables …
Developmental Assets And Community-Based Youth Programs In Colombia, Guatemala, And Honduras , Claire M. de Mezerville-López 2023 International Institute for Restorative Practices
Developmental Assets And Community-Based Youth Programs In Colombia, Guatemala, And Honduras , Claire M. De Mezerville-López
Journal of youth development.
This paper explores the external developmental assets and how they manifest in specific youth programs from Colombia, Guatemala, and Honduras. An evaluation process was created through a qualitative phenomenological with the youth programs' leadership. To triangulate the data, a survey was developed and piloted with a small sample from three youth programs, one from Honduras, one from Guatemala and one from Colombia, exploring how the staff evaluate items related with the external developmental assets. This survey was created in a way that the results display in the form of a Spiderweb and in a circular way that evokes and relates …
Book Review It Takes An Ecosystem: Understanding The People, Places, And Possibilities Of Learning And Development Across Settings , Denise Montgomery 2023 CultureThrive
Book Review It Takes An Ecosystem: Understanding The People, Places, And Possibilities Of Learning And Development Across Settings , Denise Montgomery
It Takes an Ecosystem: Understanding the People, Places, and Possibilities of Learning and Development Across Settings, edited by Thomas Akiva and Kimberly H. Robinson, is a call to take a holistic and dynamic ecosystem approach to thinking about, designing, developing, and investing in the allied youth fields to more equitably and effectively support young people’s learning and development. Published in 2022, the volume outlines a vision for out-of-school time programs and systems, schools, community-based organizations, and the public sector to move beyond focusing separately on individual systems to a learning and development ecosystem approach that more accurately and inclusively reflects …
Mentoring In Group-Based Adolescent Girl Programs In Low- And Middle-Income Countries: Evidence-Informed Approaches , Miriam Temin, Sarah Blake, Eva Roca 2023 Independent Consultant
Mentoring In Group-Based Adolescent Girl Programs In Low- And Middle-Income Countries: Evidence-Informed Approaches , Miriam Temin, Sarah Blake, Eva Roca
No abstract provided.
Table Of Contents , 2023 Clemson University
Table Of Contents
Supporting Staff Supports Youth Well-Being At Summer Camp , Robert P. Lubeznik-Warner, Nila Rosen 2023 University of Utah
Supporting Staff Supports Youth Well-Being At Summer Camp , Robert P. Lubeznik-Warner, Nila Rosen
Youth well-being is of central importance, now, perhaps more than ever before. In the wake of the covid pandemic, youth need emotional support and connection throughout the academic year and summer months. Camp is a primary method of summer programming in America and thus may be an important conduit for mental, emotional, social, and spiritual health for youth during the summer. Camp staff may be one mechanism for supporting youth well-being; however, relatively little is known about the relationship between camp staff well-being and youth camper well-being. To address this gap, this study used secondary cross-sectional data collected by a …
Trauma-Informed Youth Sport: Identifying Program Characteristics And Challenges To Advance Practice , Kayla Hussey, Lindsey C. Blom, Zenzi Huysmans, Dana Voelker, Matt Moore, Thalia M. Mulvihill 2023 West Virginia University
Trauma-Informed Youth Sport: Identifying Program Characteristics And Challenges To Advance Practice , Kayla Hussey, Lindsey C. Blom, Zenzi Huysmans, Dana Voelker, Matt Moore, Thalia M. Mulvihill
This purpose of this qualitative study was to explore shared characteristics and local challenges of trauma-informed youth sport program design and implementation through the voices of ten program facilitators (e.g., director, trainer; 8 women, 2 men; average age of 36.2 years, SD = 6.03) across four U.S. regions. Within a postpositivist approach and through thematic analysis of semi-structured interviews (average length of 53 minutes), shared characteristics identified by facilitators included promoting a safe and supportive environment, cultivating healthy relationships among adults and peers, and intentional psychological and social skill-building (e.g., attentional cues). Facilitators also explained the importance of understanding the …
Students' Attitudes Towards Animals Influences Youth Development Constructs Based On Interactions With Different Animal Species Prior To College , Allison K. Pachunka 2023 University of Nebraska-Lincoln
Students' Attitudes Towards Animals Influences Youth Development Constructs Based On Interactions With Different Animal Species Prior To College , Allison K. Pachunka
Department of animal science: dissertations, theses, and student research.
Human-animal interactions (HAI) are commonplace in society and play a consequential role in a variety of situations such as companion animal ownership, agriculture, or youth programs such as 4-H or FFA. Interacting with animals has been shown to provide developmental benefits to children. Positive youth development (PYD), measured by the Five Cs Model, is a framework that focuses on fostering youth’s potential through positive activities which has been studied specifically in 4-H. However, this framework has not been applied to other organizations such as the National FFA Organization (FFA) or to other young adults with less formal interactions with animals. …
Embracing Virtual Reality Technology With Black Adolescents To Redress Police Encounters , Danielle M. Olson, Tyler Musgrave, Divya Gumudavelly, Chardee Galan, Sarita Schoenebeck, D. Fox Harrell, Riana E. Anderson 2023 Massachusetts Institute of Technology
Embracing Virtual Reality Technology With Black Adolescents To Redress Police Encounters , Danielle M. Olson, Tyler Musgrave, Divya Gumudavelly, Chardee Galan, Sarita Schoenebeck, D. Fox Harrell, Riana E. Anderson
As Black youth face race-related stress from personal and vicarious experiences with police, practices advancing youth’s coping self-efficacy and agency are needed. We describe the pilot of a program supporting Black adolescents in creating virtual narratives detailing encounters and resolutions with police and offer preliminary observations of how this program could facilitate racial coping and emotional support. The program included four weeks consisting of both curriculum-based instruction and hands-on activities, four weeks solely focused on designing and developing students’ projects, and one week devoted to students’ final project presentations and peer feedback. We utilized a participatory design to co-create narratives …
A Transdiagnostic Examination Of Cognitive Heterogeneity In Children And Adolescents With Neurodevelopmental Disorders , Sarah Al-Saoud, Emily S. Nichols, Emma G. Duerden, Loretta Norton 2023 Western University
A Transdiagnostic Examination Of Cognitive Heterogeneity In Children And Adolescents With Neurodevelopmental Disorders , Sarah Al-Saoud, Emily S. Nichols, Emma G. Duerden, Loretta Norton
Western libraries undergraduate research awards (wluras).
Children and adolescents with neurodevelopmental disorders (NDDs) demonstrate extensive cognitive heterogeneity that is not adequately captured by traditional diagnostic systems. Using a transdiagnostic approach, a retrospective cohort study of cognitive functioning was conducted with a large heterogenous sample ( n = 1529) of children and adolescents 7 to 18 years of age with NDDs. Measures of short-term memory, verbal ability, and reasoning were administered to participants with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), comorbid ADHD/ASD, and typically developing (TD) participants using a 12-item web-based neurocognitive testing battery. Unsupervised machine learning techniques were implemented to create a self-organizing map (SOM), …
How Teachers Use Data: Description And Differences Across Prek Through Third Grade , Amanda Witte, Lisa Knoche, Susan Sheridan, Natalie A. Koziol 2023 University of Nebraska-Lincoln
How Teachers Use Data: Description And Differences Across Prek Through Third Grade , Amanda Witte, Lisa Knoche, Susan Sheridan, Natalie A. Koziol
Nebraska center for research on children, youth, families, and schools: faculty publications.
The use of data to inform instruction has been linked to improved student outcomes, early identification of intervention needs, and teacher decision-making and efficacy. Additionally, data are used as a means of accountability within educational settings. However, little is known about data use practices among early grades teachers. The purpose of the current study is to describe the data use of PreK to third grade teachers and to investigate differences in data use and support across grade levels. Participants were 307 early childhood teachers in PreK and early elementary school. Analysis of survey data revealed, overall, most teachers across grade …
Mind, Body And Race: A Look Into How Implicit Biases Influence The Perception Of Emotion , Faiza Ahmad, Adam Anderson, James Dalton Rounds, Christina Chick, Alize Hill 2023 The University of Texas Rio Grande Valley
Mind, Body And Race: A Look Into How Implicit Biases Influence The Perception Of Emotion , Faiza Ahmad, Adam Anderson, James Dalton Rounds, Christina Chick, Alize Hill
Background: Most research examining the effects of implicit race-based biases in emotion perception has focused on the perception of Black faces as being angry. Limited work has been done examining the perception of “approach” emotions such as fear. Furthermore, most studies have predominantly used White subjects. Our study examined the role of implicit racial biases in shaping the perception of both anger and fear in White, Black and Asian participants.
Methods: 78 participants completed a Go/NoGo task in which they were asked to categorize different race faces as portraying either anger or fear. Participants would be asked to press the …
White Men In White Coats: Children’S Attributions Of Scientific Knowledge Based On Race And Gender , Lillian C. Holm, Mariel R. Cox, Khushboo S. Patel, Judith H. Danovitch 2023 University of Louisville
White Men In White Coats: Children’S Attributions Of Scientific Knowledge Based On Race And Gender , Lillian C. Holm, Mariel R. Cox, Khushboo S. Patel, Judith H. Danovitch
The cardinal edge.
Children use others’ characteristics (e.g., intelligence and niceness) to evaluate how much a person knows (Landrum et al., 2016). However, little is known about how gender and race influence children's perception of adults' scientific knowledge. The current study examined how children ages 5-8 (N = 25; 11 girls, 14 boys) perceive adults’ scientific knowledge. In the first task, children saw 8 different adults of varying race and gender (White man, White woman, Black man, Black woman) and rated their knowledge using a five-point scale. Children then chose one person out of two adults who they thought knew more about a …
The Resilient Families Project @ Wayside’S Hotel Louisville: Strategies For Building Resilience, Mindfulness & Happiness In At-Risk Adults , Lexi N. Frederick, Hannah Parker, Angela Ely, Lora Haynes 2023 University of Louisville
The Resilient Families Project @ Wayside’S Hotel Louisville: Strategies For Building Resilience, Mindfulness & Happiness In At-Risk Adults , Lexi N. Frederick, Hannah Parker, Angela Ely, Lora Haynes
The Resilient Families Project (RFP) provides educational experiences to strengthen evidence-based habits of resilience, mindfulness, and happiness in at-risk individuals. RFP holds programs for adults facing homelessness and women in drug/alcohol recovery who are housed by Wayside Christian Mission in their Emergency Shelter or Hotel Louisville.
RFP programs work to promote healthy attachment relations, a sense of belonging/purpose, and interactive reading, and children’s storybooks serve as the foundation for designing programs. The book “The Boy, The Mole, The Fox, and The Horse'' was reviewed through content analysis to emphasize diversity, equity, and inclusion, as well as RFP Core Ideas. Thanks …
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Developmental Psychology Studies: 10 Examples
Discover ten classic developmental psychology experiments that study how children’s self, memory, language, learning and more emerge.
Once upon a time, although it seems barely credible to us now, we were all children.
We gurgled, we cried, we laughed, we explored, we fell down, and we had very little idea about the journey on which we had just embarked.
Barring mishap, over the first few years of our lives we developed memory, language, self-concept, cognitive, social and emotional abilities.
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We took our first steps towards our future selves.
Child psychology — or, more broadly, developmental psychology — is not just the study of children, it is the study of you and me and how we came to be this way.
Just as discovering your history can teach you about the future, so developmental psychology shows us what we once were and even what we will become.
Here are 10 classic developmental psychology studies that have illuminated crucial areas of childhood development.
Each one is a piece in the jigsaw puzzle that is ourselves, and each one reminds us, through examining just one piece, how aspects of experience we now take for granted were once so complex.
Click the links for a more extensive description of each developmental psychology experiment.
1. Infant memory develops very early on
Some argue it’s impossible for us to remember anything much from before around two to four years of age.
Others think our memories can go way back – perhaps even to before birth.
The question of infant memory is thorny because it’s hard to test whether adults’ earliest memories are real or imagined.
What psychologists have done, though, is examine the emergence of memory in our first few years with a series of now classic experiments in developmental psychology.
These have found that our memory systems actually work quite well from very early on.
Infants’ memories also seems to work in much the same way as adult memories – it’s just that infant memories are much more fragile.
2. Developmental psychology: when the self emerges
To this day the ‘mirror test’ remains the best developmental psychology experiment yet developed for examining the emergence of self-concept in infants using the mirror test .
Most people look out for number one, themselves, which makes it strange to think that there was ever a time when we had no concept of ‘me’.
A simple study dating from the early 70s suggests that before the age of around two years old we can’t recognise ourselves in the mirror.
Because of this study, and the many variations in developmental psychology that have followed, some claim that it isn’t until our second birthday that our self-concept emerges.
3. How children learn
A classic study of childhood learning suggests true understanding comes from letting go of established preconceptions.
How children revise their understanding of the world is one of the most fascinating areas of developmental psychology.
But it is not just relevant to children; we all have to take on new concepts from time-to-time – even though they may not be as profound as the origin of the species.
It’s tempting to think that learning is largely about memory – especially since in the bad old days of education learning was largely accomplished by rote.
However, the idea of ‘mental models’ suggests children create, and then test, mental models of the way the world works in order to build up our understanding, and that is how children learn.
4. Attachment styles in developmental psychology
Attachment styles analyse how people respond to threats and problems in their personal relationships.
People who find relationships difficult often become unable to participate in the ordinary give-and-take of everyday life.
They may become hostile towards others, have problems in education as well as a greater chance of developing psychiatric disorders later in life.
These difficulties sometimes have their roots in the most important early relationships, evidenced in attachment styles.
It’s no wonder that developmental psychologists are so interested in the first relationships we build with our primary caregivers.
These attachment styles are likely to prove a vital influence on all our future relationships, including those with our spouse, our workmates and our own children.
While you can’t blame everything on your parents, early relationship attachment styles are like a template that we take forward with us in life.
5. Infants imitate others when only weeks old
One of the most basic forms of social behaviour is copying another person.
Although imitation is something we adults take for granted, it’s actually a pretty demanding process for a young infant.
At the heart of imitation is understanding the difference between yourself and others – something that famous Swiss child psychologist Jean Piaget thought didn’t emerge immediately in infants.
Consequently, he argued that infants could not imitate others until they were 8 to 12 months of age.
However, now some researchers think tiny infants who are between 12- and 21-days-old can imitate others.
6. When children can simulate other minds
Theory of mind is when we can put ourselves in other people’s shoes to try and imagine their thoughts, intentions and possible actions.
Without the ability to simulate what other people are thinking we would be lost in the social world.
The emergence of theory of mind in children is a vital developmental milestone; some psychologists think that a failure to develop a theory of mind is a central component of autism.
Some developmental psychology experiments suggest that at about 4- to 6-years old a range of remarkable skills start to emerge in young children that are vital for their successful functioning in society.
They begin to understand that others can hold false beliefs, they themselves can lie, and that others can lie to them — they have a theory of mind.
7. Object permanence in developmental psychology
Object permanence , or object constancy, in developmental psychology is understanding that things continue to exist, even if you cannot seem them.
Research in developmental psychology has found that infants as young as 3.5 months seem to have a basic grasp of object permanence.
It appears that young infants are not necessarily trapped in a world of shapes which have little meaning for them.
Instead, they seem to be intuitive physicists who can carry out rudimentary reasoning about physical concepts like gravity, inertia and object permanence.
8. How infants learn their first word
An infant’s very first step in their year-long developmental journey to their first word is perhaps their most impressive.
This first step is discriminating and categorising the basic sound components of the language they are hearing.
To get an idea how hard this might be think about listening to someone speaking a language you don’t understand.
Foreign languages can sound like continuous streams of noise in which it’s very hard to pick up where one word starts and another word begins.
Research in developmental psychology finds that until about 11 months of age infants are masters of discriminating phonemes used in all different types of languages.
But after 11 months infants settle down with one set of phonemes for their first language, and lose the ability to discriminate the phonemes from other languages.
9. Play and developmental psychology
The pioneering developmental psychologist Lev Vygotsky thought that, in the preschool years, play is the leading source of development.
Through play children learn and practice many basic social skills.
They develop a sense of self, learn to interact with other children, how to make friends, how to lie and how to role-play.
The classic developmental psychology study of how play develops in children was carried out by Mildred Parten in the late 1920s at the Institute of Child Development in Minnesota ( Parten, 1933 ).
She closely observed children between the ages of 2 and 5 years and categorised the types of play.
She found six different types of play , ranging from solitary, through associative to cooperative
10. Piaget’s developmental psychology theory
Jean Piaget was a developmental psychologist whose four-stage theory, published in 1936, has proved extremely influential.
Piaget’s four stages of development theory has the dubious claim to fame of being one of the most criticised psychological theories ever.
From the sensorimotor stage, through the pre-operational stage, the concrete operational stage and the formal operational stage, his theory attempts to describe how childhood development progresses.
However, Piaget’s experiments and theories about how children build up their knowledge of the world have faced endless challenges, many of them justified.
Read on about them here .
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This site is all about scientific research into how the mind works.
It’s mostly written by psychologist and author, Dr Jeremy Dean.
I try to dig up fascinating studies that tell us something about what it means to be human.
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Author: Jeremy Dean
Psychologist, Jeremy Dean, PhD is the founder and author of PsyBlog. He holds a doctorate in psychology from University College London and two other advanced degrees in psychology. He has been writing about scientific research on PsyBlog since 2004. He is also the author of the book "Making Habits, Breaking Habits" (Da Capo, 2013) and several ebooks. View all posts by Jeremy Dean
Advancing Human Assessment pp 453–486 Cite as
Research on Developmental Psychology
- Nathan Kogan 5 ,
- Lawrence J. Stricker 5 ,
- Michael Lewis 6 &
- Jeanne Brooks-Gunn 7
- Open Access
- First Online: 18 October 2017
Part of the Methodology of Educational Measurement and Assessment book series (MEMA)
Developmental psychology was a major area of research at ETS from the late 1960s to the early 1990s. This work was a natural extension of the programs in cognitive, personality, and social psychology that had begun shortly after the organization’s founding in 1947, consistent with Henry Chauncey’s vision of investigating intellectual and personal qualities. This chapter covers research on representational competence; parental influences, migration, and measurement; cognitive, personality, and social development of infants and young children; and cognitive, personality, and social development from infancy to adolescence.
- Representational Competence
- Paper Folding Task
- Teaching Parents Behavior
- Young childrenYoung Children
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Developmental psychology was a major area of research at ETS from the late 1960s to the early 1990s, a natural extension of the work in cognitive, personality, and social psychology that had begun shortly after the organization’s founding in 1947, consistent with Henry Chauncey’s vision of investigating intellectual and personal qualities (see Stricker, Chap. 13 , this volume). For a full understanding of these qualities, it is essential to know how they emerge and evolve. Hence the work in developmental psychology complemented the efforts already under way in other fields of psychology.
A great deal of the research in developmental psychology was conducted at ETS’s Turnbull Hall in the Infant Laboratory , equipped with physiological recording equipment and observation rooms (e.g., Lewis 1974 ), and in a full-fledged Montessori school outfitted with video cameras (e.g., Copple et al. 1984 ). Hence, as Lewis ( n.d .) recalled, the building “had sounds of infants crying and preschool children laughing” (p. 4). Other research was done in homes, schools, and hospitals, including a multisite longitudinal study of Head Start participants (e.g., Brooks-Gunn et al. 1989 ; Laosa 1984 ; Shipman 1972 ).
A handful of investigators directed most of the research, each carrying out a distinct program of extensive and influential work. This chapter covers research by Irving Sigel , on representational competence ; Luis Laosa, on parental influences , migration , and measurement ; Michael Lewis, on cognitive, personality, and social development of infants and young children ; and Jeanne Brooks-Gunn, on cognitive, personality, and social development from infancy to adolescence. Other important research was conducted by Gordon Hale (e.g., Hale and Alderman 1978 ), on attention; Walter Emmerich (e.g., Emmerich 1968 , 1982 ), on sex roles and personality development ; and Nathan Kogan (e.g., Wallach and Kogan 1965 ) and William Ward (e.g., Ward 1968 ), on creativity . (The Kogan and Ward research is included in Kogan, Chap. 14 , this volume.) In the present chapter, Kogan describes Sigel’s research, and Stricker takes up Laosa’s ; Lewis and Brooks-Gunn discuss their own work.
1 Representational Competence and Psychological Distance
Representational competence was the focus of Sigel’s research program. Roughly defined by Sigel and Saunders ( 1983 ), representational competence is the ability to transcend immediate stimulation and to remember relevant past events and project future possibilities. Also indicative of representational competence in preschoolers was the understanding of equivalence in symbol systems, whereby an object could be rendered three-dimensionally in pictorial form and in words.
The level of a child’s representational competence was attributed in large part to parental beliefs and communicative behaviors and to family constellation (number of children and their birth order and spacing). Earlier research by Sigel and collaborators emphasized ethnicity and socioeconomic status (SES ; see Kogan 1976 ). SES was retained in many of the ETS studies in addition to a contrast between typical children and those with communicative–language disabilities .
A conceptual model of the Sigel team’s research approach is presented in a chapter by McGillicuddy-DeLisi et al. ( 1979 ): Mothers’ and fathers’ backgrounds determined their parental belief systems. Belief systems, in turn, influenced parental communication strategies, which then accounted for the child’s level of cognitive development . It was a nonrecursive model, the child’s developmental progress (relative to his or her age) feeding back to alter the parental belief systems. In terms of research design, then, parental background was the independent variable, parental belief systems and child-directed communicative behavior were mediating variables, and children’s representational competence was the dependent variable. The full model was not implemented in every study, and other relevant variables were not included in the model. In most studies, family constellation (e.g., spacing and number of children), SES , the nature of the parent–child interaction task, the child’s communicative status (with or without language disability ), and the gender of the parent and child were shown to yield main or interaction effects on the child’s representational competence.
In the view of Sigel and his associates, the critical component of parental teaching behavior was distancing (Sigel 1993 ). Parental teachings could reflect high- or low-level distancing. Thus, in a teaching context, asking the child to label an object was an example of low-level distancing, for the child’s response was constrained to a single option with no higher-thinking processes invoked in the answer. By contrast, asking the child to consider possible uses of an object was an example of high-level distancing, for the child was forced to go beyond the overt stimulus properties of the object to adopt new perspectives toward it. In brief, the concept of distancing, as reflected in parental teaching behavior, referred to the degree of constraint versus openness that the parent imposed on the child. Sigel’s principal hypothesis was that higher-level distancing in child-directed communication by an adult would be associated with greater representational competence for that child. Correspondingly, low-level distancing by an adult would inhibit the development of a child’s representational competence.
An additional feature of Sigel’s research program concerned the nature of the task in the parent–child interaction. Two tasks were selected of a distinctively different character. For the storytelling task, age-appropriate edited versions of children’s books were used, with parents instructed to go through a story as they typically would do at home. The other task required paper folding, with the parent required to teach the child to make a boat or a plane.
1.1 Influence of Parental Beliefs and Behavior on Representational Competence
Having outlined the conceptual underpinning of Sigel’s research program along with the nature of the variables selected and the research designs employed, we can now proceed to describe specific studies in greater detail. We begin with a study of 120 families in which the target child was 4 years of age (McGillicuddy-DeLisi 1982 ; Sigel 1982 ). Family variables included SES (middle vs. working class) and single-child versus three-child families. For the three-child families, there was variation in the age discrepancy between the first and second sibling (more than 3 years apart vs. less than 3 years apart), with the restriction that siblings be of the same sex. Each mother and father performed the storytelling and paper-folding tasks with their 4-year-old child. Proper controls were employed for order of task presentations. A total of 800 parent and child observations were coded by six raters with satisfactory interrater reliability .
The presentation of the research was divided into two parts, corresponding to the portion of the analytic model under investigation. In the first part (McGillicuddy-DeLisi 1982 ), the influence of the demographic variables, SES and family constellation, on parental beliefs was examined, and in turn the influence of parental beliefs for their prediction of overt parental behaviors in a teaching situation was explored. The second part, the child’s representational competence, was treated separately in the Sigel ( 1982 ) chapter. Note that the assessment of beliefs was focused exclusively on the parents’ views of how a preschool child acquired concepts and abilities, hence making such beliefs relevant to the parental strategies employed in facilitating the child’s performance in a teaching context.
Parental beliefs were assessed in an interview based on 12 vignettes involving a 4-year-old and a mother or father. The interviewer asked the parent whether the child in the vignette had the necessary concepts or abilities to handle the problem being posed. Further inquiry focused more generally on parents’ views of how children acquire concepts and abilities. Analysis of these data yielded 26 parental belief variables that were reliably scored by three coders. ANOVA was then employed to determine the influence of SES, family constellation, gender of child, and gender of parent on each of the 26 belief variables. Beliefs were found to vary more as a function of SES and family constellation than of gender of parent or child. More specifically, parents of three children had views of child development that differed substantially from those of single-child parents. For the parents of three children, development involved attributes more internal to the child (e.g., reference to self-regulation and impulsivity) as opposed to greater emphasis on external attributes (e.g., direct instruction) in single-child parents. The results as a whole constituted an intriguing mosaic, but they were post hoc in the absence of predictions derived from a theoretical framework . Of course, the exploratory nature of such research reflected the dearth at that time of theoretical development in the study of child-directed parental beliefs and behaviors.
Consider next the observed relationships between parental beliefs and teaching behaviors. Having shown that SES and family constellation influenced parental beliefs, the question of interest was whether such beliefs provided useful information about parents’ teaching behaviors beyond what might be predicted from SES and family constellation. To answer the question, stepwise regressions were carried out with SES and family constellation entered into the analysis first, followed by the belief variables. Separate regressions—four in all—were conducted for mothers’ and fathers’ performance on the storytelling and paper-folding tasks, the dependent variables.
Demonstration of belief effects on teaching behaviors would require that multiple correlations show significant increments in magnitude when beliefs were entered into the regression analysis. Such increments were observed in all four regressions, indicating that parents’ beliefs about their children’s competencies were predictive of the way they went about teaching their children on selected tasks. Noteworthy is the evidence that the significant beliefs varied across the two tasks and that this variation was greater for mothers than for fathers. In other words, mothers appeared to be more sensitive to the properties of the task facing the child, whereas fathers appeared to have internalized a set of beliefs generally applied to different kinds of tasks. Mothers would seem to have a more differentiated view of their children’s competencies and hence were more attuned to the nature of the task than were fathers.
Thus far, we have considered the relations among family demographics, parental beliefs, and teaching strategies. The missing link, the child’s cognitive performance, was examined in the Sigel ( 1982 ) chapter, where it was specifically related to parental teaching behaviors. The child’s responses to the storytelling and paper-folding tasks were considered (e.g., extent of engagement and problem solutions), as was the child’s performance on tasks independent of parental instructions. These latter tasks included Piagetian conservation and imagery assessments and the Sigel Object Categorization Task (Sigel and Olmsted 1970 ). The major hypothesis was that the parents’ uses of distancing strategies in their teaching behaviors would be associated with enhanced cognitive performances in their children—representational competence.
To address this hypothesis, stepwise regressions were analyzed. The results confirmed the basic hypothesis linking parental child-directed distancing to the child’s representational competence. This general observation, however, conceals the specificity of the effects. Thus mothers and fathers employed different teaching strategies, and these strategies, in turn, varied across the storytelling and paper-folding tasks. Of special interest are those analyses in which the mothers’ and fathers’ teaching behaviors were entered into the same regression equation. Doing so in sequence often pointed to the complementarity of parental influences . In concrete terms, the multiple correlations sometimes demonstrated significant enhancements when both parents’ teaching strategies entered into the analysis compared to the outcome for the parents considered separately. This result implied that the children could intellectually profit from the different, but complementary, teaching strategies of mothers and fathers.
1.2 Impact of a Communicative Disability
Sigel and McGillicuddy-DeLisi ( 1984 ) were able to recruit families who had a child with a communicative disability (CD), making it possible to compare such families with those where the child was not communicatively disabled (non-CD). It was possible to match the CD and non-CD children on SES , family size, gender, age, and birth order. Again, mothers’ and fathers’ distancing behaviors were examined in the task context of storytelling and paper folding.
In the case of the child’s intellectual ability, assessed by the Wechsler Preschool and Primary School Scale of Intelligence (WPPSI; Wechsler 1949b ), parental effects were largely confined to the CD sample. Low parental distancing strategies were tightly associated with lower WPPSI scores. Of course, we must allow for the possibility that the parent was adjusting his or her distancing level to the perceived cognitive ability of the child. In contrast, the child’s representational competence , as defined by the assessments previously described in Sigel ( 1982 ), was linked with parental distancing behaviors in both CD and non-CD samples, with the magnitude of the relationship somewhat higher in the CD sample.
Of course, these associations could not address the causality question: The parent might be affecting the child or reacting to the child or, more likely, the influence was proceeding in both directions. Sigel and McGillicuddy-DeLisi ( 1984 ) argued that low-level distancing strategies by parents discouraged active thinking in the child; hence it was no surprise that such children did not perform well on representational tasks that required such thinking. They were optimistic about CD children, for high-level parental distancing seemed to encourage the kind of representational thinking that could partially compensate for their communicative disabilities (Sigel 1986 ).
1.3 Belief-Behavior Connection
Working with a subsample of the non-CD families described in the previous section, Sigel ( 1992 ) plunged into the controversial issue of the linkage between an individual’s beliefs and actual behavior instantiating those beliefs. He also developed a measure of behavioral intentions—a possible mediator of the belief–behavior connection. Although the focus was naturally on parental beliefs and behaviors, similar work in social psychology on the belief and behavior connection (e.g., Ajzen and Fishbein 1977 ), where major advances in theory and research had occurred, was not considered.
Three categories of variables were involved: (a) parents’ beliefs about how children acquired knowledge in four distinct domains (physical, social, moral, and self); (b) the strategies that parents claimed they would use to facilitate the children’s acquisition of knowledge in those domains; and (c) the behavioral strategies employed by the parents in a teaching context with their children. The first two categories were assessed with a series of vignettes. Thus, in the vignette for the physical domain, the child asks the parent how to use a yardstick to measure the capacity of their bathtub. The parents’ view about how children learn about measurement constituted the belief measure; the parents’ statements about how they would help their child learn about measurement constituted the self-referent strategy measure. For the third category, the parents taught their child how to tie knots, and the strategies employed in doing so were observed. Note that the knots task involved different content than was used in the vignettes.
Parental beliefs regarding children’s learning were categorized as emphasizing cognitive processing (e.g., children figuring out things on their own) or direct instruction (e.g., children learning from being told things by adults). Parental intended teaching strategies were classified as distancing, rational authoritative (e.g., parent gives reasons with commands), or direct authoritative (e.g., parent offers statement or rule without rationale). Parental behavioral strategies were scored for high-level versus low-level distancing.
The three variable classes—parental beliefs, parental intended teaching strategies, and parental behavioral strategies—were intercorrelated. Substantial relationships were observed between parental beliefs about learning (cognitive processing vs. direct instruction) and the strategies the parent intended to employ. As anticipated, cognitive processing was associated with distancing strategies, and direct instruction was linked to authoritative strategies. Of course, both the beliefs and self-referent strategies were derived from the same vignettes used in the parental interview, suggesting the likely influence of method variance on the correlational outcomes. When the foregoing variables were related to the parents’ behavioral strategies in teaching the knots task, the magnitude of the correlations dropped precipitously, though the marginally significant correlations were in the predicted direction. Sigel ( 1992 ) attributed the correlational decline to variation across domains. Thus the belief–strategy linkages were not constant across physical, social, and moral problems. Aggregation across these domains could not be justified. Obviously, the shifting task content and context were also responsible for the absence of anticipated linkages. Conceivably, an analytic procedure in which parents’ intended strategies were cast as mediators between their beliefs and their behavioral strategies would have yielded further enlightenment.
1.4 Collaborative Research
The large majority of Sigel’s publications were either solely authored by him or coauthored with former or present members of his staff at ETS. A small number of papers, however, were coauthored with two other investigators, Anthony Pellegrini and Gene Brody, at the University of Georgia. These publications are of particular interest because they cast Sigel’s research paradigm within a different theoretical framework , that of Vygotsky ( 1978 ), and they introduced a new independent variable into the paradigm, marital quality.
In the case of marital quality, Brody et al. ( 1986 ) raised the possibility that the quality of the marital relationship would influence mothers’ and fathers’ interactions with their elementary-school age children. More specifically, Brody et al., leaning on clinical reports, examined the assumption that marital distress would lead to compensatory behaviors by the parents when they interact with their children in a teaching context. Also under examination was the possibility that mothers and fathers would employ different teaching strategies when interacting with the children, with the nature of such differences possibly contingent on the levels of marital distress.
Again, storytelling and paper-folding tasks were used with the mothers and fathers. Level of marital distress was assessed by the Scale of Marriage Problems (Swenson and Fiore 1975 ), and a median split was used to divide the sample into distressed and nondistressed subgroups. Observation of parental teaching strategies and the child’s responsiveness was accomplished with an event-recording procedure (Sigel et al. 1977 ) that yielded interrater reliability coefficients exceeding .75 for each of the eight behaviors coded. ANOVAs produced significant Marital Problems × Parent interactions for seven of the eight behavioral indices. Nondistressed mothers and fathers did not differ on any of the behavioral indices. By contrast, distressed mothers and fathers differed in their teaching strategies, the mothers’ strategies being more effective: more questions, feedback, and suggestions and fewer attempts to take over the child’s problem-solving efforts.
Fathers in the distressed group “behave in a more intrusive manner with their school-aged children, doing tasks for them rather than allowing them to discover their own solutions and displaying fewer positive emotions in response to their children’s learning attempts” (p. 295). Mothers in distressed marriages, by contrast, responded with more effective teaching behaviors, inducing more responsive behavior from their children. Hence the hypothesis of compensatory maternal behaviors in a distressed marriage was supported. The psychological basis for such compensation, however, remained conjectural, with the strong likelihood that mothers were compensating for perceived less-than-satisfactory parenting by their husbands. Finally, Brody et al. ( 1986 ) offered the caveat that the outcomes could not be generalized to parents with more meager educational and economic resources than characterized the well-educated parents employed in their study.
In two additional studies (Pellegrini et al. 1985 , 1986 ), the Sigel research paradigm was applied, but interpretation of the results leaned heavily on Vygotsky’s ( 1978 ) theory of the zone of proximal development. Pellegrini et al. ( 1985 ) studied parents’ book-reading behaviors with 4- and 5-year-old children. Families differed in whether their children were communicatively disabled. MANOVA was applied, with the parental interaction behavior as the dependent variable and age, CD vs. non-CD status, and parent (mother vs. father) as the independent variables. Only CD vs. non-CD status yielded a significant main effect. Parental behaviors were more directive and less demanding with CD children. Furthermore, stepwise regression analysis examined the link between the parental interaction variables and WPPSI verbal IQ. For non-CD children, high cognitive demand was significantly associated with higher IQ levels; for CD children, the strongest positive predictor of IQ was the less demanding strategy of verbal/emotional support.
In general, parents seemed to adjust the cognitive demands of their teaching strategies to the level of the children’s communicative competences. In Vygotskyan terms, parents operated within the child’s zone of proximal development. Other evidence indicated that parents engaged in scaffolding to enhance their children’s cognitive–linguistic performances. Thus parents of non-CD children manifested more conversational turns in a presumed effort to elicit more language from their children. Similarly, more parental paraphrasing with non-CD children encouraged departures from the literal text, thereby fostering greater depth of interaction between parent and child. In sum, parental scaffolding of their children’s task-oriented behavior activated the potential for children to advance toward more independent problem solving as outlined in Vygotsky’s theory.
We turn, finally, to the second study (Pellegrini et al. 1986 ) influenced by Vygotsky’s theory . The research paradigm was similar to studies previously described. Again, gender of parent, children’s CD vs. non-CD status, and the tasks of book reading and paper folding constituted the independent variables, and the teaching strategies of the parents comprised the dependent variables. In addition, the extent of task engagement by the child was also examined. MANOVA was employed, and it yielded a significant main effect for the child’s communicative status and for its interaction with the task variable. ANOVAs applied to the separate teaching variables indicated that (a) parents were more directive and less demanding with CD children than with non-CD children; (b) parents were more demanding, gave less emotional support, and asked fewer questions with the paper-folding task than with the book-reading task; and (c) communicative status and task variable interacted: A CD versus non-CD difference occurred only for the book-reading task, with parents of CD children asking more questions and making lower cognitive demands.
The teaching strategy measures were factor analyzed, and the resulting four orthogonal factors became the predictor variables in a regression analysis with children’s rated task engagement as the criterion variable. For the paper-folding task, parents of both CD and non-CD children used high-demand strategies to keep their children engaged. For the book-reading task, parents of CD and non-CD children differed, with the CD parents using less demanding strategies and the non-CD parents using more demanding ones.
Pellegrini et al. ( 1986 ) had shown how ultimate problem-solving outcomes are of less significance than the processes by which such outcomes are achieved. Adult guidance is the key, with non-CD children requiring considerably less of it to remain engaged with the task than was the case for CD children. Hence the children’s competence levels alert the parents to how demanding their teaching strategies should be. Pellegrini et al. further recommended the exploration of the sequence of parental teaching strategies, as parents found it necessary on occasion to switch from more demanding to less demanding strategies when the child encountered difficulty (see Wertsch et al. 1980 ). In sum, the findings strongly support the Vygotsky model of parents teaching children through the zone of proximal development and the adjustment of parental teaching consistent with the competence level of their children.
An important feature of Sigel’s research program was linking research to practice (Renninger 2007 ). As Sigel ( 2006 ) noted,
efforts to apply research to practice require acknowledging the inherent tensions of trying to validate theory and research in practical settings. They require stretching and/or adapting the root metaphors in which we have been trained so that collaborations between researchers and practitioners are the basis of research and any application of research to practice. (p. 1022)
The research on representational competence and psychological distance has had widespread impact, notably for early childhood education (Hyson et al. 2006 ) and cognitive behavior therapy (Beck 1967 ).
2 Parental Influences , Migration, and Measurement
Laosa’s empirical work and his position papers spanned the psychological development of children, particularly Hispanics. His methodological contributions included test theory, especially as it relates to the assessment of minority children , and a standardized measure of parental teaching strategies. The major foci of Laosa’s work to be considered here are parental influences on children’s development, the consequences of migration for their adjustment and growth, and the measurement of their ability.
2.1 Parental Influences
Parental influence on children’s intellectual development has been a topic of long-standing interest to developmental psychologists (e.g., Clarke-Stewart 1977 ). A particular concern in Laosa’s work was Hispanic children , given the gap in their academic achievement. His early research concerned maternal teaching. Unlike much of the previous work in that area, Laosa made direct observations of the mothers teaching their children, instead of relying on mothers’ self-reports about interactions with their children, and distinguished between two likely SES determinants of their teaching: education and occupation. In a study of Hispanic mother–child dyads (Laosa 1978 ), mother’s education correlated positively with praising and asking questions during the teaching and correlated negatively with modeling (i.e., the mother working on the learning task herself while the child observes). However, mother’s occupation did not correlate with any of the teaching variables, and neither did father’s occupation. Laosa speculated that the education-linked differences in teaching strategies account for the relationship between mothers’ education and their children’s intellectual development found in other research (e.g., Bradley et al. 1977 ). Subsequently, Laosa ( 1980b ) also suggested that the more highly educated mothers imitate how they were taught in school.
In a follow-up study of Hispanic and non-Hispanic White mother–child dyads (Laosa 1980b ), the two groups differed on most of the teaching variables. Non-Hispanic White mothers praised and asked questions more, and Hispanic mothers modeled, gave visual cues, directed, and punished or restrained more. However, when mothers’ education was statistically controlled, the differences between the groups disappeared; controlling for mothers’ or fathers’ occupation did not reduce the differences.
In a third study, with the Hispanic mother–child dyads (Laosa 1980a ), mother’s field independence, assessed by the Embedded Figure Test (Witkin et al. 1971 ) and WAIS Block Design (Wechsler 1955 ), correlated positively with mother’s asking questions and praising, and correlated negatively with mother’s modeling. The correlations were reduced, but their pattern was similar when mother’s education was statistically controlled. Laosa suggested that asking questions and praising are self-discovery approaches to learning that reflect field independence, whereas modeling is a concrete approach that reflects field dependence; hence mothers were using strategies that foster their own cognitive style in their children. Mother’s teaching strategies, in fact, correlated modestly but inconsistently with the children’s field independence, as measured by the Children’s Embedded Figures Test (Witkin et al. 1971 ), WISC Block Design (Wechsler 1949a ), and Human Figure Drawing (Harris 1963 ), another measure of field independence. Most of the teaching strategies had scattered correlations with the Children’s Embedded Figures Test and Block Design: positive correlations with asking questions and praising (field-independent strategies) and negative correlations with modeling, punishing or restraining, and giving visual cues (field-dependent strategies).
In Laosa’s later research, a recurring topic was the impact of parents’ education on their children’s intellectual development; this line of work was presumably motivated by the influence of education in his maternal-teaching studies. Laosa ( 1982b ) viewed parental education as impacting the parent–child interaction and presented a conceptual model of this interaction as the mediator between parent education and the child’s development. He reported further analyses of the samples of Hispanic and non-Hispanic White mother–child dyads.
In one analysis, non-Hispanic White mothers and fathers read to their children more than did Hispanic parents. When parents’ education was statistically controlled, the group difference disappeared, but controlling for parents’ occupation did not reduce it. In addition, non-Hispanic mothers had higher realistic educational aspirations for their children (“ realistically , how much education do you think your child will receive?”); this difference also disappeared when mothers’ education was controlled but not when their occupation was controlled.
In another analysis, mother’s education correlated positively in both the Hispanic and non-Hispanic White groups with mother’s reading to the child, but father’s education was uncorrelated with father’s reading to the child in either group. Parent’s occupation did not correlate with reading in the two groups. In both groups, mother’s education also correlated positively with mother’s educational aspirations for the child, but mother’s occupation was uncorrelated.
Also, in an analysis of the Hispanic group, mother’s education correlated positively with the child’s ability to read or write before kindergarten, though father’s education was uncorrelated. Parent’s occupation was also uncorrelated with literacy . In addition, parent’s education correlated positively with their use of English with the child; parent’s occupation also correlated positively but weakly with English use.
Laosa argued that the set of findings, in total, suggests that the lower educational level of Hispanic parents produced a discontinuity between their children’s home and school environments that adversely affected academic achievement.
He explored the consequences of these parental influences on the test performance of 3-year-olds in two studies. In the first study (Laosa 1982a ), which targeted non-Hispanic White children , a path analysis was employed to assess the relationships, direct and indirect, between a host of family influences (e.g., mother’s education and occupation, mother’s reading to the child, nonparents in the household reading to the child, mother’s teaching strategies) and performance on the Preschool Inventory (Caldwell 1970 ), a test of verbal, quantitative, and perceptual-motor skills for kindergarten children. A Mother’s Socioeducational Values factor (defined by mother’s education and occupation and mother’s reading to child) was the strongest determinant of test performance. Less powerful determinants included nonparents in the household (probably older siblings) reading to the child and mother’s use of modeling in teaching. Laosa highlighted two important and unanticipated findings: the apparent influence of siblings and the substantial and positive influence of modeling, contrary to the conventional wisdom that verbal teaching strategies, such as asking questions, are superior to nonverbal ones, such as modeling.
In the second study (Laosa 1984 ) of Hispanic and non-Hispanic White children , the groups differed in their means on three of the five scales of the McCarthy Scales of Children’s Abilities (McCarthy 1972 ): Verbal, Quantitative, and Memory. When a Sib Structure/Size factor (later-born child, many siblings) was statistically controlled, the group differences were unaffected. But when either a Language factor (mother uses English with child, child uses English with mother) or an SES factor (parents’ education, father’s occupation, household income) was controlled, the differences were reduced; when both factors were controlled, the differences were eliminated. The findings led Laosa to conclude that these early ethnic-group differences in ability were explainable by differences in SES and English-language usage.
In a series of white papers, Laosa reviewed and synthesized the extant research literature on the consequences of migration for children’s adjustment and development, particularly Hispanic children , and laid out the salient issues (Laosa 1990 , 1997 , 1999 ). One theme was the need for—and the absence of—a developmental perspective in studying migration: “what develops, and when, how, and why it develops” (Laosa 1999 , p. 370). The pioneering nature of this effort is underscored by the observation almost two decades later that migration is neglected by developmental psychology (Suárez-Orozco and Carhill 2008 ; Suárez-Orozco et al. 2008 ).
In a 1990 paper, Laosa proposed a multivariate, conceptual model that described the determinants of the adaptation of Hispanic immigrant children to the new society. Key features of the model were the inclusion of variables antedating immigration (e.g., sending community), moderator variables (e.g., receiving community), and mediating variables (e.g., child’s perceptions and expectations) between the stresses of immigration and the outcomes.
In a complex, longitudinal survey of Puerto Rican migrants in New Jersey schools, Laosa ( 2001 ) found that the majority of the student body were Hispanic in 46% of the schools and were native speakers of Spanish in 31%. Additionally, the majority of the student body was eligible for free lunch in 77% of the schools and was from families on public assistance in 46%. Laosa concluded that the migrants faced considerable segregation by ethnicity or race as well as considerable isolation by language in high-poverty schools, factors with adverse consequences for the students’ social and academic development.
The measurement and evaluation of children’s ability and achievement, particularly the unbiased assessment of minority children, has long been beset by controversies (see Laosa 1977 ; Oakland and Laosa 1977 ). These controversies were sparked in the 1960s and 1970s by the Coleman report (Coleman et al. 1966 ), which suggested that average differences in the academic performance of Black and White students are more affected by their home background than by their schools’ resources, and by Jensen’s ( 1969 ) review of research bearing on genetic and environmental influences on intelligence. He concluded that genetics is a stronger influence, which many observers interpreted as suggesting that the well-established disparity between Black and White children in their average scores on intelligence tests is largely genetic in origin. The upshot was widespread concerns that these tests are biased and calls for banning their use in schools. These arguments were reignited by The Bell Curve (Herrnstein and Murray 1994 ), which concluded that intelligence is mainly heritable. As Laosa ( 1996 ) noted, “thus, like a refractory strain of retrovirus, the issues tend to remain latent and from time to time resurge brusquely onto the fore of public consciousness” (p. 155).
In a 1977 paper, Laosa summarized the earlier controversies and other criticisms of testing and discussed alternatives to current testing practices that had been developed in response. The alternatives included constructing “culture-fair” tests “whose content is equally ‘fair’ or ‘unfair’ to different cultural groups” (p. 14), translating tests from English, using norms for subgroups, adjusting scores for test takers with deprived backgrounds, devising tests for subgroups (e.g., the BITCH, a vocabulary test based on Black culture; Williams 1972 ), using criterion-based interpretations of scores (i.e., how well a student achieves a specific objective) instead of norm-based interpretations (i.e., how well he or she does on the test relative to others), employing tests of specific abilities rather than global measures like IQ, and making observations of actual behavior. Laosa cautioned that these alternatives may also be problematic and would need to be carefully evaluated.
In a companion piece, Laosa, joined by Thomas Oakland of the University of Texas, Austin (Oakland and Laosa 1977 ), provided a comprehensive account of standards for minority-group testing that had been formulated by professional organizations, the government, and the courts. They argued for the need to consider these standards in testing minority-group children.
Laosa ( 1982c ), in a subsequent paper on measurement issues in the evaluation of educational programs , specifically Head Start , delineated the concept of population validity and its applicability to program evaluation . Population validity deals with the question, “Do the results yielded by a given assessment technique have the same meaning when administered to persons of different sociocultural backgrounds?” (p. 512). Laosa discussed threats to population validity: familiarity (performance is influenced by familiarity with the task), communication, role relations (performance is influenced by the test taker’s relationship with the tester), and situational (e.g., physical setting, people involved).
In another paper, Laosa ( 1991 ) explicated the links between population validity, cultural diversity, and professional ethics. As an illustration, he described a study by Bradley et al. ( 1989 ) of children in three ethnic groups, Black, Hispanic, and non-Hispanic White, matched on their HOME inventory (Caldwell and Bradley 1985 ) scores, a measure of the home environment. The HOME inventory scores correlated appreciably with performance on the Bayley Scales of Infant Development (Bayley 1969 ) and the Stanford–Binet Intelligence Test (Terman and Merrill 1960 ) for the Black and non-Hispanic White children but not for the Hispanic children . Laosa suggested that this finding highlights the importance of evaluating test results separately for different ethnic groups.
Laosa pointed out that population validity is a scientific concern in basic research and an ethical issue in applied work, given the inability to predict the results in different populations from the one studied. He also noted that when population differences are observed, two questions need to be answered. One, relevant to applied work, is, Which populations react differently? The other question, pertinent to scientific research, but rarely asked, is, Why do they differ?
In his last paper on measurement issues, Laosa ( 1996 ), responding to The Bell Curve controversy, made several general points about test bias. One was that bias reflects the absence of population validity. He noted that this view accords with the Cole and Moss ( 1989 ) definition of bias: “Bias is differential validity of a given interpretation of a test score for any definable, relevant group of test takers” (p. 205).
Another point was that the definition of predictive bias in the then current third edition of the Standards for Educational and Psychological Testing (American Educational Research Association, American Psychological Association, & National Council on Measurement in Education 1985 ) is insufficient. According to the Standards , predictive bias is absent if “the predictive relationship of two groups being compared can be adequately described by a common algorithm (e.g., regression line)” (p. 12). Laosa took up the argument that intelligence tests cannot be considered to be unbiased simply because their predictions are equally accurate for different races or social classes, noting Campbell’s rejoinder that the same result would occur if the tests simply measured opportunity to learn (D. T. Campbell, personal communication, May 18, 1995).
The last point was that the consequences of test use also need to be considered (Messick 1989 ). Laosa cited Linn’s ( 1989 ) example that requiring minimum high school grades and admissions test scores for college athletes to play during their freshman year can affect what courses minority athletes take in high school, whether they will attend college if they cannot play in their freshman year, and, ultimately, their education and employment.
3 Cognitive, Personality, and Social Development of Infants and Young Children
Lewis studied infant’s cognitive attention and language ability, infants’ and young children’s physiological responses during attention, and infants’ social and emotional development . He also formulated theories of development as well as theories about the integration of children’s various competencies.
3.1 Social Development
Social development was a major interest, in particular, the mother–child interaction and the role this interaction played in the child’s development. This work on social development revolved around four themes: (a) the mother–child relationship, (b) the growth of the child’s social knowledge, (c) social cognition or the nature of the social world, and (d) the social network of children.
For example, in a 1979 volume (Lewis and Rosenblum 1979 ), The Child and Its Family , Lewis challenged the idea that the child’s mother was the only important figure in the infant’s early life and showed that fathers and siblings, as well as grandparents and teachers, were also key influences. And in a 1975 volume, on peer friendship in the opening years of life (Lewis and Rosenblum 1975 ), Lewis disputed the Piagetian idea that children could not form and maintain friendships before the age of 4 years. The finding that infants are attracted to and enjoy the company of other infants and young children , and that they can learn from them through observation and imitation, helped open the field of infant daycare (Goldman and Lewis 1976 ; Lewis 1982b ; Lewis and Schaeffer 1981 ; Lewis et al. 1975 ). Because the infant’s ability to form and maintain friends is important for the daycare context, where groups of infants are required to play together, this work also showed that the learning experience of young children and infants involved both direct and indirect interactions, such as modeling and imitation with their social world of peers, siblings, and teachers (Feiring and Lewis 1978 ; Lewis and Feiring 1982 ). This information also had an important consequence on hospital care; until this time, infants were kept far apart from each other in the belief that they could not appreciate or profit from the company of other children.
Another major theme of the research on social development involved infants’ social knowledge. In a series of papers, Lewis was able to show that infants could discriminate among human faces (Lewis 1969 ); that they were learning about their gender (Lewis and Brooks 1975 ); that they were showing sex-role-appropriate behaviors (Feiring and Lewis 1979 ; Goldberg and Lewis 1969 ; Lewis 1975a ); that they were learning about how people look, for example, showing surprise at the appearance of a midget—a child’s height but an adult’s face (Brooks and Lewis 1976 ); and that they were detecting the correspondence between particular faces and voices (McGurk and Lewis 1974 ). All of these results indicated that in the first 2 years, children were learning a great deal about their social worlds (Brooks-Gunn and Lewis 1981 ; Lewis 1981b ; Lewis et al. 1971 ).
The most important aspect of this work on social development was the child’s development of a sense of itself, something now called consciousness, which occurs in the second and third years of life. In the Lewis and Brooks-Gunn ( 1979a ) book on self-recognition, Social Cognition and the Acquisition of Self, Lewis described his mirror self-recognition test, a technique that has now been used across the world. Results with this test revealed that between 15 and 24 months of age, typically developing children come to recognize themselves in mirrors. He subsequently showed that this ability, the development of the idea of “me,” along with other cognitive abilities gives rise to the complex emotions of empathy, embarrassment, and envy as well as the later self-conscious emotions of shame, guilt, and pride (Lewis and Brooks 1975 ; Lewis and Brooks-Gunn 1981b ; Lewis and Michalson 1982b ; Lewis and Rosenblum 1974b ).
These ideas, an outgrowth of the work on self-recognition, led to Lewis’s interest in emotional development . They also resulted in a reinterpretation of the child’s need for others. While children’s attachment to their mothers was thought to be the most important relationship for the children, satisfying all of their needs, it became clear that others played an important role in children’s social and emotional lives. His empirical work on fathers (Lewis and Weinraub 1974 ) and peers (Lewis et al. 1975 ) led to the formulation of a social network theory (Feiring and Lewis 1978 ; Lewis 1980 ; Lewis and Ban 1977 ; Lewis and Feiring 1979 ; Weinraub et al. 1977 ).
3.2 Emotional Development
Lewis’s interest in social development and in consciousness led quite naturally to his research on emotional development, as already noted (Lewis 1973 , 1977b , 1980 ; Lewis and Brooks 1974 ; Lewis et al. 1978 ; Lewis and Michalson 1982a , b ; Lewis and Rosenblum 1978a , b ). Two volumes framed this work on the development of emotional life (Lewis and Rosenblum 1974b , 1978b ) and were the first published studies of emotional development. These early efforts were focused on the emotions of infants in the first year of life, including fear, anger, sadness, joy, and interest. To study emotional life, Lewis created experimental paradigms and devised a measurement system. So, for example, paradigms were developed for peer play (Lewis et al. 1975 ), social referencing (Feinman and Lewis 1983 ; Lewis and Feiring 1981 ), stranger approach (Lewis and Brooks-Gunn 1979a ), mirror recognition (Lewis and Brooks-Gunn 1979a ), and contingent learning (Freedle and Lewis 1970 ; Lewis and Starr 1979 ). A measurement system was created for observing infants’ and young children’s emotional behavior in a daycare situation that provided scales of emotional development (Lewis and Michalson 1983 ). These scales have been used by both American and Italian researchers interested in the effects of daycare on emotional life (Goldman and Lewis 1976 ).
3.3 Cognitive Development
Lewis’s interests in development also extended to the study of infants’ and children’s cognitive development, including attentional processes, intelligence, and language development (Dodd and Lewis 1969 ; Freedle and Lewis 1977 ; Hale and Lewis 1979 ; Lewis 1971b , 1973 , 1975b , 1976a , b , 1977a , 1978a , 1981a , 1982a ; Lewis and Baldini 1979 ; Lewis and Baumel 1970 ; Lewis and Cherry 1977 ; Lewis and Freedle 1977 ; Lewis and Rosenblum 1977 ; Lewis et al. 1969a, 1971 ; McGurk and Lewis 1974 ).
Lewis first demonstrated that the Bayley Scales of Infant Development (Bayley 1969 ), which were—and still are—the most widely used test of infant intelligence, had no predictive ability up to 18 months of age (Lewis and McGurk 1973 ). In an effort to find an alternative, Lewis turned to research on infants’ attentional ability, which he had begun at the Fels Research Institute, and developed it further at ETS. This work used a habituation–dishabituation paradigm where the infant was presented with the same visual stimulus repeatedly and then, after some time, presented with a variation of that stimulus. Infants show boredom to the repeated event, or habituation, and when the new event is presented, the infants show recovery of their interest, or dishabituation (Kagan and Lewis 1965 ; Lewis et al. 1967a , b ). Infants’ interest was measured both by observing their looking behavior and by assessing changes in their heart rate (Lewis 1974 ; Lewis et al. 1966a , b ; Lewis and Spaulding 1967 ). He discovered that the infants’ rate of habituation and degree of dishabituation were both related to their subsequent cognitive competence, in particular to their IQ. In fact, this test was more accurate than the Bayley in predicting subsequent IQ (Lewis and Brooks-Gunn 1981a , c ; Lewis et al. 1969 ; Lewis and McGurk 1973 ).
This research on attentional processes convinced Lewis of the usefulness of physiological measures, such as heart rate changes, in augmenting behavior observation, work which he also began at the Fels Research Institute and continued and expanded at ETS (Lewis 1971a , b , 1974 ; Lewis et al. 1969 , 1970 , 1978 ; Lewis and Taft 1982 ; Lewis and Wilson 1970 ; Sontag et al. 1969 ; Steele and Lewis 1968 ).
3.4 Atypical Development
Lewis’s research on normal development, especially on attentional processes as a marker of central nervous system functioning, led to an interest in atypical developmental processes and a program of research on children with disabilities (Brinker and Lewis 1982a , b ; Brooks-Gunn and Lewis 1981 , 1982a , b , c ; Fox and Lewis 1982a , b ; Lewis 1971c ; Lewis and Fox 1980 ; Lewis and Rosenblum 1981 ; Lewis and Taft 1982 ; Lewis and Wehren 1982 ; Lewis and Zarin-Ackerman 1977 ; Thurman and Lewis 1979 ; Zarin-Ackerman et al. 1977 ). Perhaps of most importance was the development of an intervention strategy based on Lewis’s work with typically developing children, the Learning to Learn Curriculum. Infants with disabilities were given home- and clinic-based interventions where their simple motor responses resulted in complex outcomes and where they had to learn to produce these outcomes, which served as operants—in effect, an applied-behavior-analysis intervention strategy (Brinker and Lewis 1982a , b ; Lewis 1978a , b ; Thurman and Lewis 1979 ).
Lewis formulated several influential theories about infant development . These included (a) a reconsideration of attachment theory (Weinraub and Lewis 1977 ) and (b) the infant as part of a social network (Weinraub et al. 1977 ). He also began work on a theory of emotional development (Lewis 1971b ; Lewis and Michalson 1983 ).
3.6 The Origin of Behavior Series
Lewis and Leonard Rosenblum of SUNY Downstate Medical Center organized yearly conferences on important topics in child development for research scientists in both child and animal (primate) development to bring together biological, cultural, and educational points of view. These conferences resulted in a book series, The Origins of Behavior (later titled Genesis of Behavior ), under their editorship, with seven highly cited volumes (Lewis and Rosenblum 1974a , b , 1975 , 1977 , 1978a , 1979 , 1981 ). The initial volume, The Effect of the Infant on the Caregiver (Lewis and Rosenblum 1974a ), was so influential that the term caregiver became the preferred term, replacing the old term caretaker. The book became the major reference on the interactive nature of social development —that the social development of the child involves an interaction between the mother’s effect on the infant and the effect of the infant on the mother. It was translated into several languages, and 15 years after publication, a meeting sponsored by the National Institutes of Health reviewed the effects of this volume on the field.
4 Cognitive, Personality, and Social Development From Infancy to Adolescence
Brooks-Gunn’s work encompassed research on the cognitive, personality, and social development of infants , toddlers, and adolescents , primarily within the framework of social-cognitive theory . Major foci were the acquisition of social knowledge in young children , reproductive processes in adolescence, and perinatal influences on children’s development. These issues were attacked in laboratory experiments, other cross-sectional and longitudinal studies, and experimental interventions . (A fuller account appears in Brooks-Gunn 2013 .)
4.1 Social Knowledge in Infants and Toddlers
In collaboration with Lewis, Brooks-Gunn carried out a series of studies on the development of early knowledge about the self and others in infancy and toddlerhood. They investigated how and when young children began to use social categories, such as gender, age, and relationship, to organize their world and to guide interactions (Brooks and Lewis 1976 ; Brooks-Gunn and Lewis 1979a , b , 1981 ) as well as the development of self-recognition as a specific aspect of social cognition (Lewis and Brooks-Gunn 1979b , c ; Lewis et al. 1985 ). This developmental work was embedded in genetic epistemology theory as well as social-cognitive theory , with a strong focus on the idea that the self (or person) only develops in relation to others and that the self continues to evolve over time, as does the relation to others.
The studies demonstrated that social knowledge develops very early. Infants shown pictures of their parents, strange adults, and 5-year olds and asked, Who is that? were able to label their parents’ pictures as mommy and poppy, labeling their fathers’ pictures more accurately and earlier than their mothers’ (Brooks-Gunn and Lewis 1979b ). Shown pictures of their parents and strange adults, infants smiled more often and looked longer at their parents’ pictures (Brooks-Gunn and Lewis 1981 ). And when infants were approached by strangers—5-year-old boys and girls, adult men and women, and a midget woman—the children discriminated among them on the basis of age and height, smiling and moving toward the children but frowning and moving away from the adults and, compared to the other adults, watching the midget more intently and averting their gaze less (Brooks and Lewis 1976 ).
4.2 Reproductive Events
4.2.1 menstruation and menarche.
Brooks-Gunn’s interest in the emergence of social cognition broadened to its role in the development of perceptions about reproductive events, at first menstruation and menarche. Her focus was on how social cognitions about menstruation and menarche emerge in adolescence and how males’ and females’ cognitions differ. Brooks-Gunn and Diane Ruble, then at Princeton University, began a research program on the salience and meaning of menarche and menstruation, especially in terms of definition of self and other in the context of these universal reproductive events (Brooks-Gunn 1984 , 1987 ; Brooks-Gunn and Ruble 1982a , b , 1983 ; Ruble and Brooks-Gunn 1979b ). They found that menstruation was perceived as more physiologically and psychologically debilitating and more bothersome by men than by women (Ruble et al. 1982 ). In addition, their research debunked a number of myths about reproductive changes (Ruble and Brooks-Gunn 1979a ), including the one that menarche is a normative crisis experienced very negatively by all girls. In fact, most girls reported mixed emotional reactions to menarche that were quite moderate. These reactions depended on the context the girls experienced: Those who were unprepared for menarche or reached it early reported more negative reactions as well as more symptoms (Ruble and Brooks-Gunn 1982 ).
4.2.2 Pubertal Processes
Brooks-Gunn’s research further broadened to include pubertal processes. With Michelle Warren , a reproductive endocrinologist at Columbia University, she initiated a research program on pubertal processes and the transition from childhood to early adolescence. Brooks-Gunn and Warren conducted longitudinal studies of girls to chart their emotional experiences associated with pubertal changes and the socialization practices of families . The work included measurement of hormones to better understand pubertal changes and possible emotional reactions. The investigations followed girls who were likely to have delayed puberty because of exercise and food restriction (dancers training in national ballet companies as well as elite swimmers and gymnasts) and girls attending private schools—many of the girls were followed from middle school through college (Brooks-Gunn and Warren 1985 , 1988a , b ; Warren et al. 1986 , 1991 ).
The private-school girls commonly compared their pubertal development and had no difficulty categorizing their classmates’ development (Brooks-Gunn et al. 1986 ). Relatedly, the onset of breast development for these girls correlated positively with scores on measures of peer relationships, adjustment, and body image, but pubic hair was uncorrelated, suggesting that breast growth may be a visible sign of adulthood, conferring enhanced status (Brooks-Gunn and Warren 1988b ).
The context in which the girls were situated influenced their reactions. In a context where delayed onset of puberty is valued (the dance world—most professional ballerinas are late maturers), dancers with delayed puberty had higher scores (relative to on-time dancers) on a body-image measure (Brooks-Gunn, Attie, Burrow , Rosso , & Warren , Brooks-Gunn et al. 1989 ; Brooks-Gunn and Warren 1985 ). (They also had lower scores on measures of psychopathology and bulimia; Brooks-Gunn and Warren 1985 .) In contrast, in contexts where delayed onset is not valued (swimmers, private-school students/nonathletes), delayed and on-time girls did not differ in their body images (Brooks-Gunn, Attie et al., Brooks-Gunn et al. 1989 ; Brooks-Gunn and Warren 1985 ).
Two publications in this program, in particular, were very widely cited, according to the Social Science Citation Index: Attie and Brooks-Gunn ( 1989 ), on eating problems, and Brooks-Gunn et al. ( 1987 ), on measuring pubertal status, with 389 and 323 citations through 2015, respectively.
4.2.3 Adolescent Parenthood
Given Brooks-Gunn’s research interest in menarche and other pubertal processes , it is not surprising that she moved on to research on pregnancy and parenthood, events that presage changes in self-definition as well as social comparisons with others. Brooks-Gunn joined Frank Furstenberg, a family sociologist at the University of Pennsylvania, in a 17-year follow-up of a group of teenage mothers who gave birth in Baltimore in the early 1970s (Furstenberg et al. 1987a , b , 1990 ). They charted the trajectories of these mothers as well as their children, who were about the age that their mothers had been when they gave birth to them. The interest was in both how well the mothers were doing and how the mothers’ life course had influenced their children.
In brief, the teenage mothers differed widely in their life chances: About one third were on welfare and three quarters had jobs, usually full-time ones. Characteristics of the mothers’ family of origin and of their own families (e.g., higher levels of education) and their attendance at a school for pregnant teenagers predicted the mothers’ economic success.
The outcomes for their teenage children were “strikingly poor” (Brooks-Gunn 1996 , p. 168). About one third were living with their biological father or stepfather. Half had repeated at least one grade in school, and most were sexually active. Maternal characteristics were linked to the children’s behavior. Children of mothers who had not graduated from high school were 2.4 times as likely as other children, and children of unmarried mothers were 2.2 times as likely, to have repeated a grade. And children of unmarried mothers were 2.4 times as likely to have been stopped by the police, according to their mothers.
The Furstenberg et al. ( 1987b ) monograph chronicling this study, Adolescent Mothers in Later Life, won the William J. Goode Book Award from the American Sociological Association’s Sociology of the Family Section and is considered one of the classic longitudinal studies in developmental psychology.
Brooks-Gunn and Lindsay Chase-Lansdale, then at George Washington University, also began a study of low-income, Black multigenerational families (grandmother/grandmother figure–young mother–toddler) in Baltimore to investigate family relationships, via home visits (Chase-Lansdale et al. 1994 ). One issue was the parenting by the grandmother and mother, as observed separately in videotaped interactions of them aiding the child in working on a puzzle. The quality of parenting depended on whether they resided together and on the mother’s age. Mothers’ parenting was lower in quality when they lived with grandmothers. (Residing with the grandmothers and sharing child caring may be stressful for the mothers, interfering with their parenting.) Grandmothers’ parenting was higher in quality when they lived with younger mothers than when they lived apart, but it was lower in quality when they lived with older mothers rather than apart. (Coresiding grandmothers may be more willing to help younger mothers, whom they view as needing assistance in parenting, than older mothers, whom they see as capable of parenting on their own.)
4.3 Perinatal Influences
Another line of research expanded beyond teenage parents to look at perinatal conditions, such as low birth weight and pregnancy behavior (e.g., smoking, no prenatal care), that influence parenting and children’s development. Poor families and mothers with low education were often the focus of this research, given the differential rates of both early parenthood and adverse perinatal conditions as a function of social class.
In a joint venture between ETS, St. Luke’s–Roosevelt Hospital, and Columbia University’s College of Physicians and Surgeons, Brooks-Gunn studied low-birth-weight children and their parents, many from disadvantaged families because of the greater incidence of low-birth-weight children in these families. The work led to her thinking about how to ameliorate cognitive, emotional, and academic problems in these vulnerable children (Brooks-Gunn and Hearn 1982 ).
Brooks-Gunn joined Marie McCormick , a pediatrician then at the University of Pennsylvania, in a 9-year follow-up of low-birth-weight infants from previous multisite studies (Klebanov et al. 1994 ; McCormick et al. 1992 ). The focus was on very low birth weight infants, for more of them were surviving because of advances in neonatal intensive care.
At age 9, the low-birth-weight children did not differ from normal-birth-weight children on most aspects of classroom behavior, as reported by their teachers, but they had lower attention/ language skills and scholastic competence and higher daydreaming and hyperactivity; these differences were most pronounced for extremely low birth weight children. This pattern of differences resembles attention deficit disorder (Klebanov et al. 1994 ). The low-birth-weight children also had lower mean IQs and, at home, more behavioral problems, as reported by their mothers. The adverse health status of these children underscores the importance of efforts to reduce the incidence of premature births (McCormick et al. 1992 ).
4.4 Interventions With Vulnerable Children
4.4.1 low-birth-weight children.
Brooks-Gunn and McCormick also collaborated on two other research programs involving interventions with biologically vulnerable children, the majority of whom were poor. One program focused on reducing the incidence of low-birth-weight deliveries by providing pregnant women with child-rearing and health information. This program used a public health outreach model to locate pregnant women who were not enrolled in prenatal care; the intervention was located at Harlem Hospital. This effort was a logical extension of Brooks-Gunn’s work on adolescent mothers in Baltimore (Brooks-Gunn et al. 1989 ; McCormick et al. 1987 , 1989a , b ).
The women in the program were very disadvantaged: One fifth were adolescents , three quarters were single, and half had not graduated from high school. The birth weight of their infants was unrelated to traditional risk factors: mother’s demographic (e.g., education) and psychosocial characteristics (e.g., social support). This outcome suggests that low birth weight in poor populations is largely due to poverty per se. Birth weight was associated with the adequacy of prenatal care (Brooks-Gunn et al. 1988 ; McCormick et al. 1987 ).
The outreach program was extensive—four local people searching for eligible women over the course of a year, each making roughly 20 to 25 contacts daily—but recruited only 52 additional women, at a cost of about $850 each. The labor-intensive and expensive nature of this outreach effort indicates that more cost-effective alternatives are needed (Brooks-Gunn et al. 1988 , 1989 ).
The other program involved the design and implementation of an early intervention for premature, low-birth-weight infants : enrollment in a child development education center and family support sessions. This program was initiated in eight sites and included almost 1000 children and their families; randomization was used to construct treatment and control groups. These children were followed through their 18th year of life, with the intervention from birth to 3 years of age being evaluated by Brooks-Gunn (Infant Health and Development Program 1990 ). The 3-year-olds in the intervention group had higher mean IQs and fewer maternally reported behavior problems, suggesting that early intervention may decrease low-birth-weight infants’ risk of later developmental disability .
4.4.2 Head Start
Brooks-Gunn also carried out a notable evaluation of Head Start, based on data from an earlier longitudinal study conducted at ETS in the 1970s. The ETS–Head Start Longitudinal Study, directed by Shipman ( 1972 , 1973 ), had canvassed poor school districts in three communities in an effort to identify and recruit for the study all children who were 3 ½ to 4 ½ years old, the Head Start population. The children were then assessed and information about their families was obtained. They were reassessed annually for the next 3 years. After the initial assessment, some children had entered Head Start, some had gone to other preschool programs, and some had not enrolled in any program. Clearly families chose whether to enroll their children in Head Start, some other program, or none at all (by processes that are difficult if not impossible to measure). But, by having the children’s assessments and familial and demographic measures at age 3, it was possible to document and control statistically for initial differences among children and families in the three groups. Children’s gains in ability in these groups could then be compared.
In several studies of two communities (Lee et al. 1988 , 1990 ; Schnur et al. 1992 ), Brooks-Gunn and her collaborators investigated differences in the children’s gains in the Head Start and other groups as well as preexisting group differences in the children’s demographic and cognitive characteristics. Black children enrolled in Head Start made greater gains on a variety of cognitive tests than their Black peers in the other groups by the end of the program (Lee et al. 1988 ) and diminished gains after 2 years (Lee et al. 1990 ). (The gains for the small samples of White children did not differ between the Head Start and other groups in the initial study; these children were not included in the follow-up study.) These findings imply that Head Start may have some efficacy in improving participants’ intellectual status. The Head Start children were the most disadvantaged (Schnur et al. 1992 ), seemingly allaying concerns that Head Start does not take the neediest children (Datta 1979 ).
As this review documents, ETS was a major center for basic and applied research in developmental psychology for decades. The number and quality of investigators (and their prodigious output) made for a developmental psychology program that rivaled the best in the academic community.
The research was wide ranging and influential, spanning the cognitive, personality, and social development of infants , children, and adolescents , with an emphasis on minority, working-class, and disabled individuals; addressing key theoretical, substantive, and methodological issues; using research methods that ran the gamut: laboratory and field experiments, correlational studies, surveys, and structured observations; and impacting theory, research, and practice across developmental psychology.
In common with ETS’s research in cognitive, personality, and social psychology (Stricker, Chap. 13 , and Kogan, Chap. 14 , this volume), this achievement was probably attributable to the confluence of ample institutional and financial support, doubtless due to the vision of Chauncey, who saw the value of a broad program of psychological research.
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Thanks are due to Nick Telepak for retrieving publications and to Isaac Bejar, Randy Bennett, and Ann Renninger for reviewing a draft of this chapter.
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Kogan, N., Stricker, L.J., Lewis, M., Brooks-Gunn, J. (2017). Research on Developmental Psychology. In: Bennett, R., von Davier, M. (eds) Advancing Human Assessment. Methodology of Educational Measurement and Assessment. Springer, Cham. https://doi.org/10.1007/978-3-319-58689-2_15
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Research in Developmental Psychology
What you’ll learn to do: examine how to do research in lifespan development.
How do we know what changes and stays the same (and when and why) in lifespan development? We rely on research that utilizes the scientific method so that we can have confidence in the findings. How data are collected may vary by age group and by the type of information sought. The developmental design (for example, following individuals as they age over time or comparing individuals of different ages at one point in time) will affect the data and the conclusions that can be drawn from them about actual age changes. What do you think are the particular challenges or issues in conducting developmental research, such as with infants and children? Read on to learn more.
- Explain how the scientific method is used in researching development
- Compare various types and objectives of developmental research
- Describe methods for collecting research data (including observation, survey, case study, content analysis, and secondary content analysis)
- Explain correlational research
- Describe the value of experimental research
- Compare the advantages and disadvantages of developmental research designs (cross-sectional, longitudinal, and sequential)
- Describe challenges associated with conducting research in lifespan development
Research in Lifespan Development
How do we know what we know.
An important part of learning any science is having a basic knowledge of the techniques used in gathering information. The hallmark of scientific investigation is that of following a set of procedures designed to keep questioning or skepticism alive while describing, explaining, or testing any phenomenon. Not long ago a friend said to me that he did not trust academicians or researchers because they always seem to change their story. That, however, is exactly what science is all about; it involves continuously renewing our understanding of the subjects in question and an ongoing investigation of how and why events occur. Science is a vehicle for going on a never-ending journey. In the area of development, we have seen changes in recommendations for nutrition, in explanations of psychological states as people age, and in parenting advice. So think of learning about human development as a lifelong endeavor.
How do we know what we know? Take a moment to write down two things that you know about childhood. Okay. Now, how do you know? Chances are you know these things based on your own history (experiential reality), what others have told you, or cultural ideas (agreement reality) (Seccombe and Warner, 2004). There are several problems with personal inquiry or drawing conclusions based on our personal experiences.
Our assumptions very often guide our perceptions, consequently, when we believe something, we tend to see it even if it is not there. Have you heard the saying, “seeing is believing”? Well, the truth is just the opposite: believing is seeing. This problem may just be a result of cognitive ‘blinders’ or it may be part of a more conscious attempt to support our own views. Confirmation bias is the tendency to look for evidence that we are right and in so doing, we ignore contradictory evidence.
Philosopher Karl Popper suggested that the distinction between that which is scientific and that which is unscientific is that science is falsifiable; scientific inquiry involves attempts to reject or refute a theory or set of assumptions (Thornton, 2005). A theory that cannot be falsified is not scientific. And much of what we do in personal inquiry involves drawing conclusions based on what we have personally experienced or validating our own experience by discussing what we think is true with others who share the same views.
Science offers a more systematic way to make comparisons and guard against bias. One technique used to avoid sampling bias is to select participants for a study in a random way. This means using a technique to ensure that all members have an equal chance of being selected. Simple random sampling may involve using a set of random numbers as a guide in determining who is to be selected. For example, if we have a list of 400 people and wish to randomly select a smaller group or sample to be studied, we use a list of random numbers and select the case that corresponds with that number (Case 39, 3, 217, etc.). This is preferable to asking only those individuals with whom we are familiar to participate in a study; if we conveniently chose only people we know, we know nothing about those who had no opportunity to be selected. There are many more elaborate techniques that can be used to obtain samples that represent the composition of the population we are studying. But even though a randomly selected representative sample is preferable, it is not always used because of costs and other limitations. As a consumer of research, however, you should know how the sample was obtained and keep this in mind when interpreting results. It is possible that what was found was limited to that sample or similar individuals and not generalizable to everyone else.
The particular method used to conduct research may vary by discipline and since lifespan development is multidisciplinary, more than one method may be used to study human development. One method of scientific investigation involves the following steps:
- Determining a research question
- Reviewing previous studies addressing the topic in question (known as a literature review)
- Determining a method of gathering information
- Conducting the study
- Interpreting the results
- Drawing conclusions; stating limitations of the study and suggestions for future research
- Making the findings available to others (both to share information and to have the work scrutinized by others)
The findings of these scientific studies can then be used by others as they explore the area of interest. Through this process, a literature or knowledge base is established. This model of scientific investigation presents research as a linear process guided by a specific research question. And it typically involves quantitative research , which relies on numerical data or using statistics to understand and report what has been studied.
Another model of research, referred to as qualitative research, may involve steps such as these:
- Begin with a broad area of interest and a research question
- Gain entrance into a group to be researched
- Gather field notes about the setting, the people, the structure, the activities, or other areas of interest
- Ask open-ended, broad “grand tour” types of questions when interviewing subjects
- Modify research questions as the study continues
- Note patterns or consistencies
- Explore new areas deemed important by the people being observed
- Report findings
In this type of research, theoretical ideas are “grounded” in the experiences of the participants. The researcher is the student and the people in the setting are the teachers as they inform the researcher of their world (Glazer & Strauss, 1967). Researchers should be aware of their own biases and assumptions, acknowledge them, and bracket them in efforts to keep them from limiting accuracy in reporting. Sometimes qualitative studies are used initially to explore a topic and more quantitative studies are used to test or explain what was first described.
A good way to become more familiar with these scientific research methods, both quantitative and qualitative, is to look at journal articles, which are written in sections that follow these steps in the scientific process. Most psychological articles and many papers in the social sciences follow the writing guidelines and format dictated by the American Psychological Association (APA). In general, the structure follows: abstract (summary of the article), introduction or literature review, methods explaining how the study was conducted, results of the study, discussion and interpretation of findings, and references.
Link to Learning
Brené Brown is a bestselling author and social work professor at the University of Houston. She conducts grounded theory research by collecting qualitative data from large numbers of participants. In Brené Brown’s TED Talk The Power of Vulnerability , Brown refers to herself as a storyteller-researcher as she explains her research process and summarizes her results.
Research Methods and Objectives
The main categories of psychological research are descriptive, correlational, and experimental research. Research studies that do not test specific relationships between variables are called descriptive, or qualitative, studies . These studies are used to describe general or specific behaviors and attributes that are observed and measured. In the early stages of research, it might be difficult to form a hypothesis, especially when there is not any existing literature in the area. In these situations designing an experiment would be premature, as the question of interest is not yet clearly defined as a hypothesis. Often a researcher will begin with a non-experimental approach, such as a descriptive study, to gather more information about the topic before designing an experiment or correlational study to address a specific hypothesis. Some examples of descriptive questions include:
- “How much time do parents spend with their children?”
- “How many times per week do couples have intercourse?”
- “When is marital satisfaction greatest?”
The main types of descriptive studies include observation, case studies, surveys, and content analysis (which we’ll examine further in the module). Descriptive research is distinct from correlational research , in which psychologists formally test whether a relationship exists between two or more variables. Experimental research goes a step further beyond descriptive and correlational research and randomly assigns people to different conditions, using hypothesis testing to make inferences about how these conditions affect behavior. Some experimental research includes explanatory studies, which are efforts to answer the question “why” such as:
- “Why have rates of divorce leveled off?”
- “Why are teen pregnancy rates down?”
- “Why has the average life expectancy increased?”
Evaluation research is designed to assess the effectiveness of policies or programs. For instance, research might be designed to study the effectiveness of safety programs implemented in schools for installing car seats or fitting bicycle helmets. Do children who have been exposed to the safety programs wear their helmets? Do parents use car seats properly? If not, why not?
We have just learned about some of the various models and objectives of research in lifespan development. Now we’ll dig deeper to understand the methods and techniques used to describe, explain, or evaluate behavior.
All types of research methods have unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control over how or what kind of data was collected.
Types of Descriptive Research
Observational studies , also called naturalistic observation, involve watching and recording the actions of participants. This may take place in the natural setting, such as observing children at play in a park, or behind a one-way glass while children are at play in a laboratory playroom. The researcher may follow a checklist and record the frequency and duration of events (perhaps how many conflicts occur among 2-year-olds) or may observe and record as much as possible about an event as a participant (such as attending an Alcoholics Anonymous meeting and recording the slogans on the walls, the structure of the meeting, the expressions commonly used, etc.). The researcher may be a participant or a non-participant. What would be the strengths of being a participant? What would be the weaknesses?
In general, observational studies have the strength of allowing the researcher to see how people behave rather than relying on self-report. One weakness of self-report studies is that what people do and what they say they do are often very different. A major weakness of observational studies is that they do not allow the researcher to explain causal relationships. Yet, observational studies are useful and widely used when studying children. It is important to remember that most people tend to change their behavior when they know they are being watched (known as the Hawthorne effect ) and children may not survey well.
Case studies involve exploring a single case or situation in great detail. Information may be gathered with the use of observation, interviews, testing, or other methods to uncover as much as possible about a person or situation. Case studies are helpful when investigating unusual situations such as brain trauma or children reared in isolation. And they are often used by clinicians who conduct case studies as part of their normal practice when gathering information about a client or patient coming in for treatment. Case studies can be used to explore areas about which little is known and can provide rich detail about situations or conditions. However, the findings from case studies cannot be generalized or applied to larger populations; this is because cases are not randomly selected and no control group is used for comparison. (Read The Man Who Mistook His Wife for a Hat by Dr. Oliver Sacks as a good example of the case study approach.)
Surveys are familiar to most people because they are so widely used. Surveys enhance accessibility to subjects because they can be conducted in person, over the phone, through the mail, or online. A survey involves asking a standard set of questions to a group of subjects. In a highly structured survey, subjects are forced to choose from a response set such as “strongly disagree, disagree, undecided, agree, strongly agree”; or “0, 1-5, 6-10, etc.” Surveys are commonly used by sociologists, marketing researchers, political scientists, therapists, and others to gather information on many variables in a relatively short period of time. Surveys typically yield surface information on a wide variety of factors, but may not allow for an in-depth understanding of human behavior.
Surveys are useful in examining stated values, attitudes, opinions, and reporting on practices. However, they are based on self-report, or what people say they do rather than on observation, and this can limit accuracy. Validity refers to accuracy and reliability refers to consistency in responses to tests and other measures; great care is taken to ensure the validity and reliability of surveys.
Content analysis involves looking at media such as old texts, pictures, commercials, lyrics, or other materials to explore patterns or themes in culture. An example of content analysis is the classic history of childhood by Aries (1962) called “Centuries of Childhood” or the analysis of television commercials for sexual or violent content or for ageism. Passages in text or television programs can be randomly selected for analysis as well. Again, one advantage of analyzing work such as this is that the researcher does not have to go through the time and expense of finding respondents, but the researcher cannot know how accurately the media reflects the actions and sentiments of the population.
Secondary content analysis, or archival research, involves analyzing information that has already been collected or examining documents or media to uncover attitudes, practices, or preferences. There are a number of data sets available to those who wish to conduct this type of research. The researcher conducting secondary analysis does not have to recruit subjects but does need to know the quality of the information collected in the original study. And unfortunately, the researcher is limited to the questions asked and data collected originally.
Correlational and Experimental Research
When scientists passively observe and measure phenomena it is called correlational research . Here, researchers do not intervene and change behavior, as they do in experiments. In correlational research, the goal is to identify patterns of relationships, but not cause and effect. Importantly, with correlational research, you can examine only two variables at a time, no more and no less.
So, what if you wanted to test whether spending money on others is related to happiness, but you don’t have $20 to give to each participant in order to have them spend it for your experiment? You could use a correlational design—which is exactly what Professor Elizabeth Dunn (2008) at the University of British Columbia did when she conducted research on spending and happiness. She asked people how much of their income they spent on others or donated to charity, and later she asked them how happy they were. Do you think these two variables were related? Yes, they were! The more money people reported spending on others, the happier they were.
With a positive correlation , the two variables go up or down together. In a scatterplot, the dots form a pattern that extends from the bottom left to the upper right (just as they do in Figure 1). The r value for a positive correlation is indicated by a positive number (although, the positive sign is usually omitted). Here, the r value is .81. For the example above, the direction of the association is positive. This means that people who perceived the past month as being good reported feeling happier, whereas people who perceived the month as being bad reported feeling less happy.
A negative correlation is one in which the two variables move in opposite directions. That is, as one variable goes up, the other goes down. Figure 2 shows the association between the average height of males in a country (y-axis) and the pathogen prevalence (or commonness of disease; x-axis) of that country. In this scatterplot, each dot represents a country. Notice how the dots extend from the top left to the bottom right. What does this mean in real-world terms? It means that people are shorter in parts of the world where there is more disease. The r-value for a negative correlation is indicated by a negative number—that is, it has a minus (–) sign in front of it. Here, it is –.83.
Experiments are designed to test hypotheses (or specific statements about the relationship between variables ) in a controlled setting in an effort to explain how certain factors or events produce outcomes. A variable is anything that changes in value. Concepts are operationalized or transformed into variables in research which means that the researcher must specify exactly what is going to be measured in the study. For example, if we are interested in studying marital satisfaction, we have to specify what marital satisfaction really means or what we are going to use as an indicator of marital satisfaction. What is something measurable that would indicate some level of marital satisfaction? Would it be the amount of time couples spend together each day? Or eye contact during a discussion about money? Or maybe a subject’s score on a marital satisfaction scale? Each of these is measurable but these may not be equally valid or accurate indicators of marital satisfaction. What do you think? These are the kinds of considerations researchers must make when working through the design.
The experimental method is the only research method that can measure cause and effect relationships between variables. Three conditions must be met in order to establish cause and effect. Experimental designs are useful in meeting these conditions:
- The independent and dependent variables must be related. In other words, when one is altered, the other changes in response. The independent variable is something altered or introduced by the researcher; sometimes thought of as the treatment or intervention. The dependent variable is the outcome or the factor affected by the introduction of the independent variable; the dependent variable depends on the independent variable. For example, if we are looking at the impact of exercise on stress levels, the independent variable would be exercise; the dependent variable would be stress.
- The cause must come before the effect. Experiments measure subjects on the dependent variable before exposing them to the independent variable (establishing a baseline). So we would measure the subjects’ level of stress before introducing exercise and then again after the exercise to see if there has been a change in stress levels. (Observational and survey research does not always allow us to look at the timing of these events which makes understanding causality problematic with these methods.)
- The cause must be isolated. The researcher must ensure that no outside, perhaps unknown variables, are actually causing the effect we see. The experimental design helps make this possible. In an experiment, we would make sure that our subjects’ diets were held constant throughout the exercise program. Otherwise, the diet might really be creating a change in stress level rather than exercise.
A basic experimental design involves beginning with a sample (or subset of a population) and randomly assigning subjects to one of two groups: the experimental group or the control group . Ideally, to prevent bias, the participants would be blind to their condition (not aware of which group they are in) and the researchers would also be blind to each participant’s condition (referred to as “ double blind “). The experimental group is the group that is going to be exposed to an independent variable or condition the researcher is introducing as a potential cause of an event. The control group is going to be used for comparison and is going to have the same experience as the experimental group but will not be exposed to the independent variable. This helps address the placebo effect, which is that a group may expect changes to happen just by participating. After exposing the experimental group to the independent variable, the two groups are measured again to see if a change has occurred. If so, we are in a better position to suggest that the independent variable caused the change in the dependent variable . The basic experimental model looks like this:
The major advantage of the experimental design is that of helping to establish cause and effect relationships. A disadvantage of this design is the difficulty of translating much of what concerns us about human behavior into a laboratory setting.
Developmental Research Designs
Now you know about some tools used to conduct research about human development. Remember, research methods are tools that are used to collect information. But it is easy to confuse research methods and research design. Research design is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how. Developmental research designs are techniques used particularly in lifespan development research. When we are trying to describe development and change, the research designs become especially important because we are interested in what changes and what stays the same with age. These techniques try to examine how age, cohort, gender, and social class impact development.
The majority of developmental studies use cross-sectional designs because they are less time-consuming and less expensive than other developmental designs. Cross-sectional research designs are used to examine behavior in participants of different ages who are tested at the same point in time. Let’s suppose that researchers are interested in the relationship between intelligence and aging. They might have a hypothesis (an educated guess, based on theory or observations) that intelligence declines as people get older. The researchers might choose to give a certain intelligence test to individuals who are 20 years old, individuals who are 50 years old, and individuals who are 80 years old at the same time and compare the data from each age group. This research is cross-sectional in design because the researchers plan to examine the intelligence scores of individuals of different ages within the same study at the same time; they are taking a “cross-section” of people at one point in time. Let’s say that the comparisons find that the 80-year-old adults score lower on the intelligence test than the 50-year-old adults, and the 50-year-old adults score lower on the intelligence test than the 20-year-old adults. Based on these data, the researchers might conclude that individuals become less intelligent as they get older. Would that be a valid (accurate) interpretation of the results?
No, that would not be a valid conclusion because the researchers did not follow individuals as they aged from 20 to 50 to 80 years old. One of the primary limitations of cross-sectional research is that the results yield information about age differences not necessarily changes with age or over time. That is, although the study described above can show that in 2010, the 80-year-olds scored lower on the intelligence test than the 50-year-olds, and the 50-year-olds scored lower on the intelligence test than the 20-year-olds, the data used to come up with this conclusion were collected from different individuals (or groups of individuals). It could be, for instance, that when these 20-year-olds get older (50 and eventually 80), they will still score just as high on the intelligence test as they did at age 20. In a similar way, maybe the 80-year-olds would have scored relatively low on the intelligence test even at ages 50 and 20; the researchers don’t know for certain because they did not follow the same individuals as they got older.
It is also possible that the differences found between the age groups are not due to age, per se, but due to cohort effects. The 80-year-olds in this 2010 research grew up during a particular time and experienced certain events as a group. They were born in 1930 and are part of the Traditional or Silent Generation. The 50-year-olds were born in 1960 and are members of the Baby Boomer cohort. The 20-year-olds were born in 1990 and are part of the Millennial or Gen Y Generation. What kinds of things did each of these cohorts experience that the others did not experience or at least not in the same ways?
You may have come up with many differences between these cohorts’ experiences, such as living through certain wars, political and social movements, economic conditions, advances in technology, changes in health and nutrition standards, etc. There may be particular cohort differences that could especially influence their performance on intelligence tests, such as education level and use of computers. That is, many of those born in 1930 probably did not complete high school; those born in 1960 may have high school degrees, on average, but the majority did not attain college degrees; the young adults are probably current college students. And this is not even considering additional factors such as gender, race, or socioeconomic status. The young adults are used to taking tests on computers, but the members of the other two cohorts did not grow up with computers and may not be as comfortable if the intelligence test is administered on computers. These factors could have been a factor in the research results.
Another disadvantage of cross-sectional research is that it is limited to one time of measurement. Data are collected at one point in time and it’s possible that something could have happened in that year in history that affected all of the participants, although possibly each cohort may have been affected differently. Just think about the mindsets of participants in research that was conducted in the United States right after the terrorist attacks on September 11, 2001.
Longitudinal research designs
Longitudinal research involves beginning with a group of people who may be of the same age and background (cohort) and measuring them repeatedly over a long period of time. One of the benefits of this type of research is that people can be followed through time and be compared with themselves when they were younger; therefore changes with age over time are measured. What would be the advantages and disadvantages of longitudinal research? Problems with this type of research include being expensive, taking a long time, and subjects dropping out over time. Think about the film, 63 Up , part of the Up Series mentioned earlier, which is an example of following individuals over time. In the videos, filmed every seven years, you see how people change physically, emotionally, and socially through time; and some remain the same in certain ways, too. But many of the participants really disliked being part of the project and repeatedly threatened to quit; one disappeared for several years; another died before her 63rd year. Would you want to be interviewed every seven years? Would you want to have it made public for all to watch?
Longitudinal research designs are used to examine behavior in the same individuals over time. For instance, with our example of studying intelligence and aging, a researcher might conduct a longitudinal study to examine whether 20-year-olds become less intelligent with age over time. To this end, a researcher might give an intelligence test to individuals when they are 20 years old, again when they are 50 years old, and then again when they are 80 years old. This study is longitudinal in nature because the researcher plans to study the same individuals as they age. Based on these data, the pattern of intelligence and age might look different than from the cross-sectional research; it might be found that participants’ intelligence scores are higher at age 50 than at age 20 and then remain stable or decline a little by age 80. How can that be when cross-sectional research revealed declines in intelligence with age?
Since longitudinal research happens over a period of time (which could be short term, as in months, but is often longer, as in years), there is a risk of attrition. Attrition occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, die, or simply become disinterested in participating over time. Researchers should account for the possibility of attrition by enrolling a larger sample into their study initially, as some participants will likely drop out over time. There is also something known as selective attrition— this means that certain groups of individuals may tend to drop out. It is often the least healthy, least educated, and lower socioeconomic participants who tend to drop out over time. That means that the remaining participants may no longer be representative of the whole population, as they are, in general, healthier, better educated, and have more money. This could be a factor in why our hypothetical research found a more optimistic picture of intelligence and aging as the years went by. What can researchers do about selective attrition? At each time of testing, they could randomly recruit more participants from the same cohort as the original members, to replace those who have dropped out.
The results from longitudinal studies may also be impacted by repeated assessments. Consider how well you would do on a math test if you were given the exact same exam every day for a week. Your performance would likely improve over time, not necessarily because you developed better math abilities, but because you were continuously practicing the same math problems. This phenomenon is known as a practice effect. Practice effects occur when participants become better at a task over time because they have done it again and again (not due to natural psychological development). So our participants may have become familiar with the intelligence test each time (and with the computerized testing administration). Another limitation of longitudinal research is that the data are limited to only one cohort.
Sequential research designs
Sequential research designs include elements of both longitudinal and cross-sectional research designs. Similar to longitudinal designs, sequential research features participants who are followed over time; similar to cross-sectional designs, sequential research includes participants of different ages. This research design is also distinct from those that have been discussed previously in that individuals of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and to account for the possibility of cohort and/or time of measurement effects. In 1965, K. Warner Schaie described particular sequential designs: cross-sequential, cohort sequential, and time-sequential. The differences between them depended on which variables were focused on for analyses of the data (data could be viewed in terms of multiple cross-sectional designs or multiple longitudinal designs or multiple cohort designs). Ideally, by comparing results from the different types of analyses, the effects of age, cohort, and time in history could be separated out.
Challenges Conducting Developmental Research
The previous sections describe research tools to assess development across the lifespan, as well as the ways that research designs can be used to track age-related changes and development over time. Before you begin conducting developmental research, however, you must also be aware that testing individuals of certain ages (such as infants and children) or making comparisons across ages (such as children compared to teens) comes with its own unique set of challenges. In the final section of this module, let’s look at some of the main issues that are encountered when conducting developmental research, namely ethical concerns, recruitment issues, and participant attrition.
You may already know that Institutional Review Boards (IRBs) must review and approve all research projects that are conducted at universities, hospitals, and other institutions (each broad discipline or field, such as psychology or social work, often has its own code of ethics that must also be followed, regardless of institutional affiliation). An IRB is typically a panel of experts who read and evaluate proposals for research. IRB members want to ensure that the proposed research will be carried out ethically and that the potential benefits of the research outweigh the risks and potential harm (psychological as well as physical harm) for participants.
What you may not know though, is that the IRB considers some groups of participants to be more vulnerable or at-risk than others. Whereas university students are generally not viewed as vulnerable or at-risk, infants and young children commonly fall into this category. What makes infants and young children more vulnerable during research than young adults? One reason infants and young children are perceived as being at increased risk is due to their limited cognitive capabilities, which makes them unable to state their willingness to participate in research or tell researchers when they would like to drop out of a study. For these reasons, infants and young children require special accommodations as they participate in the research process. Similar issues and accommodations would apply to adults who are deemed to be of limited cognitive capabilities.
When thinking about special accommodations in developmental research, consider the informed consent process. If you have ever participated in scientific research, you may know through your own experience that adults commonly sign an informed consent statement (a contract stating that they agree to participate in research) after learning about a study. As part of this process, participants are informed of the procedures to be used in the research, along with any expected risks or benefits. Infants and young children cannot verbally indicate their willingness to participate, much less understand the balance of potential risks and benefits. As such, researchers are oftentimes required to obtain written informed consent from the parent or legal guardian of the child participant, an adult who is almost always present as the study is conducted. In fact, children are not asked to indicate whether they would like to be involved in a study at all (a process known as assent) until they are approximately seven years old. Because infants and young children cannot easily indicate if they would like to discontinue their participation in a study, researchers must be sensitive to changes in the state of the participant (determining whether a child is too tired or upset to continue) as well as to parent desires (in some cases, parents might want to discontinue their involvement in the research). As in adult studies, researchers must always strive to protect the rights and well-being of the minor participants and their parents when conducting developmental research.
An additional challenge in developmental science is participant recruitment. Recruiting university students to participate in adult studies is typically easy. Unfortunately, young children cannot be recruited in this way. Given these limitations, how do researchers go about finding infants and young children to be in their studies?
The answer to this question varies along multiple dimensions. Researchers must consider the number of participants they need and the financial resources available to them, among other things. Location may also be an important consideration. Researchers who need large numbers of infants and children may attempt to recruit them by obtaining infant birth records from the state, county, or province in which they reside. Researchers can choose to pay a recruitment agency to contact and recruit families for them. More economical recruitment options include posting advertisements and fliers in locations frequented by families, such as mommy-and-me classes, local malls, and preschools or daycare centers. Researchers can also utilize online social media outlets like Facebook, which allows users to post recruitment advertisements for a small fee. Of course, each of these different recruitment techniques requires IRB approval. And if children are recruited and/or tested in school settings, permission would need to be obtained ahead of time from teachers, schools, and school districts (as well as informed consent from parents or guardians).
And what about the recruitment of adults? While it is easy to recruit young college students to participate in research, some would argue that it is too easy and that college students are samples of convenience. They are not randomly selected from the wider population, and they may not represent all young adults in our society (this was particularly true in the past with certain cohorts, as college students tended to be mainly white males of high socioeconomic status). In fact, in the early research on aging, this type of convenience sample was compared with another type of convenience sample—young college students tended to be compared with residents of nursing homes! Fortunately, it didn’t take long for researchers to realize that older adults in nursing homes are not representative of the older population; they tend to be the oldest and sickest (physically and/or psychologically). Those initial studies probably painted an overly negative view of aging, as young adults in college were being compared to older adults who were not healthy, had not been in school nor taken tests in many decades, and probably did not graduate high school, let alone college. As we can see, recruitment and random sampling can be significant issues in research with adults, as well as infants and children. For instance, how and where would you recruit middle-aged adults to participate in your research?
Another important consideration when conducting research with infants and young children is attrition . Although attrition is quite common in longitudinal research in particular (see the previous section on longitudinal designs for an example of high attrition rates and selective attrition in lifespan developmental research), it is also problematic in developmental science more generally, as studies with infants and young children tend to have higher attrition rates than studies with adults. Infants and young children are more likely to tire easily, become fussy, and lose interest in the study procedures than are adults. For these reasons, research studies should be designed to be as short as possible – it is likely better to break up a large study into multiple short sessions rather than cram all of the tasks into one long visit to the lab. Researchers should also allow time for breaks in their study protocols so that infants can rest or have snacks as needed. Happy, comfortable participants provide the best data.
Lifespan development is a fascinating field of study – but care must be taken to ensure that researchers use appropriate methods to examine human behavior, use the correct experimental design to answer their questions, and be aware of the special challenges that are part-and-parcel of developmental research. After reading this module, you should have a solid understanding of these various issues and be ready to think more critically about research questions that interest you. For example, what types of questions do you have about lifespan development? What types of research would you like to conduct? Many interesting questions remain to be examined by future generations of developmental scientists – maybe you will make one of the next big discoveries!
Lifespan development is the scientific study of how and why people change or remain the same over time. As we are beginning to see, lifespan development involves multiple domains and many ages and stages that are important in and of themselves, but that are also interdependent and dynamic and need to be viewed holistically. There are many influences on lifespan development at individual and societal levels (including genetics); cultural, generational, economic, and historical contexts are often significant. And how developmental research is designed and data are collected, analyzed, and interpreted can affect what is discovered about human development across the lifespan.
Lifespan Development Copyright © 2020 by Julie Lazzara is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.
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Review article, contribution of developmental psychology to the study of social interactions: some factors in play, joint attention and joint action and implications for robotics.
- CLLE, Université de Toulouse, CNRS, UT2J, Toulouse, France
Children exchange information through multiple modalities, including verbal communication, gestures and social gaze and they gradually learn to plan their behavior and coordinate successfully with their partners. The development of joint attention and joint action, especially in the context of social play, provides rich opportunities for describing the characteristics of interactions that can lead to shared outcomes. In the present work, we argue that human–robot interactions (HRI) can benefit from these developmental studies, through influencing the human’s perception and interpretation of the robot’s behavior. We thus endeavor to describe some components that could be implemented in the robot to strengthen the feeling of dealing with a social agent, and therefore improve the success of collaborative tasks. Focusing in particular on motor precision, coordination, and anticipatory planning, we discuss the question of complexity in HRI. In the context of joint activities, we highlight the necessity of (1) considering multiple speech acts involving multimodal communication (both verbal and non-verbal signals), and (2) analyzing separately the forms and functions of communication. Finally, we examine some challenges related to robot competencies, such as the issue of language and symbol grounding, which might be tackled by bringing together expertise of researchers in developmental psychology and robotics.
Developmental psychologists aim at describing and explaining changes across the life span in a wide range of areas such as social, emotional, and cognitive abilities. Focusing on childhood is a way of grasping numerous changes, especially in terms protect of communication: infants gradually learn to identify the common ground they have with others and engage in social interactions. The development of such abilities relies on the personal experiences shared between partners in specific contexts ( Liebal et al., 2013 ), among which social play may offer particularly rich opportunities for children to acquire joint action and joint attention skills. Studying the different forms and functions of communication in this context paves the way for identifying the necessary ingredients for effective joint activities and therefore better understanding the architecture of human–social interactions. Even though the concept of effectiveness may cover different theoretical frameworks, the latter objectives have several applications, for example in supporting children with atypical development, especially when they have difficulty communicating both verbally and non-verbally (e.g., children with autism spectrum disorders, ASD), but also in the field of artificial intelligence. The role of robots in society raises indeed a lot of debates and challenges, as they share more and more space and tasks with humans, for instance in service robotics to assist elderly people. The robots’ ability to initiate and respond to social interactions is one of the key factors that will shape their integration in our everyday life in the future. Researchers in social robotics have been working on the question of joint action for over two decades now, sometimes in collaboration with developmental psychologists (e.g., Scassellati, 2000 ), in order to improve robots’ motor and communicative skills. Developmental models of human communicative behavior can indeed help define the components to implement in human–robot interactions (HRI), so as to build rich and natural joint activities ( Breazeal et al., 2004 ; Lemaignan et al., 2017 ).
The objective of this paper is twofold. First, we intend to present the point of view and some research perspectives of developmental psychologists on joint attention and joint action, in particular in the context of social play. To this end, we will also define, starting from studies on non-human primates, what can be regarded as complex (or rich) and natural (or effective) interactions in both human communication and HRI. Second, we aim to show the extent to which the above-mentioned issues may be of interest to roboticists, in helping conceptualize and implement some variables associated with joint attention and joint action in the context of HRI. Collaborative tasks involving robot and human partners, regarded as tantamount to children’s social play, will thus be considered through the prism of pragmatic communication, allowing researchers to dissociate the forms and the functions of communication.
How Does Communication Develop in the Context of Social Play?
The definitions of play include a wide range of activities, which makes it difficult to determine where play begins and where it ends, even though it is traditionally associated with positive affective valence ( Garvey, 1990 ). Play, which occurs in several animal species (most notably in mammals), has been argued to allow “practice of real-world skills in a relatively safe environment” ( Byrne, 2015 ). We will focus here on social play in human children, which may also enable them, as highlighted by Bruner (1973) , to “learn by doing” as they interact with one or several partners. At the individual level, children can indeed explore and enhance specific skills like motor control and creativity, while developing for example cooperation abilities at the social level. The concepts of artifact-mediated and object-oriented action, originally formulated by Vygotsky (1999) , are particularly relevant to describe these situations: the relationship between the child and the surrounding objects is indeed mediated by cultural means, tools, and signs. Studying the development of play can therefore reveal how children come to represent and think about their environment.
Social attention is a crucial capacity for the emergence of these play situations, allowing children to focus on some of the other’s characteristics such as the facial expressions, gaze direction, gestures, and vocalizations. When the direction of another’s attention has been identified (for example through gaze following or point following), we can shift our own attention to focus at the same time on the same external object or event as our partner. This process of joint attention is usually inferred from behavioral cues, including mainly gaze alternation between one’s partner and a specific referent ( Bourjade, 2017 ). Joint attention seems therefore necessary for individuals to perform joint action, i.e., to coordinate their actions in space and time to produce a joint outcome, whether it involves here symbolic play (with or without objects), construction toys, board games or any other forms of play.
Joint attention and joint action begin to appear at the end of the first year in human development ( Carpenter et al., 1998 ), gradually allowing children to integrate the notion of common ground and engage in social interactions. The development of gaze understanding, which has been widely studied, plays a key role in this regard. It was for example shown in a study using habituation-of-looking-time procedure that infants start to understand ecologically valid instances of social gaze between two adults interacting, and to have expectations concerning gaze target at 10 months of age ( Beier and Spelke, 2012 ). Besides, responsive joint attention skills (e.g., gaze following and point following) have been reported to emerge before initiative joint attention skills, from 8 months of age ( Corkum and Moore, 1998 ; Beuker et al., 2013 ).
However, depending on the authors, the definitions of these social-cognitive skills can be more or less demanding, the main difference lying in whether or not individuals have mutual understanding of their shared focus of attention. The ability to “know together” that we are attending to the same thing as our partner has sometimes been referred to as shared attention ( Emery, 2000 ; Shteynberg, 2015 ), which would develop in parallel with shared intentionality ( Tomasello and Carpenter, 2007 ). The latter involves the motivation to share goals and intentions with the other, as well as forms of cognitive representation for doing so. This ability has been argued to constitute a hallmark of the human species ( Tomasello et al., 2005 ), even though it is particularly difficult to assess when verbal language is not available as a clue to these representations (in pre-linguistic children or non-human primates). Similarly, joint action may rely solely on the learning of the cues that appear significant (e.g., gestures and eye contact) to coordinate actions in space and time with a partner, or it may also involve, in a more demanding perspective, the common and explicit knowledge of the objectives of the activity and of the way to achieve them ( Tomasello and Carpenter, 2007 ).
Joint attention and joint action, whether they are accompanied or not with shared and explicit intentions, thus allow children to participate with others in collaborative activities in which each partner benefits from the joint outcome and/or from the interaction in itself. In a series of experiments, the ability to coordinate with a partner in social games was shown to significantly improve between 18 and 24 months of age, whether the games involved complementary or similar roles ( Warneken et al., 2006 ). In the first game of this study, one person had to send a wooden block down one of a tube mounted on a box on a 20 degrees incline, while the other person had to catch it at the other end with a tin can that made a rattling sound. Two tubes were mounted in parallel so that individuals could perform in turn the different roles. In the second game, two persons had to make a wooden block jump on a small trampoline (67 cm diameter ring covered with cloth) by holding the rim on opposite sides. The trampoline collapsed when being held on only one side. Children successfully participated in both games, although the 24 month-olds were more proficient than the 18 month-olds, and they all produced at least one communicative attempt to reengage the adult partner when the latter stopped participating in the activity. Children for example pointed at the object, and/or vocalized while looking at the adult, which was regarded as evidence for a uniquely human form of cooperation, involving shared intentionality ( Warneken et al., 2006 ). A less “mentalistic” interpretation could be proposed ( D’Entremont and Seamans, 2007 ), but these results nevertheless highlight children’s motivation for reinstating joint action toward a shared goal. The development of this capacity has received much attention from researchers, as the initiation of joint attention appears to be strongly related to language comprehension and production in the second and third year of life ( Colonnesi et al., 2010 ; Cochet and Byrne, 2016 ), as well as to theory of mind ability (e.g., Charman et al., 2000 ; Milward et al., 2017 ) in both typical and atypical development (e.g., Adamson et al., 2017 ).
In addition, the observation of children’s behavior during collaborative activities may lead to a thorough description of multimodal communication (e.g., gaze, facial expressions, gestures, and verbal language) and of the way its components become coordinated. For example, the production of gestures gradually coordinates with gaze in the course of development. Children start to produce pointing gestures to orient the attention of another person around 12 months of age; an object, a person or an event can become the shared focus of attention but then children do not usually look at their partner while they point ( Franco and Butterworth, 1996 ). A couple of months later, they are able to alternate their gaze between their partner and the object of interest, which represents a key feature of intentional triadic interactions ( Cochet and Vauclair, 2010 ). At 16 months of age, gaze toward the adult can precede the production of pointing ( Franco and Butterworth, 1996 ), suggesting that children may thus take into account the partner’s attentional state before initiating communication ( Lamaury et al., 2017 ).
Children also gradually learn to take account of their partner’s facial expressions to infer their emotional state and adjust their response accordingly. Infants are sensitive to the characteristics of faces from very early on; newborns look for example significantly longer at happy expressions than at fearful ones, demonstrating some discrimination skills ( Farroni et al., 2007 ). The still-face paradigm, initially designed by Tronick et al. (1978) also suggests that infants have expectations about interactional reciprocity from a few months of age, partly relying on emotional expression. This sensitivity manifests itself in specific behavioral and physiological responses (e.g., reduced positive affect and gazing at the parent, increased negative affect, rise in facial skin temperature) when the mother puts on a neutral and unresponsive face, after a period of spontaneous play with his/her infant ( Aureli et al., 2015 ). The ability to recognize and identify facial expressions of basic emotions further develops in preschool children, before they can understand a few months later the external causes of emotions and then, around 5 years of age, the role of other’s desires or beliefs in emotional expression ( Pons et al., 2004 ).
During play interactions, being attentive to the other’s facial expressions allows each partner to consider the emotional nature of the signals (e.g., joy, surprise, and frustration) and to possibly modify his/her own behavior to change or maintain this emotional state. The development of facial expression perception thus plays a key role in the emergence of joint actions, in coordination with other communicative modalities. Facial expressions are indeed usually synchronized with vocalizations and/or gestures, and this from infancy.
The vocal and the gestural modalities also become more and more coordinated as children grow older, which represents a key feature of human communication as we use gestures as we speak throughout our life. Communicative gestures are first complemented by vocalizations, whose prosodic patterns may already code for semantic and pragmatic functions ( Leroy et al., 2009 ). In the second year of life, children then produce their first gesture-word combinations, which have an important role in the transition to the two-word stage (e.g., Butcher and Goldin-Meadow, 2000 ). Pointing and conventional gestures (e.g., waving goodbye, gestural agreement, and refusal: Guidetti, 2002 , 2005 ) remain in the child repertory after the two-word stage, but other forms of gestural-vocal coordination are observed from 3 years of age with the emergence of co-speech gestures. Although we are usually not aware of producing or perceiving them, co-speech gestures can lend rhythm, emphasize speech and sometimes serve deictic or iconic functions. The deictic presentation of pointing gesture can for example be combined with vocal pointing , performed through syntactic or prosodic means ( Lœvenbruck et al., 2008 ). Such coordination between the vocal and gestural modalities is omnipresent in adults and play a crucial role in face-to-face communication for both speaker and listener (e.g., McNeill, 2000 ; Kendon, 2004 ).
Moreover, the characteristics of gaze, gestures, and vocalizations and their coordination may vary according to the communicative function of the signal. A gesture can indeed serve different purposes, starting with the traditional distinction between imperative and declarative functions ( Bates et al., 1975 ). Imperative gestures are used to request a specific object or action from a partner whereas declarative gestures are used to share interest with the other about some referent or provide him/her with information that might be useful. Imperative and declarative pointing, which both represent powerful means of establishing joint attention, have been extensively studied and compared: hand shape and body posture were shown to differ according to the communicative function of the pointing gesture ( Cochet et al., 2014 ), as well as the frequency of gaze alternation between the partner and the referent and the frequency of vocalizations ( Cochet and Vauclair, 2010 ). These comparisons (see section “Pragmatics in HRI: Which Ingredients Are Necessary for Effective Interactions?” for more detailed results) thus highlight the strong relationship between the form of the gestures (in the broad sense, i.e., including visual and vocal behavior in addition to movement kinematics and hand shapes) and pragmatic features in children, even semantic ones in adults ( Cochet and Vauclair, 2014 ).
To sum up, when two children are playing together or when a child is playing with an adult, they do so in the framework of joint action; they attend to a common situation and use multimodal communication to initiate, maintain, or respond to the interaction. These three different roles in the interaction can be assessed with the Early Social Communication Scales, in particular with the French version ( Guidetti and Tourrette, 2017 ). In an evaluation situation, giving the child the opportunity to initiate the interaction is particularly crucial in atypical development, for example in children with ASD. The initiation of shared attention is a key ability in this context as it allows joint action coordination ( Vesper et al., 2016 ) and has also significant consequences on the development of cognitive and emotional processes ( Shteynberg, 2015 ). Whether this coordination relies on the representation and the understanding of the other’s intentions or only on behavioral cues is a challenging question, as we do not have any direct access to the other’s subjectivity. In the field of HRI, an objective that appears sufficiently ambitious for now, or at least the one we chose to focus on in the present review, is to design robots able to identify the observable changes in the human’s behavior, in order to make the right inferences and thus the appropriate decisions in the interaction. This appears as an essential condition for a successful exchange between a robot and a human, which can depend on the joint outcome (has the common goal been reached?), but also on the way the interaction has been perceived by each individual, for example in terms of coordination between gaze and gesture and fluidity of movement ( Hough and Schlangen, 2016 ). The richness of communication here lies indeed in the ability of each partner to integrate multiple communicative cues in a way that what will seem natural to the humans, i.e., that will be close to peer interaction in everyday life.
This appears as a complex ability and probably the most challenging one to replicate in HRI. In pursuit of this objective, we now need to further describe the concept of appropriateness and propose a frame to determine the relative importance and the relative complexity of the different behaviors observed during joint activities such as social play.
To What Extent Can Interactions Be Characterized as Complex ?
Smith (2015) has argued that “development, like evolution and culture, is a process that creates complexity by accumulating change.” This perspective applies to the development of social interactions, from the emergence of joint attention to coordinated and multimodal communication that enable joint action. Several attempts have been made in developmental robotics to explore the cognitive, social, and motivational dynamics of human interactions ( Oudeyer, 2017 ); algorithmic and robotic models can then be used to study the developmental processes involved for instance in imitation ( Demiris and Meltzoff, 2008 ) or language ( Cangelosi et al., 2010 ). In this context, roboticists aim at designing systems allowing for self-organized and “progressive increase in the complexity” of the robot’s behavior ( Oudeyer et al., 2007 ).
To benefit further from their exchanges, developmentalists and roboticists may therefore need to frame the study of HRI by disambiguating the concept of complexity. Because “complicated systems will be best understood at the lowest possible level” ( Smith, 2015 ), we aim to differentiate different levels of complexity depending on the nature of the elements to take into account for decision making. This analysis will allow us to go forward in the study of joint attention and joint action and define what is implied by the qualifying terms “complex” (or rich) and “appropriate” (or effective) when referring to interactions.
To this end, we used a categorization recently proposed in research on animal behavior, including human and non-human primates, to define the concept of complexity ( Cochet and Byrne, 2015 ). Three dimensions have been described: motor precision, coordination, and anticipatory planning, which can relate to both individual and social activities. The authors argue that “the complexity of a given mechanism/behavior can be assessed by distinguishing which of these three dimensions are involved and to what degree,” which may “clarify our understanding of animal behavior and cognition.” Such analysis applied to joint attention and joint action, although there may be other ways of untangling the question of complexity, may here allow researchers to dissect the different factors involved in social interactions for each dimension, and thus help them assess the “manipulability” of these factors in HRI.
In order to make appropriate decisions in a collaborative task, i.e., decisions leading to the desired joint outcome and/or decisions that approach the characteristics of human interactions, the robot first needs to recognize specific patterns in his/her partners’ behavior, without asking for agreement or information for all actions. The robot can for example rely on gaze direction, manual movements or body posture to identify the human’s attentional and intentional states and thus define the most useful role it can play in the interaction. By way of illustration, if a human and a robot share the common goal of building a pile with four cubes in a definite order and putting a triangle at the top, each of them can perform different actions: they can grasp an object (a cube or a triangle) on the table, grasp an object on the pile, give an object to the partner, support the pile while the partner places a cube on it, etc. Other actions can emerge, for example if the pile collapses or if one agent does not pile the cubes in the correct order ( Clodic et al., 2014 ). Individuals can then blame each other, or give each other some instructions. In addition to the perception of its own environment, the robot thus has to observe the activity of the human and take his/her perspective (e.g., to determine whether an object is reachable for the other).
Motor precision is therefore necessary in this context to obtain flexible and human-aware shared plan execution ( Devin and Alami, 2016 ), as it enables a selective shift of attention toward aspects of the environment that will become shared knowledge, which has also been described as the accuracy of shared attention states ( Shteynberg, 2015 ). First, the emergence of joint attention requires to properly use gaze and/or pointing gesture to localize the object or event referred to. Verbal cues also demand particularly fine motor skills through speech articulators. Second, joint action necessitates some motor control to reach the expected outcome, hence the importance of evaluating beforehand human motor skills, especially during development, as well as the technical capabilities of the robot. Following on from the previous example, children’s grasping skills in relation to the size of the cubes as well as the characteristics of robotic gripper to handle objects have to be finely described.
Moreover, recent experimental findings have shown that the execution of object-oriented actions is influenced by the social context such as the relative position of another person and the degree of familiarity with this person ( Gianelli et al., 2013 ). Individuals perform for example more fluent reach-to-grasp movements, with lower acceleration peaks and longer reaction time when a partner is located close enough to be able to intervene on the same object than when he/she is farther away ( Quesque et al., 2013 ). In addition, there is a significant relationship between the kinematic features of the actions and the actor’s explicit social intention: movements have longer durations, higher elevations and longer reaction times when individuals place an object on a table for another person than when they place the object for a later personal use ( Quesque and Coello, 2015 ). These variations, although they do not seem to be intentionally produced, have been suggested to facilitate the partner’s detection of planned actions, thus enhancing potential interactions. These kinematic effects were indeed shown to influence the subsequent motor productions of an observer ( Quesque et al., 2015 ). The motor characteristics of actions performed in a social context may therefore prime the perceiver to prepare and anticipate appropriate motor responses in the interaction.
The second dimension that can allow us to understand the complexity of joint activities pertains to the coordination between several communicative modalities and between interacting individuals. Whether joint action involves complementary or similar roles, it can be performed through several coordination processes, which can determine the efficiency of shared attention states ( Shteynberg, 2015 ). Efficiency requires here a representational shift from the first-person singular to the first-person plural, as the partners attend to the same referent at the same time. The ability to monitor each other’s attention and action, using behavioral cues such as gaze direction, facial expressions, gestures, and speech is essential for successful coordination. The intentional production of communicative signals, representing hints for one’s partner, is also an efficient way of achieving joint outcomes.
Coordination is therefore necessary first at the individual level, so that the different communicative modalities such as gestures and gaze synchronize or follow one another in a natural order, i.e., acceptable with regard to human interaction patterns (see above). Each agent can then make decisions based on these signals, moderate their behavior accordingly and thus coordinate at the social level to reach a common objective. The ability to adjust one’s behavior to others’ actions during collaborative activities (including play) has been argued to “reach a higher degree of complexity when intentional and referential signals are directly addressed to specific individuals” ( Cochet and Byrne, 2015 ). In order to build the pile of cubes, interacting partners can then for example point toward a specific cube or ask the other to wait before placing another cube.
In those cases, coordination processes can be enhanced by predicting the effects of each other’s actions on joint outcomes and by distributing tasks effectively ( Vesper et al., 2016 ). This ability involves the third dimension characterizing the question of complexity, namely the dimension of anticipatory planning ( Cochet and Byrne, 2015 ). It requires to go beyond the immediate perception of the environment and represent the relationship between a sequence of actions and a precise goal. At the individual level, planning ability implies to mentally review an action sequence in anticipation of a future need (e.g., selecting a specific cube in a first room in order to build a pile of cubes in another room). At the social level, planning ability allows individuals to predict the other’s behavior and adjust one’s own sequence of actions, leading to a better coordination. Whether the ability to make such inferences necessitates to mentalize about others’ inner states (e.g., beliefs and preferences) is still subject of debate, but again, this question may not be central in the context of joint attention and joint action between a robot and a human.
The above-described categorization can therefore provide a common ground between ethologists, psychologists, and roboticists that may clarify which dimensions need to be considered in an attempt to implement the characteristics of motor precision, coordination and anticipatory planning in human–robot joint activities (see Table 1 for an overview). The objective is to approach the complexity (or richness) of human interactions and obtain appropriate (or effective) responses from robots with regard to these different dimensions.
TABLE 1. Complexity in HRI: illustration of three dimensions at the individual and social levels (adapted from Cochet and Byrne, 2015 ).
Pragmatics in HRI: Which Ingredients Are Necessary for Effective Interactions?
The increasing complexity of communicative abilities (complexity that involves the three above-mentioned dimensions) in the course of human development leads to a rich potential of interactions. Children actively go through different stages allowing them to engage successfully in joint activities, i.e., to operate within their physical environment, coordinate with other people, plan their own behavior and anticipate their partners’. Intending to model, at least partially, human developmental pathway seems a fruitful way of designing robots that can effectively initiate and respond to communicative situations. Such enterprise, although still recent, has given rise to a substantial amount of literature in robotics, especially from the 2000s, covering several sub-fields such as for example developmental and epigenetic robotics, cognitive systems and social robotics. Several journals, including both HRI experimental studies and computational modeling, focus entirely on these questions (e.g., IEEE Transactions on Cognitive and Developmental Systems, Journal of Human-Robot Interaction, Journal of Social Robotics ), and numerous conferences also take place every year, whose proceedings are usually available online 1 .
The data from developmental psychology described in the first section, coupled with the framework proposed in the second section to help researchers define complex and effective HRI, may contribute to this growing body of work. To this effect, it seems necessary (1) to consider the multimodality of interactions and (2) to adopt a pragmatic perspective to be based upon an accurate representation of human communicative behaviors. Indeed, children learn to communicate through joint activities with adults who combine various forms of expressions, serving various functions. In the course of development, children gradually integrate the dissociation between the form and the function of language – they become more and more flexible in understanding that a single form can serve different functions and reciprocally, that a single function can be expressed through several forms. Language is here regarded as more than a medium to convey an information, in agreement with a proposition that was developed in the speech act theory ( Austin, 1962 ; Searle and Vanderveken, 1985 ). Language would be way of acting on the environment, of “doing things with words,” independently of its structural properties. Initially aiming at describing the relationships between the forms and functions of linguistic utterances, this theory defines several speech acts, depending on whether one intends to assert, comment, warn, request, deplore, etc. This theory has later been adapted to non-verbal behavior (e.g., McNeill, 1998 ; Guidetti, 2002 ). The form still refers to the message structure, but applies to the whole body, including the posture, the structure of communicative gestures (kinematic features and hand shape), gaze and facial expressions. These non-verbal signals can be used in complementarity with speech or be used alone for example in the case of conventional gestures (see Guidetti, 2002 ). The function refers to the illocutionary force of the speech act (what one achieves by speaking), in other words here to the effect of these communicative acts in a specific context, thus giving some insight into the signaller’s intention. Gestures, and especially the conventional gestures produced by children during the prelinguistic period, are thus regarded as genuine communicative acts, with a propositional content that can equal the one expressed by words. For instance, agreeing and refusing can be expressed gesturally by nodding or shaking one’s head. The separate analysis of the forms and functions of communication, as well as the description of the different modalities involved during interactions, therefore provide a key framework to help define what capacities the robot should be equipped with to ensure efficient collaboration with humans.
In this perspective, Mavridis (2015) has proposed a list of “ten desiderata that human–robot systems should fulfill” to maximize communication effectiveness. One of the guiding lines relates to the importance of considering multiple speech acts, for both verbal and non-verbal communication, and not restrict the robot competencies to “motor command requests.” In the same way as imperative gestures (see section “How Does Communication Develop in the Context of Social Play?”) are generally understood and produced later than declarative gestures in human development ( Camaioni et al., 2004 ), robotic systems initially aimed to assign the robot a servant role, with the human driving the interaction. Devising wider robots’ pragmatic abilities is a first step toward the conception of human–robot shared plans. The robot may for example comment on the pile of cubes as it is being built (see example section “To What Extent Can Interactions Be Characterized as complex ?”) to support or correct the human’s action, rather than just producing a motor response to the human request. The dimension of social coordination is thus added to that of motor precision (see Table 1 ).
Similarly, flexibility in HRI also requires “mixed initiative dialog” ( Mavridis, 2015 ), so that the robot can both initiate and respond to the interaction. Integrating models based on human adaptation and probabilistic decision processes, Nikolaidis et al. (2017) have indeed shown that the performance of human–robot teams in collaborative tasks is improved when the robot guides the human toward an effective strategy, compared to the common approach of having the robot strictly adapting to the human. The human’s trust in the robot was also facilitated by a greater symmetry in role distribution and adaptation between the robot and the human, which might in turn lead to greater acceptability of HRI.
Designing such “socially intelligent and cooperative robots” ( Breazeal et al., 2004 ) requires specific temporal dynamics of the interaction, which represents a considerable challenge especially at a computational level. These dynamics convey social meanings to such an extent that any delay in the interaction can sometimes question its effectiveness. Researchers here face a dilemma that seem to bring into opposition interaction complexity (which requires to take account of numerous parameters) and interaction timing. The implementation of fast timescales (on the order of 100 ms) is usually considered necessary for robots to integrate (i.e., detect, interpret, and predict) and react to social stimuli in a timely manner through interactions ( Durantin et al., 2017 ). Researchers developing a storytelling robot interacting with children aged 4–5 years have confirmed the importance of temporal features in the pragmatics of interactions. Contingent responses from the robot, in relation to the attentional and social cues signaled by the children, were indeed found to facilitate engagement of the latter ( Heath et al., 2017 ).
The variation in some characteristics of the robot’s behaviors according to the action performed may also illustrate further the question of pragmatics in HRI, moving us one step closer toward human-like interactions. For example, the morphological differences that have been reported in young children between pointing and reaching ( Cochet et al., 2014 ) could be applied to the robot. First, regarding body posture, we might expect robots to lean closer to a given object when they intend to grasp it than when they want to communicate about that object. Second, depending on the robot technical possibilities (e.g., two- or three-finger grippers, biomimetic anthropomorphic hands), differences in the form of manual gestures produced should be observed between imperative and declarative pointing. The former is typically characterized by whole-hand gestures (all the fingers are extended in the direction of the referent), while the latter is mostly associated with index-finger gestures (the index finger is extended toward the referent and the other fingers are curled inside the hand) ( Cochet and Vauclair, 2010 ; Liszkowski and Tomasello, 2011 ). Hand shape is also influenced by precision constraints: imperative gestures are likely to shift from whole-hand pointing to index-finger pointing when the target is surrounded by distractors ( Cochet et al., 2014 ), which can be the case when the robot has to identify a specific object among several (e.g., the human can ask the robot to give him/her the red cube). Here, the notion of iconicity, which plays a role in both oral and sign languages, may help researchers to precisely analyze the structure of gestures and better understand the interface between gestures and signs ( Guidetti and Morgenstern, 2017 ). The importance of motor precision is here directly related to the dimensions of coordination and anticipatory planning, therefore providing a comprehensive framework to assess the complexity and effectiveness of HRI.
Moreover, the importance of implementing responsive social gaze in robots has previously been highlighted (e.g., Yoshikawa et al., 2006 ), but this response might also vary depending on the communicative function involved. To mirror child development, gaze alternation between the partner and the referent should indeed be more frequent in declarative situations than in imperative ones ( Cochet and Vauclair, 2010 ). The coordination between gestures and gaze (see also section “How Does Communication Develop in the Context of Social Play?”) is also an important factor, which can help the robot to estimate the state of goals, plans, and actions from human point of view, and allow the human to feel that he/she is involved in fluid interactions with the robot, both facilitating the emergence of joint outcomes. If a robot alternates its gaze between an object and its partner before initiating a pointing gesture, the human may for example interpret this behavior as the robot’s willingness to take into account his/her attentional state before gesturing, thus favoring the exchange of information. Broadly speaking, coordinated gaze behavior could be considered as the most fundamental modality for effective HRI, or at least as a key prerequisite in collaborative tasks.
The consideration of facial expressions may also facilitate turn-taking dynamics and limit miscommunication, by allowing some inferences about the other’s affective state. Integrating the emotional component into HRI gives each partner additional cues to decide what is the most appropriate response in a given situation. The development of methods for facial expression analysis raises several issues though (e.g., Kanade et al., 2000 ). Even if there have been some attempts to design facial expression mechanism in humanoid robots (e.g., Hashimoto et al., 2006 ; Gao et al., 2010 ), most of current robots’ facial features are still far from the extremely rich motor possibilities of the human face. In parallel, the development of real time coding of emotional expressions seems to be an achievable goal ( Bartlett et al., 2003 ), allowing robots to directly perceive some changes in the human facial expressions.
In addition to visual information, the auditory modality can also play a role in influencing robots’ and humans’ decisions and coordination processes. In children at around 2 years of age, vocalizations accompany more frequently declarative gestures than imperative ones ( Cochet and Vauclair, 2010 ). More recently, the prosody of these vocalizations was shown to gradually match the function of pointing during the second year of life ( Tiziana et al., 2017 ), allowing to differentiate imperative from declarative gestures ( Grünloh and Liszkowski, 2015 ). Other features such as the positioning of the object and the attentional state of the partner have also been suggested to influence the rising and falling tones in the vocal productions simultaneous to gestures ( Leroy et al., 2009 ). Prosody can therefore serve pragmatic purposes, and changes in pitch, intensity, or duration of speech or vocalizations can in this regard be considered as a full-fledged component of multimodal communication.
Beyond prosody, language content may be the most effective way for human–robot teams to coordinate. However, the design of robots with language comprehension and production abilities that could lead to fluid conversations with humans raises several issues. Verbal language requires indeed symbolic representations, which need to be connected not only to the robot’s sensory system, but also to “mental models” of the world internalized within its cognitive system. Mavridis (2015) has highlighted here the question of “situated language and symbol grounding.” For example, the relation between the verbal label “cube” uttered by the human and the physical cube that it refers to in front of the robot can be mediated through sensory data, but the use of conventional signs should allow the robots to go beyond the here-and-now and extend symbol grounding to abstract entities in addition to objects, people, or events. To implement architecture that can be compared to human interactions, this relation should be bidirectional: the visual perception of a cube should activate the right symbol in the robot’s cognitive system, leading to the production of the word “cube”; reciprocally, a request addressed to the robot to give the human the cube should create a precise representation, allowing the robot to identify the right object.
Moreover, the identification of emotion labels in the verbal modality could also contribute, in addition to the recognition of emotional facial expressions and acoustic properties of speech (see Breazeal, 2004 for a complete review on emotion systems in robots), to a better coordination between each partner of the interaction. The haptic modality, playing an important role in social interactions, is also regarded as a valuable medium for expressing emotion ( Yohanan and MacLean, 2012 ). By developing motion capturing system and tactile sensors, the robot may use its human partner’s positions and such “affective touch” to estimate human intentions ( Miyashita et al., 2005 ). This modality, essential in human development, may be a particularly good candidate to study complexity of HRI, involving simultaneously motor precision, coordination and planning (see section “To What Extent Can Interactions Be Characterized as complex ?”).
Finally, in addition to the coordination dimension, the verbal dialog between a robot and a human would ideally imply purposeful speech and planning ( Mavridis, 2015 ), in order to avoid fixed mapping between stimuli and responses. Anticipatory planning abilities, as described in Section “To What Extent Can Interactions Be Characterized as complex ?”, would enable the robot to make the most appropriate or efficient decisions in a given shared activity, in conjunction with its perspective-taking skills and the goal of the activity. If the robot can represent which information are needed by the human to perform a specific action (and therefore identify which information the human misses), it can decide to express a verbal request or comment on the situation, and/or plan a sequence of actions to coordinate with its partner.
This last example raises the question of intrinsic motivation in interactions: why is each partner engaged in this multimodal coordination, and to what extent does it influence the characteristics of the interaction? Studies in developmental robotics have shown that intrinsic motivation systems based on curiosity can directly impact learning skills and lead to autonomous mental development in robots ( Oudeyer et al., 2007 ). Such mechanism is obviously involved in human development and in social play in particular: children discover and create new possibilities by exploring their physical and social environment. Through the development of social referencing, self-consciousness or cooperation, human social interactions may even sometimes constitute a motivated goal per se ( Tomasello, 2009 ), which provides some perspectives to shape robots’ intrinsic motivation with a “social reward” function.
We can see here that the relationships between theories in developmental psychology and robotics offer bidirectional benefits. To put it in a nutshell, some models in developmental robotics are based on psychological theories, which are then formalized and implemented in robots, while developmental robotics allows researchers in psychology to go further in the elaboration of their theories through thorough experimentations and hypothesis testing. This applies to a variety of questions addressed in this review, from the conditions that influence learning process during interactions ( Boucenna et al., 2014 ) to the description of stages in language development ( Morse and Cangelosi, 2017 ). Advances in developmental robotics may thus provide previous help in the analysis and implementation of the processes involved in interactions.
Conclusion and Perspectives
The question at stake in the present work was to improve the effectiveness of human–robot interactions in collaborative tasks, first in terms of joint outcomes – has the task been completed? – but also with regard to the human’s perception and interpretation of the interaction. Is the robot’s behavior appropriate, i.e., acceptable, considering the frame of human communication? We argue here that the observation of the development and the structure of interactions between the child and the adult, especially in the context of social play, can help answer this question. To shape a shared common space between the human and the robot that could reflect the complexity of human interactions, we have also proposed to focus on three dimensions: motor precision, coordination, and anticipatory planning. The specific examples developed in Section “Pragmatics in HRI: Which Ingredients Are Necessary for Effective Interactions?” suggest that the more robots use human-like communicative modalities (e.g., facial expressions, gestures, and language) in respect to these three dimensions, the more they invite interactive behaviors that are natural to people. The interpretation of dealing with a social agent is strengthened, which facilitates in turn the interaction with robots. In this sense, and to paraphrase Cangelosi et al. (2010) , the integration of action and language may constitute a roadmap to better frame and assess HRI from a developmental point of view and with a pragmatic perspective.
However, there are still numerous obstacles before achieving the level of details pictured in the present article, involving mainly technological challenges, given the motor and cognitive correlates of the above-mentioned behaviors. To put it bluntly, developmental psychologists cannot expect roboticists to implement in robots all the subtleties of multimodal communication that occur in human children. There may also be some conceptual difficulties as the attempts to approach human realism, aiming at maintaining the human’s trust in the robot, can sometimes be confronted with an uneasy feeling of viewing and/or hearing a robot that looks imperfectly human. This uncanny valley effect ( Mitchell et al., 2011 ; Mori, 1970 , 2012 ), which was shown to emerge in middle childhood in relation to developing expectations about humans and machines ( Brink et al., 2017 ), may complicate the design of socially interactive robots, both in terms of appearance and behavior. Empirical evidence for the uncanny valley seems nevertheless inconsistent or restricted to specific conditions ( Kätsyri et al., 2015 ), with the definition of human-likeness mostly involving physical realism.
By contrast, anthropomorphic behavior (see Duffy, 2003 ), in addition to its facilitating role in the interaction with humans (see above), also results in better and faster learning by the robots. For example, in a task in which they have to learn the meaning of words, the robots’ performances are enhanced when they provide humans with social cues to communicate a learning preference, as these cues influence the tutoring of the human teacher ( de Greeff and Belpaeme, 2015 ). We observe the same phenomena when human children start to learn new concepts: according to Bruner’s constructivist theory, children need scaffolding from adults (or from children who have already acquired the concept) in the form of active support, which may represent at first a reduction in the choices a child might face. Such learning processes play obviously an important role in human development, and may also enable quick and effective application of robotic systems. Multi-level learning may indeed constitute a key line of research for HRI ( Mavridis, 2015 ), which might again benefit from research in developmental psychology.
Reciprocally, the field of robotics provides interesting perspectives for psychologists, especially for research on atypical development. Atypical development might be a direct window on typical development and vice versa: “development is the key to understanding developmental disorders” ( Karmiloff-Smith, 1998 ). Joint action and joint attention are for example usually impaired in children with ASD; the comparison with typical development has revealed different use of social gaze and often a lack of the declarative function, both for verbal and non-verbal communication. The exchanges between robotics and developmental psychology could help conceptualize the stages of joint attention in order to better understand how children develop joint attention and get through the whole sequence of declarative pointing. This will have an impact on elaborating intervention programs for children with neurodevelopmental disorders. Moreover, numerous intervention programs have recently been proposed showing the added value of therapy robot for the development of communication, play, or emotional skills (e.g., Robins et al., 2009 ; Huijnen et al., 2016 ).
In conclusion, the combination of insights and methods in robotics and developmental psychology allows researchers to conceive models of HRI in which the robots can come to develop motor, social, and cognitive skills. These models may benefit fundamental research on joint attention and joint action in typical development, but also early evaluation and intervention programs for atypical development (e.g., Dautenhahn, 2007 ). The continuation of these interdisciplinary discussions, which may possibly integrate some of the elements proposed in the present article, will undoubtedly lead to more and more solid HRI models in the next decades.
HC and MG devised the conceptual ideas presented in the article. HC drafted the manuscript. MG revised it critically and gave final approval of the version to be submitted.
This article is part of the project JointAction4HRI, funded by the French National Agency for Research (n°16-CE33-0017).
Conflict of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Many ideas presented in this paper stem from fruitful discussions with R. Alami, A. Clodic, and E. Pacherie, all involved in the Joint Action for Human-Robot Interaction project funded by French National Agency for Research (Project No. 16-CE33-0017-01).
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Keywords : human–robot interaction, human development, joint attention, joint action, coordination, complexity, gestures
Citation: Cochet H and Guidetti M (2018) Contribution of Developmental Psychology to the Study of Social Interactions: Some Factors in Play, Joint Attention and Joint Action and Implications for Robotics. Front. Psychol. 9:1992. doi: 10.3389/fpsyg.2018.01992
Received: 13 October 2017; Accepted: 28 September 2018; Published: 19 October 2018.
Copyright © 2018 Cochet and Guidetti. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hélène Cochet, [email protected]
This article is part of the Research Topic
Modeling Play in Early Infant Development
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Research Methods in Developmental Psychology
University of Calfornia, Irvine
What do infants know about the world in which they live – and how do they grow and change with age? These are the kinds of questions answered by developmental scientists. This module describes different research techniques that are used to study psychological phenomena in infants and children, research designs that are used to examine age-related changes in development, and unique challenges and special issues associated with conducting research with infants and children. Child development is a fascinating field of study, and many interesting questions remain to be examined by future generations of developmental scientists – maybe you will be among them!
- Child development
- Developmental psychology
- Infant development
- Research designs
- Research methods
- Learning Objectives
- Describe different research methods used to study infant and child development
- Discuss different research designs, as well as their strengths and limitations
- Report on the unique challenges associated with conducting developmental research
A group of children were playing hide-and-seek in the yard. Pilar raced to her hiding spot as her six-year-old cousin, Lucas, loudly counted, “… six, seven, eight, nine, ten! Ready or not, here I come!”. Pilar let out a small giggle as Lucas ran over to find her – in the exact location where he had found his sister a short time before. At first glance, this behavior is puzzling: why would Pilar hide in exactly the same location where someone else was just found? Whereas older children and adults realize that it is likely best to hide in locations that have not been searched previously, young children do not have the same cognitive sophistication. But why not… and when do these abilities first develop?
Developmental psychologists investigate questions like these using research methods that are tailored to the particular capabilities of the infants and children being studied. Importantly, research in developmental psychology is more than simply examining how children behave during games of hide-and-seek – the results obtained from developmental research have been used to inform best practices in parenting, education, and policy.
This module describes different research techniques that are used to study psychological phenomena in infants and children, research designs that are used to examine age-related changes in developmental processes and changes over time, and unique challenges and special issues associated with conducting research with infants and children.
Infants and children—especially younger children—cannot be studied using the same research methods used in studies with adults. Researchers, therefore, have developed many creative ways to collect information about infant and child development. In this section, we highlight some of the methods that have been used by researchers who study infants and older children, separating them into three distinct categories: involuntary or obligatory responses , voluntary responses , and psychophysiological responses . We will also discuss other methods such as the use of surveys and questionnaires. At the end of this section, we give an example of how interview techniques can be used to study the beliefs and perceptions of older children and adults – a method that cannot be used with infants or very young children.
Involuntary or obligatory responses
One of the primary challenges in studying very young infants is that they have limited motor control – they cannot hold their heads up for short amounts of time, much less grab an interesting toy, play the piano, or turn a door knob. As a result, infants cannot actively engage with the environment in the same way as older children and adults. For this reason, developmental scientists have designed research methods that assess involuntary or obligatory responses. These are behaviors in which people engage without much conscious thought or effort. For example, think about the last time you heard your name at a party – you likely turned your head to see who was talking without even thinking about it. Infants and young children also demonstrate involuntary responses to stimuli in the environment. When infants hear the voice of their mother, for instance, their heart rate increases – whereas if they hear the voice of a stranger, their heart rate decreases (Kisilevsky et al., 2003). Researchers study involuntary behaviors to better understand what infants know about the world around them.
One research method that capitalizes on involuntary or obligatory responses is a procedure known as habituation . In habituation studies, infants are presented with a stimulus such as a photograph of a face over and over again until they become bored with it. When infants become bored, they look away from the picture. If infants are then shown a new picture--such as a photograph of a different face-- their interest returns and they look at the new picture. This is a phenomenon known as dishabituation . Habituation procedures work because infants generally look longer at novel stimuli relative to items that are familiar to them. This research technique takes advantage of involuntary or obligatory responses because infants are constantly looking around and observing their environments; they do not have to be taught to engage with the world in this way.
One classic habituation study was conducted by Baillargeon and colleagues ( 1985 ). These researchers were interested in the concept of object permanence , or the understanding that objects exist even when they cannot be seen or heard. For example, you know your toothbrush exists even though you are probably not able to see it right this second. To investigate object permanence in 5-month-old infants, the researchers used a violation of expectation paradigm . The researchers first habituated infants to an opaque screen that moved back and forth like a drawbridge (using the same procedure you just learned about in the previous paragraph). Once the infants were bored with the moving screen, they were shown two different scenarios to test their understanding of physical events. In both of these test scenarios, an opaque box was placed behind the moving screen. What differed between these two scenarios, however, was whether they confirmed or violated the solidity principle – the idea that two solid objects cannot occupy the same space at the same time. In the possible scenario, infants watched as the moving drawbridge stopped when it hit the opaque box (as would be expected based on the solidity principle). In the impossible scenario, the drawbridge appeared to move right through the space that was occupied by the opaque box! This impossible scenario violates the solidity principle in the same way as if you got out of your chair and walked through a wall, reappearing on the other side.
The results of this study revealed that infants looked longer at the impossible test event than at the possible test event. The authors suggested that the infants reacted in this way because they were surprised – the demonstration went against their expectation that two solids cannot move through one another. The findings indicated that 5-month-old infants understood that the box continued to exist even when they could not see it. Subsequent studies indicated that 3½- and 4½-month-old infants also demonstrate object permanence under similar test conditions ( Baillargeon, 1987 ). These findings are notable because they suggest that infants understand object permanence much earlier than had been reported previously in research examining voluntary responses (although see more recent research by Cashon & Cohen, 2000 ).
As infants and children age, researchers are increasingly able to study their understanding of the world through their voluntary responses. Voluntary responses are behaviors that a person completes by choice. For example, think about how you act when you go to the grocery store: you select whether to use a shopping cart or a basket, you decide which sections of the store to walk through, and you choose whether to stick to your grocery list or splurge on a treat. Importantly, these behaviors are completely up to you (and are under your control). Although they do not do a lot of grocery shopping, infants and children also have voluntary control over their actions. Children, for instance, choose which toys to play with.
Researchers study the voluntary responses of infants and young children in many ways. For example, developmental scientists study recall memory in infants and young children by looking at voluntary responses. Recall memory is memory of past events or episodes, such as what you did yesterday afternoon or on your last birthday. Whereas older children and adults are simply asked to talk about their past experiences, recall memory has to be studied in a different way in infants and very young children who cannot discuss the past using language. To study memory in these subjects researchers use a behavioral method known as elicited imitation ( Lukowski & Milojevich, in press ).
In the elicited imitation procedure, infants play with toys that are designed in the lab to be unlike the kinds of things infants usually have at home. These toys (or event sequences, as researchers call them) can be put together in a certain way to produce an outcome that infants commonly enjoy. One of these events is called Find the Surprise. As shown in Figure 1, this toy has a door on the front that is held in place by a latch – and a small plastic figure is hidden on the inside. During the first part of the study, infants play with the toy in whichever way they want for a few minutes. The researcher then shows the infant how make the toy work by (1) flipping the latch out of the way and (2) opening the door, revealing the plastic toy inside. The infant is allowed to play with the toy again either immediately after the demonstration or after a longer delay. As the infant plays, the researcher records whether the infant finds the surprise using the same procedure that was demonstrated.
Use of the elicited imitation procedure has taught developmental scientists a lot about how recall memory develops. For example, we now know that 6-month-old infants remember one step of a 3-step sequence for 24 hours ( Barr, Dowden, & Hayne, 1996 ; Collie & Hayne, 1999 ). Nine-month-olds remember the individual steps that make up a 2-step event sequence for 1 month, but only 50% of infants remember to do the first step of the sequence before the second ( Bauer, Wiebe, Carver, Waters, & Nelson, 2003 ; Bauer, Wiebe, Waters, & Bangston, 2001 ; Carver & Bauer, 1999 ). When children are 20 months old, they remember the individual steps and temporal order of 4-step events for at least 12 months – the longest delay that has been tested to date ( Bauer, Wenner, Dropik, & Wewerka, 2000 ).
Behavioral studies have taught us important information about what infants and children know about the world. Research on behavior alone, however, cannot tell scientists how brain development or biological changes impact (or are impacted by) behavior. For this reason, researchers may also record psychophysiological data, such as measures of heart rate, hormone levels, or brain activity. These measures may be recorded by themselves or in combination with behavioral data to better understand the bidirectional relations between biology and behavior.
One manner of understanding associations between brain development and behavioral advances is through the recording of event-related potentials , or ERPs. ERPs are recorded by fitting a research participant with a stretchy cap that contains many small sensors or electrodes. These electrodes record tiny electrical currents on the scalp of the participant in response to the presentation of particular stimuli, such as a picture or a sound (for additional information on recording ERPs from infants and children, see DeBoer, Scott, & Nelson, 2005 ). The recorded responses are then amplified thousands of times using specialized equipment so that they look like squiggly lines with peaks and valleys. Some of these brain responses have been linked to psychological phenomena. For example, researchers have identified a negative peak in the recorded waveform that they have called the N170 ( Bentin, Allison, Puce, Perez, & McCarthy, 2010 ). The peak is named in this way because it is negative (hence the N) and because it occurs about 140ms to 170ms after a stimulus is presented (hence the 170). This peak is particularly sensitive to the presentation of faces, as it is commonly more negative when participants are presented with photographs of faces rather than with photographs of objects. In this way, researchers are able to identify brain activity associated with real world thinking and behavior.
The use of ERPs has provided important insight as to how infants and children understand the world around them. In one study ( Webb, Dawson, Bernier, & Panagiotides, 2006 ), researchers examined face and object processing in children with autism spectrum disorders, those with developmental delays, and those who were typically developing. The children wore electrode caps and had their brain activity recorded as they watched still photographs of faces (of their mother or of a stranger) and objects (including those that were familiar or unfamiliar to them). The researchers examined differences in face and object processing by group by observing a component of the brainwave they called the prN170 (because it was believed to be a precursor to the adult N170). Their results showed that the height of the prN170 peak (commonly called the amplitude ) did not differ when faces or objects were presented to typically developing children. When considering children with autism, however, the peaks were higher when objects were presented relative to when faces were shown. Differences were also found in how long it took the brain to reach the negative peak (commonly called the latency of the response). Whereas the peak was reached more quickly when typically developing children were presented with faces relative to objects, the opposite was true for children with autism. These findings suggest that children with autism are in some way processing faces differently than typically developing children (and, as reported in the manuscript, children with more general developmental delays).
Developmental science has come a long way in assessing various aspects of infant and child development through behavior and psychophysiology – and new advances are happening every day. In many ways, however, the very youngest of research participants are still quite limited in the information they can provide about their own development. As such, researchers often ask the people who know infants and children best – commonly, their parents or guardians – to complete surveys or questionnaires about various aspects of their lives. These parent-report data can be analyzed by themselves or in combination with any collected behavioral or psychophysiological data.
One commonly used parent-report questionnaire is the Child Behavior Checklist (CBCL; Achenbach & Rescorla, 2000 ). Parents complete the preschooler version of this questionnaire by answering questions about child strengths, behavior problems, and disabilities, among other things. The responses provided by parents are used to identify whether the child has any behavioral issues, such as sleep difficulties, aggressive behaviors, depression, or attention deficit/hyperactivity problems.
A recent study used the CBCL-Preschool questionnaire ( Achenbach & Rescorla, 2000 ) to examine preschooler functioning in relation to levels of stress experienced by their mothers while they were pregnant ( Ronald, Pennell, & Whitehouse, 2011 ). Almost 3,000 pregnant women were recruited into the study during their pregnancy and were interviewed about their stressful life experiences. Later, when their children were 2 years old, mothers completed the CBCL-Preschool questionnaire. The results of the study showed that higher levels of maternal stress during pregnancy (such as a divorce or moving to a new house) were associated with increased attention deficit/hyperactivity problems in children over 2 years later. These findings suggest that stressful events experienced during prenatal development may be associated with problematic child behavioral functioning years later – although additional research is needed.
Whereas infants and very young children are unable to talk about their own thoughts and behaviors, older children and adults are commonly asked to use language to discuss their thoughts and knowledge about the world. In fact, these verbal report paradigms are among the most widely used in psychological research. For instance, a researcher might present a child with a vignette or short story describing a moral dilemma, and the child would be asked to give their own thoughts and beliefs ( Walrath, 2011 ). For example, children might react to the following:
“Mr. Kohut’s wife is sick and only one medication can save her life. The medicine is extremely expensive and Mr. Kohut cannot afford it. The druggist will not lower the price. What should Mr. Kohut do, and why?”
Children can provide written or verbal answers to these types of scenarios. They can also offer their perspectives on issues ranging from attitudes towards drug use to the experience of fear while falling asleep to their memories of getting lost in public places – the possibilities are endless. Verbal reports such as interviews and surveys allow children to describe their own experience of the world.
Now you know about some tools used to conduct research with infants and young children. Remember, research methods are the tools that are used to collect information. But it is easy to confuse research methods and research design . Research design is the strategy or blueprint for deciding how to collect and analyze information. Research design dictates which methods are used and how.
Researchers typically focus on two distinct types of comparisons when conducting research with infants and children. The first kind of comparison examines change within individuals . As the name suggests, this type of analysis measures the ways in which a specific person changes (or remains the same) over time. For example, a developmental scientist might be interested in studying the same group of infants at 12 months, 18 months, and 24 months to examine how vocabulary and grammar change over time. This kind of question would be best answered using a longitudinal research design. Another sort of comparison focuses on changes between groups . In this type of analysis, researchers study average changes in behavior between groups of different ages. Returning to the language example, a scientist might study the vocabulary and grammar used by 12-month-olds, 18-month-olds, and 24-month-olds to examine how language abilities change with age. This kind of question would be best answered using a cross-sectional research design.
Longitudinal research designs
Longitudinal research designs are used to examine behavior in the same infants and children over time. For example, when considering our example of hide-and-seek behaviors in preschoolers, a researcher might conduct a longitudinal study to examine whether 2-year-olds develop into better hiders over time. To this end, a researcher might observe a group of 2-year-old children playing hide-and-seek with plans to observe them again when they are 4 years old – and again when they are 6 years old. This study is longitudinal in nature because the researcher plans to study the same children as they age. Based on her data, the researcher might conclude that 2-year-olds develop more mature hiding abilities with age. Remember, researchers examine games such as hide-and-seek not because they are interested in the games themselves, but because they offer clues to how children think, feel and behave at various ages.
Longitudinal studies may be conducted over the short term (over a span of months, as in Wiebe, Lukowski, & Bauer, 2010 ) or over much longer durations (years or decades, as in Lukowski et al., 2010) . For these reasons, longitudinal research designs are optimal for studying stability and change over time. Longitudinal research also has limitations, however. For one, longitudinal studies are expensive: they require that researchers maintain continued contact with participants over time, and they necessitate that scientists have funding to conduct their work over extended durations (from infancy to when participants were 19 years old in Lukowski et al., 2010 ). An additional risk is attrition . Attrition occurs when participants fail to complete all portions of a study. Participants may move, change their phone numbers, or simply become disinterested in participating over time. Researchers should account for the possibility of attrition by enrolling a larger sample into their study initially, as some participants will likely drop out over time.
The results from longitudinal studies may also be impacted by repeated assessments. Consider how well you would do on a math test if you were given the exact same exam every day for a week. Your performance would likely improve over time not necessarily because you developed better math abilities, but because you were continuously practicing the same math problems. This phenomenon is known as a practice effect . Practice effects occur when participants become better at a task over time because they have done it again and again; not due to natural psychological development. A final limitation of longitudinal research is that the results may be impacted by cohort effects . Cohort effects occur when the results of the study are affected by the particular point in historical time during which participants are tested. As an example, think about how peer relationships in childhood have likely changed since February 2004 – the month and year Facebook was founded. Cohort effects can be problematic in longitudinal research because only one group of participants are tested at one point in time – different findings might be expected if participants of the same ages were tested at different points in historical time.
Cross-sectional research designs are used to examine behavior in participants of different ages who are tested at the same point in time. When considering our example of hide-and-seek behaviors in children, for example, a researcher might want to examine whether older children more often hide in novel locations (those in which another child in the same game has never hidden before) when compared to younger children. In this case, the researcher might observe 2-, 4-, and 6-year-old children as they play the game (the various age groups represent the “cross sections”). This research is cross-sectional in nature because the researcher plans to examine the behavior of children of different ages within the same study at the same time. Based on her data, the researcher might conclude that 2-year-olds more commonly hide in previously-searched locations relative to 6-year-olds.
Cross-sectional designs are useful for many reasons. Because participants of different ages are tested at the same point in time, data collection can proceed at a rapid pace. In addition, because participants are only tested at one point in time, practice effects are not an issue – children do not have the opportunity to become better at the task over time. Cross-sectional designs are also more cost-effective than longitudinal research designs because there is no need to maintain contact with and follow-up on participants over time.
One of the primary limitations of cross-sectional research, however, is that the results yield information on age-related change, not development per se . That is, although the study described above can show that 6-year-olds are more advanced in their hiding behavior than 2-year-olds, the data used to come up with this conclusion were collected from different children. It could be, for instance, that this specific sample of 6-year-olds just happened to be particularly clever at hide-and-seek. As such, the researcher cannot conclude that 2-year-olds develop into better hiders with age; she can only state that 6-year-olds, on average, are more sophisticated hiders relative to children 4 years younger.
Sequential research designs
Sequential research designs include elements of both longitudinal and cross-sectional research designs. Similar to longitudinal designs, sequential research features participants who are followed over time; similar to cross-sectional designs, sequential work includes participants of different ages. This research design is also distinct from those that have been discussed previously in that children of different ages are enrolled into a study at various points in time to examine age-related changes, development within the same individuals as they age, and account for the possibility of cohort effects.
Consider, once again, our example of hide-and-seek behaviors. In a study with a sequential design, a researcher might enroll three separate groups of children (Groups A, B, and C). Children in Group A would be enrolled when they are 2 years old and would be tested again when they are 4 and 6 years old (similar in design to the longitudinal study described previously). Children in Group B would be enrolled when they are 4 years old and would be tested again when they are 6 and 8 years old. Finally, children in Group C would be enrolled when they are 6 years old and would be tested again when they are 8 and 10 years old.
Studies with sequential designs are powerful because they allow for both longitudinal and cross-sectional comparisons. This research design also allows for the examination of cohort effects. For example, the researcher could examine the hide-and-seek behavior of 6-year-olds in Groups A, B, and C to determine whether performance differed by group when participants were the same age. If performance differences were found, there would be evidence for a cohort effect. In the hide-and-seek example, this might mean that children from different time periods varied in the amount they giggled or how patient they are when waiting to be found. Sequential designs are also appealing because they allow researchers to learn a lot about development in a relatively short amount of time. In the previous example, a four-year research study would provide information about 8 years of developmental time by enrolling children ranging in age from two to ten years old.
Because they include elements of longitudinal and cross-sectional designs, sequential research has many of the same strengths and limitations as these other approaches. For example, sequential work may require less time and effort than longitudinal research, but more time and effort than cross-sectional research. Although practice effects may be an issue if participants are asked to complete the same tasks or assessments over time, attrition may be less problematic than what is commonly experienced in longitudinal research since participants may not have to remain involved in the study for such a long period of time.
When considering the best research design to use in their research, scientists think about their main research question and the best way to come up with an answer. A table of advantages and disadvantages for each of the described research designs is provided here to help you as you consider what sorts of studies would be best conducted using each of these different approaches.
Challenges Associated with Conducting Developmental Research
The previous sections describe research tools to assess development in infancy and early childhood, as well as the ways that research designs can be used to track age-related changes and development over time. Before you begin conducting developmental research, however, you must also be aware that testing infants and children comes with its own unique set of challenges. In the final section of this module, we review some of the main issues that are encountered when conducting research with the youngest of human participants. In particular, we focus our discussion on ethical concerns, recruitment issues, and participant attrition.
As a student of psychological science, you may already know that Institutional Review Boards (IRBs) review and approve of all research projects that are conducted at universities, hospitals, and other institutions. An IRB is typically a panel of experts who read and evaluate proposals for research. IRB members want to ensure that the proposed research will be carried out ethically and that the potential benefits of the research outweigh the risks and harm for participants. What you may not know though, is that the IRB considers some groups of participants to be more vulnerable or at-risk than others. Whereas university students are generally not viewed as vulnerable or at-risk, infants and young children commonly fall into this category. What makes infants and young children more vulnerable during research than young adults? One reason infants and young children are perceived as being at increased risk is due to their limited cognitive capabilities, which makes them unable to state their willingness to participate in research or tell researchers when they would like to drop out of a study. For these reasons, infants and young children require special accommodations as they participate in the research process.
When thinking about special accommodations in developmental research, consider the informed consent process. If you have ever participated in psychological research, you may know through your own experience that adults commonly sign an informed consent statement (a contract stating that they agree to participate in research) after learning about a study. As part of this process, participants are informed of the procedures to be used in the research, along with any expected risks or benefits. Infants and young children cannot verbally indicate their willingness to participate, much less understand the balance of potential risks and benefits. As such, researchers are oftentimes required to obtain written informed consent from the parent or legal guardian of the child participant, an adult who is almost always present as the study is conducted. In fact, children are not asked to indicate whether they would like to be involved in a study at all (a process known as assent ) until they are approximately seven years old. Because infants and young children also cannot easily indicate if they would like to discontinue their participation in a study, researchers must be sensitive to changes in the state of the participant (determining whether a child is too tired or upset to continue) as well as to parent desires (in some cases, parents might want to discontinue their involvement in the research). As in adult studies, researchers must always strive to protect the rights and well-being of the minor participants and their parents when conducting developmental science.
An additional challenge in developmental science is participant recruitment. Recruiting university students to participate in adult studies is typically easy. Many colleges and universities offer extra credit for participation in research and have locations such as bulletin boards and school newspapers where research can be advertised. Unfortunately, young children cannot be recruited by making announcements in Introduction to Psychology courses, by posting ads on campuses, or through online platforms such as Amazon Mechanical Turk . Given these limitations, how do researchers go about finding infants and young children to be in their studies?
The answer to this question varies along multiple dimensions. Researchers must consider the number of participants they need and the financial resources available to them, among other things. Location may also be an important consideration. Researchers who need large numbers of infants and children may attempt to do so by obtaining infant birth records from the state, county, or province in which they reside. Some areas make this information publicly available for free, whereas birth records must be purchased in other areas (and in some locations birth records may be entirely unavailable as a recruitment tool). If birth records are available, researchers can use the obtained information to call families by phone or mail them letters describing possible research opportunities. All is not lost if this recruitment strategy is unavailable, however. Researchers can choose to pay a recruitment agency to contact and recruit families for them. Although these methods tend to be quick and effective, they can also be quite expensive. More economical recruitment options include posting advertisements and fliers in locations frequented by families, such as mommy-and-me classes, local malls, and preschools or day care centers. Researchers can also utilize online social media outlets like Facebook, which allows users to post recruitment advertisements for a small fee. Of course, each of these different recruitment techniques requires IRB approval.
Another important consideration when conducting research with infants and young children is attrition . Although attrition is quite common in longitudinal research in particular, it is also problematic in developmental science more generally, as studies with infants and young children tend to have higher attrition rates than studies with adults. For example, high attrition rates in ERP studies oftentimes result from the demands of the task: infants are required to sit still and have a tight, wet cap placed on their heads before watching still photographs on a computer screen in a dark, quiet room. In other cases, attrition may be due to motivation (or a lack thereof). Whereas adults may be motivated to participate in research in order to receive money or extra course credit, infants and young children are not as easily enticed. In addition, infants and young children are more likely to tire easily, become fussy, and lose interest in the study procedures than are adults. For these reasons, research studies should be designed to be as short as possible – it is likely better to break up a large study into multiple short sessions rather than cram all of the tasks into one long visit to the lab. Researchers should also allow time for breaks in their study protocols so that infants can rest or have snacks as needed. Happy, comfortable participants provide the best data.
Child development is a fascinating field of study – but care must be taken to ensure that researchers use appropriate methods to examine infant and child behavior, use the correct experimental design to answer their questions, and be aware of the special challenges that are part-and-parcel of developmental research. After reading this module, you should have a solid understanding of these various issues and be ready to think more critically about research questions that interest you. For example, when considering our initial example of hide-and-seek behaviors in preschoolers, you might ask questions about what other factors might contribute to hiding behaviors in children. Do children with older siblings hide in locations that were previously searched less often than children without siblings? What other abilities are associated with the development of hiding skills? Do children who use more sophisticated hiding strategies as preschoolers do better on other tests of cognitive functioning in high school? Many interesting questions remain to be examined by future generations of developmental scientists – maybe you will make one of the next big discoveries!
- Outside Resources
- Discussion Questions
- Why is it important to conduct research on infants and children?
- What are some possible benefits and limitations of the various research methods discussed in this module?
- Why is it important to examine cohort effects in developmental research?
- Think about additional challenges or unique issues that might be experienced by developmental scientists. How would they handle the challenges and issues you’ve addressed?
- Work with your peers to design a study to identify whether children who were good hiders as preschoolers are more cognitively advanced in high school. What research design would you use and why? What are the advantages and limitations of the design you selected?
- Achenbach, T. M., & Rescorla, L. A. (2000). Manual for the ASEBA preschool forms and profiles: An integrated system of multi-informant assessment. Burlington, VT: University of Vermont Department of Psychiatry.
- Baillargeon, R. (1987). Object permanence in 3½- and 4½-month-old infants. Developmental Psychology, 23, 655-664. doi: 10.1037/0012-1622.214.171.1245
- Baillargeon, R., Spelke, E., & Wasserman, S. (1985). Object permanence in five-month-old infants. Cognition, 20, 191-208. doi: 10.1016/0010-0277(85)90008-3
- Barr, R., Dowden, A., & Hayne, H. (1996). Developmental changes in deferred imitation by 6- to 24-month-old infants. Infant Behavior and Development, 19 , 159-170. doi: 10.1016/s0163-6383(96)90015-6
- Bauer, P. J., Wenner, J. A., Dropik, P. L., & Wewerka, S. S. (2000). Parameters of remembering and forgetting in the transition from infancy to early childhood. Monographs of the Society for Research in Child Development, 65 , 1-204. doi: 10.1016/j.imlet.2014.04.001
- Bauer, P. J., Wiebe, S. A., Carver, L. J., Waters, J. M., & Nelson, C. A. (2003). Developments in long-term explicit memory late in the first year of life: Behavioral and electrophysiological indices. Psychological Science, 14 , 629-635. doi: 10.1046/j.0956-7976.2003.psci_1476.x
- Bauer, P. J., Wiebe, S. A., Waters, J. M., & Bangston, S. K. (2001). Reexposure breeds recall: Effects of experience on 9-month-olds’ ordered recall. Journal of Experimental Child Psychology, 80 , 174-200. doi: 10.1006/jecp.2000.2628
- Bentin, S., Allison, T., Puce, A., Perez, E., & McCarthy, G. (2010). Electrophysiological studies of face perception in humans. Journal of Cognitive Neuroscience , 8, 551-565. doi: 10.1162/jocn.19126.96.36.1991
- Carver, L. J., & Bauer, P. J. (1999). When the event is more than the sum of its parts: 9-month-olds’ long-term ordered recall. Memory, 7 , 147-174. doi: 10.1080/741944070
- Cashon, C. H., & Cohen, L. B. (2000). Eight-month-old infants’ perception of possible and impossible events. Infancy, 1 , 429-446. doi: 10.1016/s0163-6383(98)91561-2
- Collie, R., & Hayne, H. (1999). Deferred imitation by 6- and 9-month-old infants: More evidence for declarative memory. Developmental Psychobiology, 35 , 83-90. doi: 10.1002/(sici)1098-2302(199909)35:2 3.0.co;2-s
- DeBoer, T., Scott, L. S., & Nelson, C. A. (2005). ERPs in developmental populations. In T. C. Handy (Ed.), Event-related potentials: A methods handbook (pp. 263-297) . Cambridge, MA: The MIT Press.
- Lukowski, A. F., & Milojevich, H. M. (2016). Examining recall memory in infancy and early childhood using the elicited imitation paradigm. Journal of Visualized Experiments, 110 , e53347.
- Lukowski, A. F., Koss, M., Burden, M. J., Jonides, J., Nelson, C. A., Kaciroti, N., … Lozoff, B. (2010). Iron deficiency in infancy and neurocognitive functioning at 19 years: Evidence of long-term deficits in executive function and recognition memory. Nutritional Neuroscience, 13 , 54-70. doi: 10.1179/147683010x12611460763689
- Ronald, A., Pennell, C. E., & Whitehouse, A. J. O. (2011). Prenatal maternal stress associated with ADHD and autistic traits in early childhood. Frontiers in Psychology, 1 , 1-8. doi: 10.3389/fpsyg.2010.00223
- Walrath, R. (2011). Kohlberg’s theory of moral development. In Encyclopedia of Child Behavior and Development (pp. 859–860).
- Webb, S. J., Dawson, G., Bernier, R., & Panagiotides, H. (2006). ERP evidence of atypical face processing in young children with autism. Journal of Autism and Developmental Disorders, 36 , 884-890. doi: 10.1007/s10803-006-0126-x
- Wiebe, S. A., Lukowski, A. F., & Bauer, P. J. (2010). Sequence imitation and reaching measures of executive control: A longitudinal examination in the second year of life. Developmental Neuropsychology, 35 , 522-538. doi: 10.1080/87565641.2010.494751
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Developmental Psychology Topics
Topics for research, papers, and other projects
Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."
Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.
- Childhood Topics
- Adolescence Topics
- Adulthood Topics
- How to Choose
- Tips for Students
Are you looking for a developmental psychology topic for a psychology paper , experiment, or science fair project? Topics you might pick can range from prenatal development to health during the final stages of life.
Developmental psychology is a broad topic that involves studying how people grow and change throughout their whole lifetime. Topics don't just include physical growth but also the emotional, cognitive, and social development that people experience at different stages of their lives.
At a Glance
The following are just a few different topics that might help inspire you. Remember, these are just ideas to help you get started. You might opt to explore one of these areas, or you might think of a related question that interests you as well.
Developmental Psychology Topics on Childhood
- Could packaging nutritious foods in visually appealing ways encourage children to make healthier food choices?
- Do children who listen to music while studying perform better or worse on exams?
- Do students who eat breakfast perform better in school than those who do not eat breakfast?
- Does birth order have an impact on procrastination ? Are first-borns less likely to procrastinate? Are last-borns more likely to put off tasks until the last minute?
- Does teaching infants sign language help or hinder the language acquisition process?
- How do parenting styles impact a child's level of physical activity? Are children raised by parents with permissive or uninvolved parents less active than those raised by parents with authoritative or authoritarian styles?
- How does bullying impact student achievement? Are bullied students more likely to have worse grades than their non-bullied peers?
- Which type of reinforcement works best for getting students to complete their homework: a tangible reward (such as a piece of candy) or social reinforcement (such as offering praise when homework is completed on time)?
Developmental Psychology Topics on Adolescence
- What factors tend to influence the onset of depression in teens and young adults?
- How do peer relationships influence identity formation during adolescence and young adulthood?
- What impact do parent-child relationships have in predicting substance use among teens and young adults?
- How does early substance use during adolescence impact impulsivity and risk-taking during early adulthood?
- How does technology use during adolescence influence social and emotional development?
- How does social media use influence body image among teens?
- What factors contribute to success during the transition from the teen years to early adulthood?
- How do cultural differences impact different aspects of adolescent development?
Developmental Psychology Topics on Adulthood
- Are older adults who rate high in self-efficacy more likely to have a better memory than those with low self-efficacy?
- Do the limits of short-term memory change as we age? How do the limits of short-term memory compare at ages, 15, 25, 45, and 65?
- Do mental games such as word searches, Sudoku, and word matching help elderly adults keep their cognitive skills sharp?
- How do explanations for the behavior of others change as we age? Are younger adults more likely to blame internal factors for events and older adults more likely to blame external variables?
Choosing Developmental Psychology Topics
Developmental psychology is a huge and diverse subject, so picking a topic isn't always easy. Some tips that can help you choose a good developmental psychology topic include:
- Focus on a specific topic : Make sure that your topic isn't too broad to avoid getting overwhelmed by the amount of information available
- Have a clear question or hypothesis : Your research question should be focused and clearly defined
- Do some background research : Spend some time reviewing the existing literature to get a better idea about what you want to cover with your topic
- Consider developmental theories : You might consider analyzing your topic through the lens of a particular theory of developmental psychology
- Check out recent research : Use research databases to find the most recently published research on your topic
Before you start working on any paper, experiment, or science project, the first thing you need to do is understand the rules your instructor has established for the assignment.
Also, be sure to check the official guidelines given by your teacher. If you are not sure about these guidelines, ask your instructor if there are any specific requirements before you get started on your research .
If you are going to actually conduct an experiment , you need to present your idea to your instructor to gain their permission before going forward. In some cases, you might have to also present your plan to your school's Institutional Review Board.
Tips for Researching Developmental Psychology Topics
After you have gotten to move forward with your chosen topic, the next step is to do some background research. This step is essential! If you are writing a paper, the information you find will make up your literature review.
If you are performing an experiment, it will provide background information for the introduction of your lab report . For a psychology science project, this research will help you in your presentation and can help you decide how to best approach your own experiment.
What This Means For You
Choosing a topic for a developmental psychology experiment, paper, or project can be tough! The ideas above can be a great place to start, but you might also consider questions you've had about your own life. Once you have a general idea for your topic, narrow it down, do some background research and talk to your instructor.
Nielsen M, Haun D. Why developmental psychology is incomplete without comparative and cross-cultural perspectives . Philos Trans R Soc Lond B Biol Sci . 2016;371(1686):20150071. doi:10.1098/rstb.2015.0071
Leite DFB, Padilha MAS, Cecatti JG. Approaching literature review for academic purposes: The Literature Review Checklist . Clinics (Sao Paulo) . 2019;74:e1403. Published 2019 Nov 25. doi:10.6061/clinics/2019/e1403
Grady C. Institutional review boards: Purpose and challenges . Chest . 2015;148(5):1148-1155. doi:10.1378/chest.15-0706
Kim WO. Institutional review board (IRB) and ethical issues in clinical research . Korean Journal of Anesthesiology . 2012;62(1):3-12. doi:10.4097/kjae.2012.62.1.3
By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."
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