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Human-Computer Interaction (HCI)

What is human-computer interaction (hci).

Human-computer interaction (HCI) is a multidisciplinary field of study focusing on the design of computer technology and, in particular, the interaction between humans (the users) and computers. While initially concerned with computers, HCI has since expanded to cover almost all forms of information technology design.

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Here, Professor Alan Dix explains the roots of HCI and which areas are particularly important to it.

The Meteoric Rise of HCI

HCI surfaced in the 1980s with the advent of personal computing, just as machines such as the Apple Macintosh, IBM PC 5150 and Commodore 64 started turning up in homes and offices in society-changing numbers. For the first time, sophisticated electronic systems were available to general consumers for uses such as word processors, games units and accounting aids. Consequently, as computers were no longer room-sized, expensive tools exclusively built for experts in specialized environments, the need to create human-computer interaction that was also easy and efficient for less experienced users became increasingly vital. From its origins, HCI would expand to incorporate multiple disciplines, such as computer science, cognitive science and human-factors engineering.

hci research work

HCI soon became the subject of intense academic investigation. Those who studied and worked in HCI saw it as a crucial instrument to popularize the idea that the interaction between a computer and the user should resemble a human-to-human, open-ended dialogue. Initially, HCI researchers focused on improving the usability of desktop computers (i.e., practitioners concentrated on how easy computers are to learn and use). However, with the rise of technologies such as the Internet and the smartphone, computer use would increasingly move away from the desktop to embrace the mobile world. Also, HCI has steadily encompassed more fields:

“…it no longer makes sense to regard HCI as a specialty of computer science; HCI has grown to be broader, larger and much more diverse than computer science itself. HCI expanded from its initial focus on individual and generic user behavior to include social and organizational computing, accessibility for the elderly, the cognitively and physically impaired, and for all people, and for the widest possible spectrum of human experiences and activities. It expanded from desktop office applications to include games, learning and education, commerce, health and medical applications, emergency planning and response, and systems to support collaboration and community. It expanded from early graphical user interfaces to include myriad interaction techniques and devices, multi-modal interactions, tool support for model-based user interface specification, and a host of emerging ubiquitous, handheld and context-aware interactions.” — John M. Carroll, author and a founder of the field of human-computer interaction.

The UX Value of HCI and Its Related Realms

HCI is a broad field which overlaps with areas such as user-centered design (UCD) , user interface (UI) design and user experience (UX) design . In many ways, HCI was the forerunner to UX design.

hci research work

Despite that, some differences remain between HCI and UX design. Practitioners of HCI tend to be more academically focused. They're involved in scientific research and developing empirical understandings of users. Conversely, UX designers are almost invariably industry-focused and involved in building products or services—e.g., smartphone apps and websites. Regardless of this divide, the practical considerations for products that we as UX professionals concern ourselves with have direct links to the findings of HCI specialists about users’ mindsets. With the broader span of topics that HCI covers, UX designers have a wealth of resources to draw from, although much research remains suited to academic audiences. Those of us who are designers also lack the luxury of time which HCI specialists typically enjoy. So, we must stretch beyond our industry-dictated constraints to access these more academic findings. When you do that well, you can leverage key insights into achieving the best designs for your users. By “collaborating” in this way with the HCI world, designers can drive impactful changes in the market and society.

Learn More about Human-Computer Interaction

The Interaction Design Foundation’s encyclopedia chapter on Human-Computer Interaction , by John M. Carroll, a founder of HCI, is an ideal source for gaining a solid understanding of HCI as a field of study.

Keep up to date with the latest developments in HCI at the international society for HCI, SIGCHI .

Learn the tools of HCI with our courses on HCI, taught by Professor Alan Dix, author of one of the most well-known textbooks on HCI:

Human-Computer Interaction: The Foundations of UX Design

Perception and Memory in HCI and UX

Design for Thought and Emotion

Questions related to Human-Computer Interaction (HCI)

Cognition in human-computer interaction includes the mental processes occurring between humans and computers. This encompasses perceiving inputs from the computer, processing them in the brain, and producing outputs like physical actions, speech, and facial expressions. 

The video above looks at cognition as a continuous input-output loop that goes from action, through to perception (input through our senses), to cognition (mental processing), back to action (the output). Although one might perceive this process as starting with perception, it is vital to remember that perceptions often trigger actions, but at their core, humans and animals focus on performing activities in the world. This understanding is crucial for the design of effective digital interactions.

Design in human-computer interaction, as discussed in the video, is about achieving goals within constraints. It involves understanding the purpose or goal, like enjoyment or work efficiency, and navigating the constraints, such as medium, platform, time, and money, to achieve that purpose. 

It is essential to understand the materials, both digital and human, and to make trade-offs between different goals and constraints. Ultimately, the central message is that the user is at the heart of what you do as a designer. Understanding the users and the technology you work with is crucial for successful design.

Ergonomics in Human-Computer Interaction (HCI) refers to the design and implementation of interfaces that ensure user comfort, efficiency, and effectiveness. In this video, HCI expert Prof Alan Dix discusses touch and haptics in user interfaces, highlighting the importance of ergonomics in device design.

Copyright holder: On Demand News-April Brown _ Appearance time: 04:42 - 04:57 _ Link: https://www.youtube.com/watch?v=LGXMTwcEqA4

Copyright holder: Ultraleap _ Appearance time: 05:08 - 05:15 _ Link: https://www.youtube.com/watch?v=GDra4IJmJN0&ab_channel=Ultraleap

For example, mobile phones and cars use haptic feedback to provide users with intuitive and engaging experiences. However, poorly implemented haptic feedback can confuse users. This underscores the importance of ergonomics in HCI to ensure that interfaces are user-friendly, intuitive, and do not cause strain or discomfort, ultimately enhancing the user's overall experience with a device or application.

Human-Computer Interaction (HCI) is crucial due to its direct impact on the user experience. 

As highlighted in the video, the shift towards service orientation, prompted by the internet and digital goods, has made usability and user experience increasingly important. Users now have multiple choice points and can easily swap services if they are not satisfied, which underscores the criticality of user experience. Prof Alan Dix uses the analogy of Maslow’s hierarchy of needs in the context of user interfaces, stating that once the basic needs of functionality and usability are addressed, user experience becomes the key differentiator. 

User experience is the factor that will make someone choose your product over another. Therefore, optimizing the HCI is paramount to ensure the success and competitiveness of a product or service.

HCI does not require any knowledge of coding. While coding can be a part of the design process and implementation, it is not necessary for understanding and applying the principles of human-computer interaction.

The first computer, as we know it today, was invented in the 1950s. At that time, computers were room-sized and cost millions of dollars or pounds or euros in current terms. Thomas Watson of IBM famously mispredicted that five computers would be enough forever, reflecting the sentiment of the time. Over the decades, the cost and size of computers have drastically reduced, making them accessible to the general public. By the mid-70s, the first personal computers were coming through, and today, the total number of computers and smartphones exceeds the number of people in the world. 

For a detailed evolution of computer technology, watch the video below:

Copyright holder: Tim Colegrove _ Appearance time: 3:02 - 3:09 Copyright license and terms: CC BY-SA 4.0, via Wikimedia Commons _ Link: https://commons.wikimedia.org/wiki/File:Trinity77.jpg

Copyright holder: Mk Illuminations _ Appearance time: 6:30 - 6:40 _ Link: https://www.youtube.com/watch?v=4DD5qLvHANs

If you are looking to study Human-Computer Interaction (HCI), the Interaction Design Foundation (IxDF) is the most authoritative online learning platform. IxDF offers three comprehensive online HCI courses:

HCI: Foundations of UX Design : This course provides a solid foundation in HCI principles and how they apply to UX design.

HCI: Design for Thought and Emotion : Unlock the secrets of the human mind and learn how to apply these insights to your work.

HCI: Perception and Memory : Learn about the role of perception and memory in HCI and how to design interfaces that align with human cognitive capabilities.

Enroll in these courses to enhance your HCI knowledge and skills from the comfort of your home.

Literature on Human-Computer Interaction (HCI)

Here’s the entire UX literature on Human-Computer Interaction (HCI) by the Interaction Design Foundation, collated in one place:

Learn more about Human-Computer Interaction (HCI)

Take a deep dive into Human-Computer Interaction (HCI) with our course Human-Computer Interaction: The Foundations of UX Design .

Interactions between products/designs/services on one side and humans on the other should be as intuitive as conversations between two humans—and yet many products and services fail to achieve this. So, what do you need to know so as to create an intuitive user experience ? Human psychology? Human-centered design? Specialized design processes? The answer is, of course,  all  of the above, and this course will cover them all.

Human-Computer Interaction (HCI) will give you the skills to properly understand, and design, the relationship between the “humans”, on one side, and the “computers” (websites, apps, products, services, etc.), on the other side. With these skills, you will be able to build products that work more efficiently and therefore sell better. In fact, the Bureau of Labor Statistics predicts the IT and Design-related occupations will grow by 12% from 2014–2024, faster than the average for all occupations. This goes to show the immense demand in the market for professionals equipped with the right design skills .

Whether you are a newcomer to the subject of HCI or a professional, by the end of the course you will have learned how to implement user-centered design for the best possible results .

In the “ Build Your Portfolio: Interaction Design Project ”, you’ll find a series of practical exercises that will give you first-hand experience of the methods we’ll cover. If you want to complete these optional exercises, you’ll create a series of case studies for your portfolio which you can show your future employer or freelance customers.

This in-depth, video-based course is created with the amazing Alan Dix , the co-author of the internationally best-selling textbook  Human-Computer Interaction and a superstar in the field of Human-Computer Interaction . Alan is currently professor and Director of the Computational Foundry at Swansea University.    

All open-source articles on Human-Computer Interaction (HCI)

Human computer interaction - brief intro.

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Interaction Design - brief intro

Data visualization for human perception, design iteration brings powerful results. so, do it again designer.

hci research work

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Usability Evaluation

Affordances, visual representation, disruptive innovation, contextual design, how to use mental models in ux design.

hci research work

Visual Aesthetics

Activity theory, wearable computing, card sorting, 3d user interfaces, end-user development, context-aware computing, social computing, human-robot interaction, open access - link to us.

We believe in Open Access and the  democratization of knowledge . Unfortunately, world class educational materials such as this page are normally hidden behind paywalls or in expensive textbooks.

If you want this to change , cite this page , link to us, or join us to help us democratize design knowledge !

Cite according to academic standards

Simply copy and paste the text below into your bibliographic reference list, onto your blog, or anywhere else. You can also just hyperlink to this page.

New to UX Design? We’re Giving You a Free ebook!

The Basics of User Experience Design

Download our free ebook The Basics of User Experience Design to learn about core concepts of UX design.

In 9 chapters, we’ll cover: conducting user interviews, design thinking, interaction design, mobile UX design, usability, UX research, and many more!

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Research   /   Research Areas Human-Computer Interaction

Human-Computer Interaction (HCI) is a rapidly expanding area of research and development that has transformed the way we use computers in the last thirty years. Research topics and areas include augmented-reality, collective action, computer-mediated communication, computer-supported collaborative work, crowdsourcing and social computing, cyberlearning and future learning technologies, inclusive technologies and accessibility, interactive audio, mixed-initiative systems, mobile interaction design, multi-touch interaction, social media, social networks, tangible user interfaces, ubiquitous computing, and user-centered design.

Northwestern hosts a vibrant HCI community across schools, with faculty and students involved in a wide range of projects. Students in HCI are enrolled in programs in Computer Science, Communication, Learning Sciences, and Technology & Social Behavior. Students also take courses and attend seminars through the Segal Design Institute.

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Human-Computer Interaction and Visualization

HCI researchers at Google have enormous potential to impact the experience of Google users as well as conduct innovative research. Grounded in user behavior understanding and real use, Google’s HCI researchers invent, design, build and trial large-scale interactive systems in the real world. We declare success only when we positively impact our users and user communities, often through new and improved Google products. HCI research has fundamentally contributed to the design of Search, Gmail, Docs, Maps, Chrome, Android, YouTube, serving over a billion daily users. We are engaged in a variety of HCI disciplines such as predictive and intelligent user interface technologies and software, mobile and ubiquitous computing, social and collaborative computing, interactive visualization and visual analytics. Many projects heavily incorporate machine learning with HCI, and current projects include predictive user interfaces; recommenders for content, apps, and activities; smart input and prediction of text on mobile devices; user engagement analytics; user interface development tools; and interactive visualization of complex data.

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From desktops and laptops to phones and tablets to virtual reality, wearable devices, the Internet of Things, and robotics, technologies based on computing are all around us. The field of human-computer interaction (HCI) studies how we interact with these technologies, and how those technologies in turn shape our world. HCI researchers seek to improve how humans interact with technology, to understand the societal impact of technologies, and to invent new technologies that alter the way we perceive and navigate the world around us.

UChicago CS includes many researchers and lab groups that investigate these angles using interdisciplinary, user-centered, and physical-computing approaches. Faculty and students design more usable privacy and security tools, improve how users interact with robots, programming languages, and IoT devices, and make technologies more inclusive for marginalized and underserved populations. Other groups design wearable devices and user interfaces that augment human abilities and create more seamless integration between the virtual and natural environments.

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Canon (computing for anyone) lab, human-robot interaction (hri) lab, super (security, usability, & privacy education & research) group, network operations and internet security (noise) lab, amyoli internet research (air) lab, human-computer integration lab, chicago human + ai (chai) lab, axlab – actuated experience lab, related faculty.

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News & Events

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Prof. Rebecca Willett awarded the SIAG DATA Career prize

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Argonne scientists use AI to identify new materials for carbon capture

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Alumni Spotlight: Dixin Tang, Assistant Professor of Computer Science at UT Austin

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NetMicroscope Uses AI to Improve Network Monitoring for a Better Internet Experience

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NeurIPS 2023 Award-winning paper by DSI Faculty Bo Li, DecodingTrust, provides a comprehensive framework for assessing trustworthiness of GPT models

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New research unites quantum engineering and artificial intelligence

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“Machine Learning Foundations Accelerate Innovation and Promote Trustworthiness” by Rebecca Willett

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Nightshade: Data Poisoning to Fight Generative AI with Ben Zhao

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Exploring 3D Paintbrush: An AI That Colors with Words

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Group From UChicago CS To Present Four Papers at Most Prestigious International Quantum Conference

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Alumni Spotlight: Get To Know Emily Wenger, a 2023 CS Graduate Who Was Just Named To The Forbes 30 Under 30 List

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Three UChicago PhD Students From The Department of Computer Science Named To Forbes 30 Under 30 List

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High School Students In The Collegiate Scholars Program Get To Know Robots

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AxLab Features Multidisciplinary Works at World’s Largest Art and Technology Festival

spring 2013

Cs376: research topics in human-computer interaction.

Monday & Wednesday, 1:15PM – 3:05PM , Littlefield 107

[email protected]

Michael Bernstein , Gates 308, Office Hours: Friday 3:50pm-5pm

ta :  Joy Kim , office hours Wednesdays 10:30-11:30, Gates 3B Atrium

ta :  Diana MacLean , office hours Mondays 12:00pm-1:00pm, Gates 372

Final Presentations

Date: Friday June 3rd, 12:15PM – 3:15PM

Jurors: Terry Winograd and Stu Card

Location: Wallenberg 124

Visitor Parking: near Cantor Art Center ( map ), and look for yellow and black 'P's on the map.

Come see final project presentations on Fri Jun 8 ! Free and open to the public!

This is a 4-unit course, open to all graduate students. For undergraduates, earning an A- or better in cs147 is a prerequisite. (Graduate students with a unit cap may enroll for 3 units; the workload is the same.) Students registered for the class will receive a letter grade—the "credit/no credit" option is not available.

Students in this course are encouraged to attend CS547, the HCI seminar ; Fridays 12:50 - 2:05pm.

Course Structure

The course comprises two pieces: reading and discussing research papers , and a quarter-long research project .

For each class period, students will submit short commentaries on the assigned readings ( submitted online in this format by 7am on the day of class). After 7am on the day of class, all commentaries will be made available for other students to read (again, through the online submission system ). The discussion leader and course staff will all read these before class to prepare for discussion. Students are expected to do all of the readings; commentaries are only required for those marked on the syllabus .

Students will lead one class discussion each. For details on how to structure a discussion, go here. The discussant(s) should meet with the course staff at the end of the previous class - come to this meeting with a plan for your discussion. On discussion day, students submit their materials instead of their commentary using the online submission system . The discussant should read all student commentaries before class and integrate them into the discussion. Finally, the discussant is responsible for grading the student commentaries.

Note: Stanford students can use the Stanford Library proxy for off-campus access to the readings posted on ACM Portal.

Submit Commentary?

Research Group Partner Choices due at end of class

Project Abstract Draft Due at 7:00am - Submit Online

Project Abstract Final Due at 7:00am - Submit Online

Please sign up for Project Progress Meetings .

Pilot Study Exercise at end of class on May 15th

Project Papers Due at at 7:00am - Submit Online

Project Presentations · 8:30am – 11:30am, Wallenberg 124 Guest Jurors: Terry Winograd and Stu Card -->

What do HCI Researchers do?

I’m a post-doctoral researcher in Human Computer Interaction (HCI), and here is my parents’ answer when somebody asks them what I do for a living: “she is doing computer science”.

Although this is not not completely wrong, it is still… a bit vague. And that’s entirely my fault, because I’ve never been patient enough to tell them what I actually do. In fact, explaining to our (not so tech-savvy) friends or relatives what we actually do as HCI researchers can be, let’s be honest (and polite), quite painful.

So here is my attempt to describe the job of a HCI researcher. This post is mainly intended to:

  • parents, siblings, friends, partners that are willing to dedicate 20 minutes of their time to try and understand what their child, sibling, friend or partner is actually doing when/if they go to work;
  • masters’ students who are considering doing a PhD in HCI but are not so sure what is it all about;
  • new PhD students in HCI who are a bit lost and are not sure what they should do with their time or what their co-workers are actually doing.

I thought about discussing what topics HCI researchers work on, and what’s the point of HCI research, but the article was already too long so it would probably be for a next post. In the meantime, this is what I’m going to talk about:

Helping the lab and the research group.

Helping the community., doing stuff.

Let’s start by stating the obvious: HCI researchers, after all, are mainly researchers. HCI is just their field of expertise. So what does a researcher do? First thing first, a researcher does not only do research. Researchers’ activities mainly fall into two categories : teaching and teaching-related tasks; research and research-related tasks . What differentiates HCI researchers from others is what they do when they are not teaching, reading or writing. Or, in other words, when they actually do research.

Most researchers working in the public sector are also teachers. The official title depends on the countries (click here for the Wikipedia list), and on the rank of the teacher. Examples include teaching assistant, lecturer, associate professor and professor. Some researchers, such a the majority of CNRS researchers in France, are not entitled to any teaching duty.

The amount of teaching varies a lot, depending on the researchers’ status and their country of residence. For example, in France, a regular PhD student in Computer Science will have 64 hours of lectures a year while a “Maître de Conférence” is entitled to 128 hours of lectures, which equals to 192 of “lab hours”. In Slovenia, things are also different. At my research lab, my colleagues who are PhD candidates have to teach around 300 lab hours while as a teacher assistant with a PhD, I am entitled to around 180 hours of lectures (6 hours a week). The amount of teaching that researchers are supposed to do can also differ from the amount of teaching they actually do - it is not rare that teachers to additional hours because there isn’t enough staff in the department.

But one should not forget that teaching is not just about giving lectures in front of students. Teaching also includes: preparing the lectures, preparing and correcting the exams, entering the grades, answering students’ emails, learning about educational software or pedagogical approaches, etc. Teaching also involve activities related to the department, such as attending meetings to elaborate the new syllabus or promoting the department programs at various fairs.

Each researcher will spend a different amount of time on each of these activities: some will prepare their Powerpoint in no time at all, others will spend hours polishing it; some will never answer any emails, others will not only answer emails but also meet up with students to give additional explanations.

When researchers are not teaching, they try to do some research. However, and as for teaching, doing research is not only about doing research :) Research also involves a lot of peripheral activities that can be very time-consuming and can leave little to no time at all for actual research.

At the local level, these activities can include: attending a seminar; communicating about research results through articles or interviews for the laboratory newsletter, attending meetings organized by the laboratory to address important issues (e.g. do we need to hire a new researcher) or more trivial ones (e.g. shall the lab pay for the new coffee machine ?).

A consequent amount of time is also dedicated to research funding. In order to get money for their projects (e.g. to buy equipment or to be able to go to a conference), researchers have to write project proposals, and, if they got some money, they usually also have to write reports that describe how their research is progressing and how they are using the money that they received. Finding funds for a research project often involves lots of meetings with potential partners, and lots of administrative tasks. Once a researcher get some funds, it is time to spend it wisely! Easy peasy? Not really… Researchers who need to buy new equipment may spend hours trying to figure out what is the best equipment and then even more hours to get a certain amount of quotes from different companies.

Depending on how high the researcher is in the hierarchy, these activities can take a few hours only, or most of the researcher’s time. A new and candid PhD student will very unlikely be involved in so many and time-consuming activities, except for the fun part (attending the conferences), while the director of a lab or of a research group will have to answer tons of emails every day.

Source: PhD Comics

At a global level, these research-related tasks are often referred to as community services . This may sound like a weird expression, but it is actually quite self-explanatory. Researchers working in the same field pertain to a community . This community exist through collaborations, publications being read and distributed among researchers, networks, but also conferences, workshops and so on. Within the HCI community, there is one community that is particularly big and strong: the CHI community - CHI being the most important conference that everybody MUST attend to really consider himself/herself a true HCI researcher :) (yes, I am sarcastic).

Community services may include: helping with the organization of a conference; being a member of a committee and attending meetings; setting up a new local chapter, which will later organize seminars to help researchers share their knowledge and grow their network; being responsible for the proceedings of a journal, etc. The services can be made for regional, national or international communities.

Reviewing articles is an other important activity. The process is as follows: a group of researchers finally manage to put together an article after weeks/months/years of research. They sent it to a conference or a journal. The members of the editorial board will assign other researchers to read and comment this article. The point is to decide whether the article is worth publishing at the said venue. These reviewers are selected based on their notoriety and/or levels or expertise. As a researcher, you can sign in to some systems to say that you are willing to review, or you can receive an email reading something like: “Dear Researcher, would you like to review this article ? We need your expertise.” If you accept to review the article, your job is to read it and write down a summary that will highlight the pros and cons of the article. Based on this, you make a recommendation on whether this article should be accepted or not. Sounds simple, right?

You can have a look at this page to see some examples of good and bad reviews.

Finally, research!

When researchers are done with all of this teaching, administrative tasks and community services, they can work on their research. Finally! To me, research consists of three main activities: reading , doing , and writing . Some researchers follow these steps in a very linear way, other tend to do everything at the same time. Some love programming, others much prefer writing, very few like to spend hours reading.

So what is it all about? As researchers, our aim is to produce and disseminate knowledge. To produce knowledge, we must first know what knowledge already exist. This is the “reading” part. Let’s give an example. I am actually working on interactive web documentaries. When I started my post-doc, I had never worked on this topic, so I didn’t know what knowledge already existed on this topic. I therefore read a lot to gain some knowledge, e.g. I read articles published by other research laboratories or popular websites. I also watched several web documentaries and read Wikipedia pages about topics I was not familiar with. After reading all of this, I had a clearer idea of what were the actual “gaps” in the literature. For example, I found out that the interactivity of web documentary has not been studied much, i.e. we do not really know whether people really enjoy clicking on different parts of a website to access some videos or if it actually annoys them so much that they close their browser because of this (this is a bit simplified, but that’s the general idea).

There are thousands of thousands of articles out there, published by thousands of researchers in thousands of venues. Reading without a specific purpose in mind can be extremely time-consuming. However, reading on a regular basis is still very important: any article can prove useful at some point, new articles are published everyday and one should stay up-do-date, reading papers can inspire new ideas and reading articles is the best way to learn more about one topic.

A good thing to realise how many articles are out there is to go to Google Scholar and to type in some keywords. For example “ smartphone food ” lead to… 168 000 results!

After/while reading, a researcher will come up with some ideas on how to “create” knowledge, e.g by starting addressing a problem that hasn’t be resolved yet. This part of doing research can be extremely diverse, especially in HCI. There is no one single procedure to follow, no single methodology.

How researchers will address a problem depends on their background, skills, interest, time they are willing to spend on that project, fundings and equipments they have, etc. This can include: conducting interviews, developing a new software and evaluating how it works, developing a new theory, designing a new algorithm, analyzing large data sets, comparing different ways of interacting with a smartphone or a computer (e.g. vocal commands vs gestures), building a new system (e.g. an invisible drone)… the list is endless!

Researchers will spend hours implementing their ideas. Of course, the first idea is rarely the best one. So researchers will spend even more hours trying out new ideas, discussing their ideas with their peers, redefining their original research question, implementing new ideas and testing them out. And so on and so on, until they reach a point where they think their idea, and its actual implementation (be it a theoretical framework or a very futurist technology), is actually a worthy “contribution” - it adds knowledge to the existing knowledge. It might sound simple, but this is the most engaging and demanding part of research.

According to J. Wobbrock and J. Kientz , seven types of HCI contributions exist. I’ll focus on three common types:

Artifacts . This is, I believe, the most popular type of contribution within the HCI community. The idea is to design a new system, tool, piece of software, technique, you-name-it in order to better understand how this new you-name-it could help people achieve a task more efficiently, improve accessibility, change the way people consider/use technology, facilitate communication, etc. The purpose of this new artifact can vary a lot and be perceived quite differently: artifacts that I might find not so useful might be seen as real game-changers by other researchers :)

Empirical contributions are based on data. Data may come from experiments, interviews, sensors, observations. Anything. Thanks to these data and through hours of data analysis, researchers try to answer one question. For example, if the question is “is it easier to read white subtitles on a black background rather than yellow subtitles”, researchers will collect data (e.g. by measuring how many seconds people need to read a sentence) and then analyze it to conclude something like: “people need less time to read yellow subtitles than white subtitles”. Conducting experiments is therefore one of the key activities of many HCI researchers: whether in the lab or in the wild, experiments allow them to empirically measure how people interact with systems.

Surveys are also called literature reviews . They summarize existing research by comparing results, artifact characteristics, methodologies, etc. Their aim is to help structure knowledge on what topic “with the goal of exposing trends and gaps”. Compared to artifacts and empirical contributions, surveys may seem easier to do as they only require reading, analysing and writing, but they can also be very time-consuming. A good survey will help other researchers identify what knowledge already exist, what questions haven’t been addressed yet, what are the best tools and techniques that have been used and investigated so far, etc.

To me, that’s the most interesting part. For many researchers that I know, this is the boring part. But writing is really important, because at the end, the article is the main way to disseminate knowledge that researchers somehow managed to create. HCI researchers usually publish 10-pages long articles in conferences or 20 to 30-pages long articles in journals. Regardless of the venue, one article usually contains the following information:

  • what is the research about?
  • what was the literature saying, and how does the proposed research contribute to the literature?
  • how was research conducted and what were the results?
  • what are the key findings and limitations of the research work?

Writing an article may sound easy, but it is actually demanding. Each word is important, and each sentence is important. Researchers have to be sure that any other researchers will be able to understand their work. Figures also play a major role and designing good figures can also take a lot of time. Adding references to other articles is also quite boring and time-consuming.

Writing an article is not a linear process: I do not know anyone who is able to write an article from A to Z without jumping back and forth between the sections, editing, adding or removing paragraphs. Also, and because researchers usually write articles collaboratively, articles go from one researcher to another, leading to different versions of the articles with comments, suggestions, etc. which must all be taken into account. Writing help to make sure that an idea is clear, or that a methodology is sound. If I am not able to write down a correct and interesting research question, they are high chances that I am actually not sure what the research question is. In highschool, one of my teachers used to remind us of one citation from Boileau, whenever we had to write essays:

“Whatever is well conceived is clearly said, And the words to say it flow with ease.”

This couldn’t be more true when it comes to writing research articles.

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World Leaders in Research-Based User Experience

Top research laboratories in human-computer interaction (hci).

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March 30, 2002 2002-03-30

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Web design and usability are subsets of the greater discipline of human-computer interaction (HCI). Dating back to Vannevar Bush's description of hypertext in 1945, Doug Engelbart 's invention of the mouse in 1964, and many other early projects, HCI has a rich history of research that has defined the way we interact with technology today.

Even though good HCI research occurs at hundreds of worldwide locations, a few research labs have defined the field and nurtured the most important work. Here's my list of the best.

In This Article:

The dawn of time: 1945-1979, a first look: 2000-2010, making the list: criteria, long-term trend: the fall of the good, the future of corporate research.

Gold: Stanford Research Institute (SRI) Silver: Xerox PARC Bronze: Bell Laboratories

Gold: Xerox PARC Silver: IBM T.J. Watson Research Center, Yorktown Heights Bronze: MIT Media Lab

Gold: Bell Communications Research (Bellcore) Silver: Apple Computer Advanced Technology Group Bronze: Xerox PARC

It's early yet to truly evaluate research labs' contribution to this decade, so check back in 2010 for the final score. Currently, my assessment of the best HCI research labs is:

Gold: Microsoft Research Silver: Xerox PARC Bronze: Carnegie Mellon University

( Update 2013 : I think my assessment in 2002 proved fairly predictive for the decade, because now with the benefit of hindsight I would still give out the same "medals.")

These lists obviously reflect my preferences as to what constitutes important research topics. I tend to place more weight on fundamental advances in two areas: understanding how people use technology and understanding the best methods for designing for humans (both of which were emphasized by the Bell system and the old IBM research group). I place less weight on demonstrations of new interface gadgets (as emphasized by the Media Lab, Apple, and Microsoft).

What do these lists of best HCI labs through history tell us? First, that PARC has been really good . It is the only lab to make the list every decade.

Unfortunately, the second and more striking conclusion is that the list highlights the rise and fall of the mighty . Very few labs that dominated during the 20th Century have any kind of prominence in HCI today. Also, besides Xerox, only the Bell system made the list more than once.

I certainly don't think that companies go downhill because they fund good user interface research. However, there might be a tendency for companies to reach the top of the HCI field when they've already peaked. Unfortunately, HCI has rarely been the first priority of new research organizations, so by the time research managers recognize the need for it and build up a world-class HCI team, it's often too late.

It's striking that only two of the 12 research medals went to universities. I think this is because university departments seem to view the best HCI research as both too mundane and too resource intensive . Many academics disdain research topics that are closely connected to real-world needs. For proof, look no further than the appalling lack of Web usability research. There are more papers on unworkable, esoteric 3-D browsers than on how hundreds of millions of people use the biggest real-time collaborative system ever built.

Although HCI research can be conducted on a small budget, most of the best projects do require the lavish resources that leading corporate labs have historically provided. Now, however, the future of the field is in dire straits because there are almost no big-budget labs left. Will it be worth making a best-of list for 2010-2020? One can only hope.

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What Is HCI (Human-Computer Interaction)? Meaning, Importance, Examples, and Goals

Human-computer interaction (HCI) targets the design and implementation of interactive technology.

Human-computer interaction (HCI) is defined as the field of study that focuses on optimizing how users and computers interact by designing interactive computer interfaces that satisfy users’ needs. This article explains the fundamentals of HCI, its goals, importance, and examples.

Table of Contents

What is hci, importance of hci, examples of hci, goals of hci.

Human-computer interaction (HCI) is the field of study that focuses on optimizing how users and computers interact by designing interactive computer interfaces that satisfy users’ needs. It is a multidisciplinary subject covering computer science, behavioral sciences, cognitive science, ergonomics, psychology, and design principles.

The emergence of HCI dates back to the 1980s, when personal computing was on the rise. It was when desktop computers started appearing in households and corporate offices. HCI’s journey began with video games, word processors, and numerical units.

However, with the advent of the internet and the explosion of mobile and diversified technologies such as voice-based and Internet of Things (IoT) , computing became omnipresent and omnipotent. Technological competence further led to the evolution of user interactions. Consequently, the need for developing a tool that would make such man-machine interactions more human-like grew significantly. This established HCI as a technology, bringing different fields such as cognitive engineering, linguistics, neuroscience, and others under its realm.

Today, HCI focuses on designing, implementing, and evaluating interactive interfaces that enhance user experience using computing devices. This includes user interface design , user-centered design, and user experience design.

Human-Computer Interaction

Human-Computer Interaction

Key components of HCI

Fundamentally, HCI is made up of four key components :

1. The user

The user component refers to an individual or a group of individuals that participate in a common task. HCI studies users’ needs, goals, and interaction patterns. It analyzes various parameters such as users’ cognitive capabilities , emotions, and experiences to provide them with a seamless experience while interacting with computing systems.

2. The goal-oriented task

A user operates a computer system with an objective or goal in mind. The computer provides a digital representation of objects to accomplish this goal. For example, booking an airline for a destination could be a task for an aviation website. In such goal-oriented scenarios, one should consider the following aspects for a better user experience:

  • The complexity of the task that the user intends to accomplish
  • Knowledge and skills necessary to interact with the digital object
  • Time required to carry out the task

3. The interface

The interface is a crucial HCI component that can enhance the overall user interaction experience . Various interface-related aspects must be considered, such as interaction type (touch, click, gesture, or voice), screen resolution, display size, or even color contrast. Users can adjust these depending on the user’s needs and requirements.

For example, consider a user visiting a website on a smartphone. In such a case, the mobile version of the website should only display important information that allows the user to navigate through the site easily. Moreover, the text size should be appropriately adjusted so that the user is in a position to read it on the mobile device. Such design optimization boosts user experience as it makes them feel comfortable while accessing the site on a mobile phone.

4. The context

HCI is not only about providing better communication between users and computers but also about factoring in the context and environment in which the system is accessed. For example, while designing a smartphone app, designers need to evaluate how the app will visually appear in different lighting conditions (during day or night) or how it will perform when there is a poor network connection. Such aspects can have a significant impact on the end-user experience.

Thus, HCI is a result of continuous testing and refinement of interface designs that can affect the context of use for the users.

See More: What Is Semantic Analysis? Definition, Examples, and Applications in 2022

HCI is crucial in designing intuitive interfaces that people with different abilities and expertise usually access. Most importantly, human-computer interaction is helpful for communities lacking knowledge and formal training on interacting with specific computing systems.

With efficient HCI designs, users need not consider the intricacies and complexities of using the computing system. User-friendly interfaces ensure that user interactions are clear, precise, and natural.

Let’s understand the importance of HCI in our day-to-day lives:

1. HCI in daily lives

Today, technology has penetrated our routine lives and has impacted our daily activities. To experience HCI technology, one need not own or use a smartphone or computer. When people use an ATM , food dispensing machine, or snack vending machine, they inevitably come in contact with HCI. This is because HCI plays a vital role in designing the interfaces of such systems that make them usable and efficient.

2. Industry

Industries that use computing technology for day-to-day activities tend to consider HCI a necessary business-driving force. Efficiently designed systems ensure that employees are comfortable using the systems for their everyday work. With HCI, systems are easy to handle, even for untrained staff.

HCI is critical for designing safety systems such as those used in air traffic control (ATC) or power plants. The aim of HCI, in such cases, is to make sure that the system is accessible to any non-expert individual who can handle safety-critical situations if the need arises.

3. Accessible to disabled

The primary objective of HCI is to design systems that make them accessible, usable, efficient, and safe for anyone and everyone. This implies that people with a wide range of capabilities, expertise, and knowledge can easily use HCI-designed systems. It also encompasses people with disabilities. HCI tends to rely on user-centered techniques and methods to make systems usable for people with disabilities .

4. An integral part of software success

HCI is an integral part of software development companies that develop software for end-users. Such companies use HCI techniques to develop software products to make them usable. Since the product is finally consumed by the end-user, following HCI methods is crucial as the product’s sales depend on its usability.

5. Useful for untrained communities

Today, user manuals for general computer systems are a rarity. Very few advanced and complex computing systems provide user manuals. In general, users expect the systems to be user-friendly and enable them to access the system within a few minutes of interacting with it. Here, HCI is an effective tool that designers can use to design easy-to-use interfaces . HCI principles also ensure that the systems have obvious interfaces and do not require special training to be used. Hence, HCI makes computing systems suitable for an untrained community.

See More: What Is a Decision Tree? Algorithms, Template, Examples, and Best Practices

Technological development has brought to light several tools, gadgets, and devices such as wearable systems, voice assistants, health trackers, and smart TVs that have advanced human-computer interaction technology.

Let’s look at some prominent examples of HCI that have accelerated its evolution.

1. IoT technology

IoT devices and applications have significantly impacted our daily lives. According to a May 2022 report by IoT Analytics, global IoT endpoints are expected to reach 14.4 billion in 2022 and grow to 27 billion (approx.) by 2025. As users interact with such devices, they tend to collect their data, which helps understand different user interaction patterns. IoT companies can make critical business decisions that can eventually drive their future revenues and profits.

A recent development in the field of HCI introduced the concept of ‘ pre-touch sensing ’ through pre-touch phones. This means the phone can detect how the user holds the phone or which finger approaches the screen first for operation. Upon detecting the user’s hand movements, the device immediately predicts the user’s intentions and performs the task before the user gives any instructions.

Another HCI-related development is that of ‘ Paper ID ’. The paper acts as a touchscreen, senses the environment, detects gestures, and connects to other IoT devices. Fundamentally, it digitizes the paper and executes tasks based on gestures by focusing on man-machine interaction variables.

2. Eye-tracking technology

Eye-tracking is about detecting where a person is looking based on the gaze point. Eye-tracking devices use cameras to capture the user’s gaze along with some embedded light sources for clarity. Moreover, these devices use machine learning algorithms and image processing capabilities for accurate gaze detection .

Businesses can use such eye-tracking systems to monitor their personnel’s visual attention. It can help companies manage distractions that tend to trouble their employees, enhancing their focus on the task. In this manner, eye-tracking technology, along with HCI-enabled interactions, can help industries monitor the daily operations of their employees or workers.

Other applications include ‘driver monitoring systems’ that ensure road security. Moreover, in the future, HCI-enabled eye-tracking systems may allow users to scroll through a computer screen just by rolling their eyeballs.

3. Speech recognition technology

Speech recognition technology interprets human language, derives meaning from it, and performs the task for the user. Recently, this technology has gained significant popularity with the emergence of chatbots and virtual assistants.

For example, products such as Amazon’s Alexa, Microsoft’s Cortana, Google’s Google Assistant, and Apple’s Siri employ speech recognition to enable user interaction with their devices, cars, etc. The combination of HCI and speech recognition further fine-tune man-machine interactions that allow the devices to interpret and respond to users’ commands and questions with maximum accuracy. It has various applications, such as transcribing conference calls, training sessions, and interviews.

4. AR/VR technology

AR and VR are immersive technologies that allow humans to interact with the digital world and increase the productivity of their daily tasks. For example, smart glasses enable hands-free and seamless user interaction with computing systems. Consider an example of a chef who intends to learn a new recipe. With smart glass technology, the chef can learn and prepare the target dish simultaneously.

Moreover, the technology also reduces system downtime significantly. This implies that as smart AR/VR glasses such as ‘Oculus Quest 2’ are supported by apps, the faults or problems in the system can be resolved by maintenance teams in real-time. This enhances user experience in a minimum time span. Also, the glasses can detect the user’s response to the interface and further optimize the interaction based on the user’s personality, needs, and preferences.

Thus, AR/VR technology with the blend of HCI ensures that the task is accomplished with minimal errors and also achieves greater accuracy and quality. Currently, HCI research is targeting other fields of study, such as brain-computer interfaces and sentiment analysis, to boost the user’s AR/VR experience.

A recent development in this regard has been enabled via ‘ Dexta Haptic Gloves .’ These VR gloves can sense and process touch parameters such as surface hardness, softness, etc. These gloves can memorize a user’s finger movements by locking and unlocking the finger joints as they interact in the VR environment. Later, the gloves can replicate the recorded data of feelings across various degrees in real life.

5. Cloud computing

Today, companies across different fields are embracing remote task forces . According to a ‘Breaking Barriers 2020’ survey by Fuze (An 8×8 Company), around 83% of employees feel more productive working remotely. Considering the current trend, conventional workplaces will witness a massive rejig and transform entirely in a couple of decades. Thanks to cloud computing and human-computer interaction, such flexible offices have become a reality.

Moreover, an employee can access data on the cloud from any physical location by exploiting cloud-based SaaS services. Such virtual settings streamline workflows and support seamless collaboration with remote teams across industry verticals without impacting productivity. Thus, with time, the idea of traditional offices will cease to exist, mainly because of SaaS and HCI.

See More: What Is General Artificial Intelligence (AI)? Definition, Challenges, and Trends

The principal objective of HCI is to develop functional systems that are usable, safe, and efficient for end-users. The developer community can achieve this goal by fulfilling the following criteria:

  • Have sound knowledge of how users use computing systems
  • Design methods, techniques, and tools that allow users to access systems based on their needs
  • Adjust, test, refine, validate, and ensure that users achieve effective communication or interaction with the systems
  • Always give priority to end-users and lay the robust foundation of HCI

To realize the above points, developers must focus on two relevant areas: usability and user experience . Let’s look at each category in detail:

1. Usability

Usability is key to HCI as it ensures that users of all types can quickly learn and use computing systems. A practical and usable HCI system has the following characteristics:

  • How to use it: This should be easy to learn and remember for new and infrequent users to learn and remember. For example, operating systems with a user-friendly interface are easier to understand than DOS operating systems that use a command-line interface.
  • Safe: A safe system safeguards users from undesirable and dangerous situations. This may refer to users making mistakes and errors while using the system that may lead to severe consequences. Users can resolve this through HCI practices. For example, systems can be designed to prevent users from activating specific keys or buttons accidentally. Another example could be to provide recovery plans once the user commits mistakes. This may give users the confidence to explore the system or interface further.
  • Efficient : An efficient system defines how good the system is and whether it accomplishes the tasks that it is supposed to. Moreover, it illustrates how the system provides the necessary support to users to complete their tasks.
  • Effective : A practical system provides high-quality performance. It describes whether the system can achieve the desired goals.
  • Utility : Utility refers to the various functionalities and tools provided by the system to complete the intended task. For example, a sound utility system offers an integrated development environment (IDE) that provides intermittent help to programmers or users through suggestions.
  • Enjoyable : Users find the computing system enjoyable to use when the interface is less complex to interpret and understand.

2. User experience

User experience is a subjective trait that focuses on how users feel about the computing system when interacting with it. Here, user feelings are studied individually so that developers and support teams can target particular users to evoke positive feelings while using the system.

HCI systems classify user interaction patterns into the following categories and further refine the system based on the detected pattern:

  • Desirable traits – satisfying, enjoyable, motivating, or surprising
  • Undesirable traits – Frustrating, unpleasant, or annoying

See More: What Is Cortana? Definition, Working, Features, and Challenges

Cleverly designed computer interfaces motivate users to use digital devices in this modern technological age. HCI enables a two-way dialog between man and machine. Such effective communication makes users believe they are interacting with human personas and not any complex computing system. Hence, it is crucial to build a strong foundation of HCI that can impact future applications such as personalized marketing, eldercare, and even psychological trauma recovery.

Did this article help you understand the fundamental principles of human-computer interaction? Comment below or let us know on Facebook Opens a new window , Twitter Opens a new window , or LinkedIn Opens a new window . We’d love to hear from you!

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International Conference on Human-Computer Interaction

HCII 2021: Design, User Experience, and Usability: UX Research and Design pp 34–47 Cite as

Science Fiction—An Untapped Opportunity in HCI Research and Education

  • Philipp Jordan 11 &
  • Paula Alexandra Silva 12  
  • Conference paper
  • First Online: 03 July 2021

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Part of the Lecture Notes in Computer Science book series (LNISA,volume 12779)

This work open up a conversation about the opportunities that Science Fiction offers to Human-Computer Interaction (HCI) and Design research. In doing so, first, it briefly challenges the term Design Fiction, an emerging concept with increasing popularity in HCI and Design research. Design Fictions are either, manifest design propositions, or intangible, imagined future interfaces, speculative interactions and would-be environments. Design Fictions as useful as they are, however, are not necessarily something new nor innovative in themselves. Speculative design and evaluation methods all have been staple methods of Computer Science research since the establishment of HCI as a discrete field sometime in the 1980s. Second, the paper proceeds to propose that the domain of Science Fiction could not only be useful, but rightly considered, as a legitimate field of creative inquire in HCI and Design education. By reframing the notion of Science Fiction from an ‘anecdotal gimmick’ toward an ‘area of study’ a novel, wide-ranging space for design inspiration, ingenuity and creativity opens up for conceptual exploration. We believe that such an elevation of Science Fiction as a serious research topic has strong potential to inform the Computer Science, HCI and Design research application and education endeavours of the future.

  • Computer science research and education
  • Design Fiction
  • Speculative future studies
  • Popular culture in science
  • Science Fiction

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https://slate.com/technology/2012/03/bruce-sterling-on-design-fictions.html .

And its many derivatives, among those discursive, critical or reflective design etc. pp.

According to some sources, Science Fiction dates back as early as 2AD with the Greek travel tale “A True Story” , a work consensually accepted as the first known writing with basic fictional elements, for example outer space travel and interstellar conflicts.

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Doctorow, C., Warner, C., Perkowitz, S., Johnson, B.D.: Science Fiction Prototyping: Designing the Future with Science Fiction (Synthesis Lectures on Computer Science). Morgan & Claypool Publishers (2011). https://www.morganclaypool.com/doi/abs/10.2200/S00336ED1V01Y201102CSL003

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Jordan, P., Silva, P.A. (2021). Science Fiction—An Untapped Opportunity in HCI Research and Education. In: Soares, M.M., Rosenzweig, E., Marcus, A. (eds) Design, User Experience, and Usability: UX Research and Design. HCII 2021. Lecture Notes in Computer Science(), vol 12779. Springer, Cham. https://doi.org/10.1007/978-3-030-78221-4_3

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Project #1 a new bridge to the digital economy: integrated ai-augmented learning and collaboration.

Mentor: Carolyn Rose , faculty

Description: This three-year NSF Future of Work (FOW) project, which started in October of 2022, seeks to address shortages of IT workers, while creating cost-effective, accessible pathways to living wage digital economy jobs for workers who previously lacked those opportunities. The tools and knowledge created by the project could eventually be applied to other STEM-focused community college degree programs across the nation, potentially impacting the lives of millions. This interdisciplinary project offers numerous opportunities to embed undergraduate research experiences related to advances in AI to enable learning interventions, design of interventions motivated by learning sciences principles, or development of extensions to an AI-augmented learning platform. The project will tackle five research questions: First, how can the Knowledge-Learning-Instruction (KLI) framework developed by learning scientists be used to align knowledge components in community college IT courses with the most effective AI-driven educational technologies to enhance and accelerate learning of those components? Second, to what extent do intelligent tutoring systems (ITS) and computer-supported collaborative learning (CSCL) experiences increase mastery and decrease the time needed to achieve it? Third, to what extent and in what ways do forms of example-based learning, used together with ITS and CSCL, further support learning and enable a wider range of learners to succeed? Fourth, to what extent can CSCL technology foster effective collaboration between community college students in 2-year information technology degree programs and the professional staff of partner firms on real-world (cloud computing) problems in the context of capstone projects and internships? Fifth, how successfully do students in the AI-augmented curricular pathway created by this project move into IT jobs relative to students in the standard course pathways?

Nature of Student Involvement: The two REU interns will work closely with McLaren, Rosé, and Teffera to achieve the project goals described above. The REU interns will be involved in weekly project meetings with McLaren’s or Rosé’s in which the research goals of the project and progress will be discussed. The REUs will also have the opportunity to work closely and exchange experiences with many other undergraduate summer interns who annually work on human-computer interaction (HCI) projects within Carnegie Mellon’s Human Computer Interaction Institute. A variety of learning opportunities will arise within the summer program at CMU, including a poster session and research talks by CMU faculty that the REU interns are encouraged to attend.

Skills we are interested in (not all required):

  • Experience with curriculum design
  • Running user studies, programming in Python
  • Artificial intelligence/NLP/Machine Learning

Project #2 Active learning in STEM education

Mentor: Paulo Carvalho , systems scientist 

Description: Mastering material in STEM classes requires students to learn and memorize large amounts of new knowledge in a short period of time. One way that has long been argued to improve such learning is by having students practice new knowledge by spacing questions over time (spaced retrieval practice). However, the evidence for the benefits of spaced retrieval practice in STEM contexts is limited. How can learn by doing be optimized in STEM classes and what computational algorithms best capture this learning?

Nature of Student Involvement: Students will be involved in all steps of experimental research, data analytics, and student modeling.

  • Quantitative data analyses
  • Experience with experimental design and data collection
  • Data science/learning analytics/student modeling experience preferred but not required

Project #3 Advancing Metamaterials by exploring novel structures, developing design tools and fabrication methods

Mentor: Alexandra Ion , faculty 

Description: We are looking to push the boundaries of mechanical metamaterials by unifying material and device. Metamaterials are advanced materials that can be designed to exhibit unusual properties and complex behavior. Their function is defined by their cell structure, i.e., their geometry. Such materials can incorporate entire mechanisms, computation, or re-configurable properties within their compliant cell structure, and have applications in product design, shape-changing interfaces, prosthetics, aerospace and many more.

In this project, we will develop design tools that allow novice users and makers to design their own complex materials and fabricate them using 3D printing or laser cutting. This may involve playfully exploring new cell designs, creating novel application examples by physical prototyping and developing open source software.

Nature of Student Involvement: Students will be part of all stages of research and will be fully embedded within the lab. We aim to give students a good insight into the nature of research and make it a fun summer!

  • CS skills: software development, background in geometry, optimization, and/or simulation
  • 3D modeling basics (CAD tools, e.g., Autodesk Fusion 360 or similar)
  • Basic knowledge of classical mechanics or material science

Project #4 AI in the Accessible Kitchen: Supporting Blind and Visually Impaired People in Performing Activities of Daily Living

Mentor: Patrick Carrington , faculty 

Description: Poor nutrition is prevalent among people with vision impairments. Studies have shown that this poor nutritional status is due to a number of factors, including social and structural issues, financial barriers, as well as independent meal preparation challenges. Previously reported aversions to cooking have led to dietary choices that include eating at restaurants over 40% of the time. The significant financial burden of these choices, combined with the aversion to cooking “from-scratch meals” leads to the alternative option of buying and cooking frozen or prepared foods which are costly, unhealthy, and calorie-rich. Challenges associated with preparing meals include sensory, procedural, and physical challenges. Our research has aimed to address this gap by developing systems that bridge the digital and physical challenges faced by vision impaired people to enable more independent meal preparation. This project would involve hardware and software prototyping as well as user studies.

Nature of Student Involvement: The student would be involved in hardware and software prototyping as well as early user tests.

Skills we are interested in (not all required):  The ideal student has some experience with 

  • Sensors 
  • UI design/development
  • Qualitative methods/data analysis

Project #5 AI Privacy

Mentor: Sauvik Das , faculty

Description: This project focuses on advancing our vision of "Privacy through Design" in the development of AI products and services. REUs will collaborate with PIs Das and Forlizzi, as well their Ph.D. students. The project entails co-designing materials aimed at helping AI practitioners prioritize privacy in consumer-facing AI products. It builds upon two key research efforts: interviews with 35 industry AI professionals to understand their privacy practices, and the development of a taxonomy of consumer AI privacy harms based on AI incidents and failures. The participating undergraduates will have the opportunity to brainstorm, create, and evaluate tools and methods designed to mitigate privacy risks in AI product design, contributing directly to the evolving landscape of AI and privacy.

Nature of Student Involvement: Students will be involved in ideating, creating and/or evaluating tools and resources to help AI practitioners mitigate privacy risk

  • Programming experience to build prototype systems
  • Experience with qualitative methods (e.g., interviews)
  • Prototyping systems with LLMs

Project #6 AI-CARING: Agents, Care Coordination, Trust and Affiliation

Mentor: Mai Lee Chang , postdoctoral fellow

Description: AI-CARING is a NSF AI Institute that is committed to both doing foundational AI research and developing technology that is useful and beneficial for society. The overall project focuses on developing AI systems to aid older adults, including those who experience cognitive decline, to continue living in their homes longer.

Our thrust focuses on how AI systems can learn the structures and forms of people's interpersonal relationships and how agents can provide support for tasks of daily living that support people's performance of self and reinforce their close familial bonds, friendships, and relationships with professionals like their doctors and other care providers.

Over the summer, we want to explore what an agent will need to learn about older adults’ and their informal caregivers’ (e.g., spouses, adult children, neighbors) day-to-day activities coordination (e.g., getting to doctor's appointments, getting food, arranging services, picking up meds) in order to provide support that is robust to uncertainty and changes in goals, care network structure, and environment. This work will capture the practices, priorities, values, triggers, and breakdowns in coordination. We are also interested in identifying critical moments or triggers that lead to changes in trust and affiliation (i.e., who the agent works for) when an agent or robot interacts with an older adult and their surroundings to design more trustworthy agents/robots for successful long-term support.

Nature of Student Involvement: Student research assistants will aid researchers in designing and executing studies to understand the needs and challenges that older adults and their informal caregivers face when making care coordination plans and how they adapt to changes. This will take a retrospective approach, interviewing stakeholders and reviewing their communication logs, calendars, and other coordination artifacts to reconstruct how they accomplished various care tasks. Student researchers will also conduct field study to discover triggers of trust and affiliation changes to understand what information an AI agent and robot need in order to learn about the changes in trust and affiliation.

  • Fieldwork including observations, interviews, and directed storytelling
  • Brainstorming
  • Design of conversational interfaces
  • Understanding of social psychology: social interaction, trust, affiliation
  • Design and execution of user studies

Project #7 Chemistry Tutor Machine Learning Programmer

Mentor: Bruce McLaren , faculty

Description: Learn about intelligent tutoring systems and how to apply machine learning to them! You will be responsible for the development of machine learned detectors designed to identify specific student behaviors for the Stoich Tutor ( https://stoichtutor.andrew.cmu.edu/ ). You will first complete work on the development of a detector for “gaming the system” and then move on to additional detectors. You will work with the research team that is investigating the link between behavioral, cognitive, and affective aspects of students and their engagement with the Stoich Tutor. You should have a computer science background with skills in HTML5/CSS3/JavaScript, Python, and an optional background in chemistry and familiarity or interest in machine learning. You will work with Prof. Bruce McLaren and Research Programmers Hayden Stec and Leah Teffera, with Stec and Teffera as the primary mentors.

Nature of Student Involvement: Programming and using machine learning to develop detectors of student behavior

  • Computer Science background 
  • Skills in HTML5/CSS3/JavaScript 
  • Python is required 
  • Background in chemistry and familiarity or interest in machine learning are optional

Project #8 Chemistry Tutor Programmer and Data Scientist

Description: Learn about intelligent tutoring systems and data science! You will be responsible for extending the Stoich Tutor ( https://stoichtutor.andrew.cmu.edu/ ) and its associated grading script. The specific way in which the tutor and grading script will be extended will be determined by results from a study conducted during 2023-2024. Additionally, you will analyze data from prior studies to guide extensions to the tutor as well as assist in the overall project, in which the research team is investigating the link between behavioral, cognitive, and affective aspects of students and their engagement with the tutor. You should have a computer science background with skills in HTML5/CSS3/JavaScript, Python, and an optional background in chemistry. You will work with Prof. Bruce McLaren and Research Programmers Hayden Stec and Leah Teffera, with Stec and Teffera as the primary mentors.

Nature of Student Involvement: The student will program a tutor for chemistry as well as maintaining and extending a grading script that assesses log data from the program

  • A Computer Science background 
  • Skills in HTML5/CSS3/JavaScript
  • Python is required
  • A background in chemistry is optional but highly desirable.

Project #9 Cloud Administrator Intelligent Tutor Programmer

Description: In this project you will bring your knowledge of computer science and cloud computing to the task of building intelligent tutoring systems (ITSs) to help community college students learn about cloud computing. You will design and write code to develop intelligent tutoring systems that will be embedded in the SAIL Cloud Administrator course. The tutors will support local community college students in better understanding programming and computational thinking. You will learn about code repositories and good software engineering methodologies and practices. You should have a computer science background with skills in HTML5/CSS3/JavaScript, and an optional background in education (e.g. TA-ing a course) and familiarity or interest in cloud administration/computing. You will work with Prof. Bruce McLaren and Leah Teffera, with Teffera as the primary mentor.

Nature of Student Involvement: The student will develop intelligent tutors for an online Cloud Administrator course.

  • Must have a computer science background
  • Optional background in education (e.g. TA-ing a course)
  • Familiarity or interest in cloud administration/computing

Project #10 Codespec: a computer programming environment

Mentor: Carl Haynes-Magyar , Presidential Postdoctoral Fellow

Description: Despite the potential of Parsons problems, few environments offer a seamless transition between different problem types. Codespec supports learners in practicing how to solve a programming problem as a Pseudocode Parsons problem, a Parsons problem, a Faded Parsons problem, a fix-code problem, or a write-code problem. The goal of the project is to develop, evaluate, and implement algorithms for knowledge tracing, adaptive problem-sequencing, and ready-to-publish results that include learning curve analysis.

Nature of Student Involvement: Write code to develop back-end features for Codespec.

Skills we are interested in (not all required): 

  • Experience or interest in computing education research, tools and environments.
  • Experience with data science, learning analytics, student modeling, large language models.
  • Preferred: CS (or other technical) major, HTML/CSS/JavaScript, Python, Django, VueJS, Figma skills.

Project #11 Computational Understanding of User Interfaces

Mentor: Jeffrey Bigham , faculty 

Description: The goal of our UI Understanding project is to build machine learning technologies that can learn to computationally understand and interact with user interfaces designed to be used by people. We have built technologies that understand graphical user interfaces from pixels, generate custom user interface code automatically, graphically reflow existing user interface to personalize them for specific abilities, and automate actions across different devices. Many of these projects target applications for people with disabilities who use user interfaces in ways other than those assumed by developers.

Nature of Student Involvement: Students will be involved in all aspects of research under the mentorship of senior graduate students and faculty -- including, defining project goals and scope, training or adapting large computer vision and natural language models, writing and presenting about results. Many of our past REU students have submitted their work to peer-reviewed venues and many have gone on to PhD programs in the area.

Skills we are interested in (not all required): Prefer students with familiarity with the following broad technical areas (will also get a chance to learn more during the REU!)

  • Experience training/fine-tuning modern machine learning pipelines (computer vision, language, multimodal)
  • Experience with one or more UI and interaction toolkit (e.g.., SwiftUI, React, others)
  • Familiarity with LLM APIs and best practices (e.g., GPT4, Claude, etc)
  • Knowledge of human-AI interaction, designing for ML systems, human-centered AI, etc.

Project #12 Designing algorithms for adaptive Extended Reality (XR)

Mentor: David Lindlbauer , faculty

Description: Extended Reality (XR) interfaces allow users to interact with the digital world anywhere and anytime. By embedding interfaces directly into users' environments, XR interfaces can both enhance productivity and be less distracting than traditional computing devices such as smartphones.

In this research, we aim to design algorithms that create context-aware XR interfaces, i.e., interfaces that automatically adjust when, where, and how to display XR interfaces. These algorithms can be optimization-based or learning-based, and form the backbone of XR systems that continuously adapt to users' needs and requirements when they interact with XR systems in a wide range of applications, from productivity, entertainment, manufacturing, or healthcare.

The research involves developing a novel algorithm for adaptive XR, and evaluating the approach in a comparative user study.

Nature of Student Involvement: Students will collaborate with other undergraduate and graduate students in creating the concept and planning of the research, and lead the implementation of the algorithm and the creation of the user study platform.

  • Strong programming skill (c# or similar)
  • Experience with Unity or Unreal
  • Interest in XR

Project #13 Designing for workers’ experiences of health & wellbeing

Mentor: Franchesca Spektor , graduate student advised by faculty Sarah Fox and Jodi Forlizzi

Description: Low wage workers are at increased risk for injury and disablement while on the job. However, traditional ways of understanding, tracking, and reporting occupational injury may be insufficient. While formal reporting requirements from OSHA may address a torn ACL, regulatory bodies provide few avenues for reporting on the repetitive chronic strain which results in injuries over time. This project aims to conduct participatory design research with local service workers in the Pittsburgh region – from custodial staff to home care workers – to learn if new tools and technologies may help bridge the gap between health & safety policies and workers’ needs on the ground. We will explore training needs, threat of retaliation, administrative barriers to reporting, and health data governance.

Nature of Student Involvement: The REU students will be closely involved in the project, focusing specifically on understanding the health & safety needs of a local service context. The students will be responsible for conducting a literature review and may have the chance to:

  • Conduct interviews, diary studies, and workshops with local workers
  • Contribute to data analysis using thematic analysis
  • Develop design prototypes to support health & safety reporting, and worker wellbeing
  • The students should hold care and curiosity about worker wellbeing, workplace technologies, and labor issues
  • Programming and technical prototyping skills for web and mobile applications
  • Experience with user research, design thinking, and UX backgrounds
  • Prior experience reading academic literature and conducting literature reviews

Project #14 Designing Inclusive Collaboration Environments

Mentor: Laura Dabbish , faculty 

Description: Open source software is important to sustaining the world’s infrastructure, and millions of volunteers help maintain it. However, growing evidence shows that people of different genders, particularly women, face particular barriers when contributing to open source software. Our research interviews people of diverse genders who have made significant open source contributions to understand how they became highly involved in open source, the barriers they face, and how they overcome them. We will also perform statistical analysis using data science on GitHub trace data to understand the extent to which our findings generalize, and the wider effects of barriers we uncover. Finally we are exploring interventions for enhancing inclusion in open collaboration environments.

Nature of Student Involvement: Students on this project will help us develop web based interventions for encouraging inclusive open source project collaboration environments, carry out interviews with open source contributors, and perform statistical analysis using data science on GitHub trace data.

  • Front end web programming and UX design skills would be helpful for this project
  • Strong organizational and interpersonal skills are important, other skills can be learned
  • Any of the following skills helpful: experience conducting interviews, experience with data science pipelines (eg, using python, SQL or R)

Project #15 Developing Novel Interfaces for Live Streaming

Mentor: Noor Hammad , graduate student advised by Jessica Hammer

Description: This project explores how to build live streaming interfaces that afford new capabilities to viewers, streamers, and game developers. We will use a system architecture built by the Centre for Transformational Play that enables the creation of “game-aware” overlays for any Unity game streamed on the Twitch platform. You will be working closely with an interdisciplinary team to improve the system, add new features, and provide technical support for research studies on Twitch.

Nature of Student Involvement: The student will be collaborating with the research team on activities such as weekly meetings, low-fidelity prototyping, study design, and pilot tests. They will be expected to complete software development tasks independently.

Skills we are interested in: 

  • Web development, particularly advanced JavaScript
  • Interest in live streaming and/or games
  • Prepared to use good collaborative software development practices (e.g. documentation, Git)
  • Some experience with Unity game development
  • Experience working with AWS or other cloud services.

Project #16 Digital Learning Game Programmer

Mentor: Bruce McLaren , faculty 

Description: Decimal Point and Ocean Adventure are learning games developed in the McLearn Lab at CMU to help late elementary and middle school students learn about decimals and decimal operations. For this project, you will write and revise code to alter and extend the two games to prepare them for new classroom studies. You will learn about code repositories, state-of-the-art software engineering methodology, and good software practices. You should have a computer science background with skills in HTML5/CSS3/JavaScript, and an optional background in mathematics or education (e.g. TA-ing a class). You will work with Prof. Bruce McLaren and Research Programmer Hayden Stec, with Stec as the primary mentor.

Nature of Student Involvement: The student will be involved in design, development, testing, and revising of code for digital learning games.

  • HTML5/CSS3/JavaScript
  • optional background in mathematics or education (e.g. TA-ing a class)

Project #17 Digital Learning Games Quality Assurance Programmer

Description: Decimal Point and Ocean Adventure are learning games developed in the McLearn Lab at CMU to help late elementary and middle school students learn about decimals and decimal operations, while Angle Jungle is a learning game to help middle school students learn about angles. For this position you will perform software quality assurance engineering to improve all of the McLearn Lab game materials — various decimal/angle tests, surveys, and three learning games (Decimal Point, Ocean Adventure, Angle Jungle) — testing the materials on all of the devices used in schools — an Apple laptop, an iPad and a ChromeBook -- and address any bugs that you found or have been previously reported. You will learn about code repositories, state-of-the-art software engineering and quality assurance methodology, and good software practices. You should have a computer science background with skills in HTML5/CSS3/JavaScript. You will work with Prof. Bruce McLaren and Research Programmer Hayden Stec, with Stec as the primary mentor.

Nature of Student Involvement: The student will be involved in design, development, testing, and revising of code for digital learning games

  • Computer science background 
  • An interest in mathematics education is also valuable.

Project #18 Evaluate Impact of Transparency in Ride-Sharing Algorithm

Mentor: Seyun Kim , graduate student advised by faculty Motahhare Eslami and Haiyi Zhu

Description: Gig economy platforms such as Uber or Lyft use algorithmic decision-making that are blackbox and lack transparency in its decision making to users of the system including drivers. A way to evaluate and test the algorithm’s impact and output is to conduct algorithmic auditing. For this project, we develop an intervention to assess the impact of whether transparency of an algorithm’s decision-making process influences perceptions of equity. We will also assess what type of information to the users would be considered as more impactful.

Nature of Student Involvement: The students will be responsible for building an intervention in the form of a software interface that engages with gig economy workers. The software interface will be an additional add-on feature to an existing platform (project) with a research group at another institute. The student will be responsible for data collection and quantitative, qualitative data analysis to understand the impact of the intervention. The data collection will involve engaging with participants in the wild.

  • Experience in software development (front end and back end) 
  • Running experiments in the real-world (data collection in the wild) 
  • Statistical analysis (quantitative analysis). The student does not necessarily need to have qualitative analysis experience.

Project #19 Human-Centered Data Science and Visualization

Mentor: Adam Perer , faculty 

Description: The Data Interaction Group (DIG) has a mission to empower everyone to analyze and communicate data with interactive systems. Our group conducts research in computer science at the intersection of human-computer interaction, machine learning, data science, programming languages, and data management.

This summer, we plan to build new tools for data scientists to help them better understand their data, which will hopefully result in better downstream machine-learning models derived from the data.

Nature of Student Involvement: Research, coding, user studies

  • Programming experience
  • Interest in data science and machine learning
  • Web development skills

Project #20 Mixed-reality AI STEM Learning

Mentor: Nesra Yannier , senior systems scientist 

Description: This project focuses on developing a mixed-reality educational system and Intelligent Science Stations bridging physical and virtual worlds to improve children's STEM learning and enjoyment in a collaborative way. It uses depth camera sensing and computer vision to detect physical objects and provide personalized immediate feedback to children as they experiment and make discoveries in their physical environment. NoRILLA Intelligent Science Stations ( www.norilla.org ) are being used in many school districts, after school programs, children's museums and science centers (e.g., Carnegie Science Center, Children's Museum of Atlanta, Please Touch Museum, CaixaForum AI Museum in Spain). Research with hundreds of children has shown that it improves children's learning by 5 times compared to equivalent tablet or computer games. This REU project will focus on extending Intelligent Science Stations to different content areas, creating new modules and curriculum, designing new games and interfaces as well as collecting and analyzing data in schools and museums of children interacting with Intelligent Science Stations and Exhibits.

Nature of Student Involvement: The student will work closely with the project lead and will be involved in different aspects of the project including design, development and research. The student will help take the project further by developing new modules/games, computer vision algorithms/tools and AI enhancements on the platform and deployment of upcoming installations.

  • Familiarity with software and hardware components
  • Familiarity with computer vision, interface development, Java/Processing, robotics and/or game design is a plus

Project #21 Scrolling Technique Library

Mentor: Brad Myers , faculty and HCII Director

Description: We have developed a new way to test how well a scrolling technique works, and we need to re-implement some older techniques to see how they compare. For example, the original Macintosh scrollbars from 1984 had arrows at the top and bottom, and a draggable indicator in the middle. Even earlier scrollbars worked entirely differently. I am hoping to recruit one good programmer to help recreate some old scrolling techniques, and possibly try out some brand new ones, like for Virtual Reality applications, to test how well they do compared to regular scrolling techniques like two-fingers on a touchpad or smartphone screen. If there is time, the project will include running user tests on the implemented techniques, and writing a CHI paper based in part on the results.

Nature of Student Involvement: The student on this project will be implementing all of the techniques as web applications.

  • The student on this project must be an excellent programmer JavaScript or TypeScript
  • Preferably with expertise in React or other web framework. 
  • Experience with running user studies would be a plus.

Project #22 Studying Novel Live Streaming Interfaces

Description: This project explores how people use live streaming interfaces to support shared attention in streamed experiences, including entertainment games and educational content. As part of this work, we will use novel live streaming “game-aware” interfaces developed by the Center for Transformational Play that allow viewers to customize their live streaming experience. You will be working closely with an interdisciplinary team to develop and execute studies into how viewers make use of these interfaces to support their streaming experiences.

Nature of Student Involvement: This student will collaborate with the research team on activities such as weekly meetings, participant recruitment, data collection, and data analysis. They will be expected to complete problem solving and logistical tasks independently.

Skills we are interested in:

  • Comfortable with independent work
  • Interest in mixed methods research
  • Good organizational skills
  • Experience with mixed research methods

Project #23 Supporting Designers in Learning to Co-create with AI for Complex Computational Design Tasks

Mentor: Nikolas Martelaro , faculty 

Description: Advancements in generative AI (GenAI) are rapidly disrupting creative professionals' work across a range of domains. To ensure that GenAI benefits creative professionals, rather than devaluing their labor, it is critical that we prepare the workforce to work with these technologies to effectively leverage their comparative advantages as humans. However, recent studies indicate that creative professionals face significant challenges in adopting GenAI successfully into their workflows. In this project, we will explore novel interactive interfaces and interaction patterns that allow professional designers to work more effectively with GenAI tools across different domains. First, we will iteratively build interactive prototypes and then evaluate their effectiveness through user studies. The results of this work will contribute to advancing future AI-augmented creative work.

Nature of Student Involvement: Attending weekly research meetings, supporting prototyping, and supporting preparation and facilitation of user studies

  • Programming
  • User research

Project #24 Supporting End-users in Auditing Harmful Algorithmic Behaviors in Generative AI

Mentor: Wesley Deng , graduate student advised by faculty Motahhare Eslami and Ken Holstein

Description: Despite impressive capabilities, text-to-image (TTI) generative AI also carries risks of biases and discrimination. Traditional algorithm audits done by small groups of AI experts often miss harmful biases due to the AI team's cultural blind spots and the difficulty of predicting the range of ways TTI systems will be used once deployed widely. Recent works from our research group have highlighted the effectiveness of end users in detecting biases overlooked by experts, demonstrating the value of engaging end users in algorithmic audits. Despite this potential, there is a lack of structured support and tools for public participation in auditing generative AI. In this project, you will build upon an existing interface ( https://taiga.weaudit.org/ ) we developed to further design, develop, and evaluate new tools and mechanisms to better support end users in auditing and red teaming Stable Diffusion, an open source TTI model. Overall, this project aims to empower end users in the auditing process and enhance public involvement in creating a responsible and ethical generative AI landscape.

Nature of Student Involvement: Research assistants (RAs) will work closely with the research team and will be involved in the design, development, and evaluation of the system. This means the RA will get exposure to project ideation, rapid prototyping, front end web development (using Javascript/HTML/CSS/other web technologies), and conducting user evaluations.

  • Experience in software development, and in particular the ability to learn new technologies
  • Experience with web technologies such as JavaScript is preferred
  • Experience in designing and conducting user studies evaluating interactive systems is preferred
  • Familiarity with text-to-image generative AI (DALL-E, Stable Diffusion) is encouraged
  • Interests in exploring topics such as Responsible AI, Human-AI Interaction, Algorithmic Fairness and Transparency

Project #25 Supporting middle school math homework with novel parent support tools

Mentor: Conrad Borchers , graduate student advised by Vincent Aleven and Ken Koedinger

Description: This project aims to design, implement, and test AI-based support tools that provide tailored recommendations to parents for how they might support their children's homework. The student will engage in high-fidelity prototyping and design research, studying parental engagement and student learning during interactions with the tool. The research output will contribute new scientific understanding of how cognitive and socio-emotional support can be merged productively. Prior work has identified that differences in parent styles during homework support relate to achievement gaps. Therefore, one potential research question is how to design interactive systems powered by AI that help parents and students adopt more favorable attitudes and approaches to homework.

The research extends prior project activities in the context of a grant on smart middle school mathematics homework support. We have conducted prototyping sessions with several students and their parents, identifying key needs for more effective and equitable homework support. We are also planning to pilot an initial prototype of the tool in late November. Therefore, the REU intern will contribute to design research activities at a stage of high fidelity.

Nature of Student Involvement: The REU intern will be tasked with conducting in-depth interview sessions and interactive usability studies with parents and children to refine the tool's design, including potential involvement in programming.

  • Required: Demonstrated track record of conducting high-fidelity prototyping, usability testing, and user experience research, ideally in close collaboration with software engineers
  • Desirable but not required: Experience in deploying machine learning applications in a web application, including experience with frontend engineering; experience with learning technologies

Project #26 Supporting Upper Extremity Health Monitoring and Management for Wheelchair Users

Mentor: Patrick Carrington , faculty

Description: Upper extremity (UE) health issues are a common concern among wheelchair users and have a large impact on their independence, social participation, and quality of life. However, despite the well-documented prevalence and negative impacts, these issues remain unresolved. Existing solutions (e.g. surgical repair, conservative treatments) often fail to promote sustained UE health improvement in wheelchair users’ day-to-day lives. In this project, we explore how health tracking technologies could support wheelchair users’ UE health self-care, including movement sensing, modeling body mechanics, and developing appropriate user interfaces for feedback and data analysis.

Nature of Student Involvement: The student will be involved in development, prototyping, and/or user studies.

Skills we are interested in (not all required): Candidates should ideally have experience programming, some experience with machine learning is helpful, experience with hardware and specifically IMUs is also positive.

Project #27 Tangible Privacy & Security

Description: This project aims to address the persistent challenges of human error and negligence in cybersecurity and privacy by leveraging tangible computing. Building upon our lab's previous research - Spidey Sense, Bit Whisperer, and Smart Webcam Cover, we aim to overcome barriers related to awareness, ability, and motivation among end-users. Through the strategic introduction of tangible computing, our goal is to empower users with greater control and an enhanced understanding of privacy-invasive sensors in the physical world, thereby fostering proactive engagement in security and privacy practices. In pursuit of these goals, we are exploring two key ideas: 1) the development of a tangible control for privacy preferences in shared spaces, especially in large environments such as buildings or city-wide spaces, and 2) the creation of privacy-invasive sensors that provide clear indications of the data being captured and the range of data being collected—such as a webcam that visually communicates its field of view in the real world.

Nature of Student Involvement: Student will be involved in Ideation, Prototyping and Conducting Interviews.

  • Hardware prototyping skills
  • Conducting interviews and analyzing response data
  • Programming skills

Project #28 Technologies for Training Everyday Mindfulness and Emotional Regulation

Mentor: Anna Fang , graduate student advised by Haiyi Zhu

Description: Practices like mindfulness and meditation that help people feel present without judgment and for reducing stress have become emerging topics of interest in HCI research. Technologies for improving people’s ability to be self-aware, emotionally self-regulate, or self-transcend often ask users to imagine themselves in environments like a quiet forest or watching the calm ocean waves, meant to feel separate and isolated from their everyday lives. However, the primary goal of practices is actually for people to generalize these skills to their day-to-day, in which most people do not usually live in these natural environments, silent atmospheres, or sitting in meditation postures.

As a result, in this project, we will be exploring a novel technological space for supporting practice of self-care skills in daily environments. We will not only explore and design for people’s needs, but also build and evaluate HCI technology (e.g. immersive technologies like VR or mixed reality, wearable devices, social computing systems) for practicing things like mindfulness, calm breathing, lowering anxiety and stress, or other self-regulation techniques. Our goal is to help people be better prepared for mental and emotional regulation when challenges arise.

Nature of Student Involvement: The student will work closely with the project leads. Students may participate in coding/development, organizing and carrying out interviews or other evaluation techniques for the project, organizing and analyzing findings, etc. Students will get a breadth of experience, such as learning things from need-finding to system building to paper writing. We welcome students to contribute their own ideas and feel ownership over guiding this project along with the faculty and student advisors!

  • Experience in programming or software development (e.g. Python, Java)
  • Experience or interest in interviewing or conducting user studies
  • Interest in developing for or applying artificial intelligence, VR/AR technologies, wearables, or other technical HCI
  • Passion and excitement about novel technologies for mental health!

Summer Undergraduate Research Program

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  • Your Summer at a Glance

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CSCI 2300: Human-Computer Interaction Seminar

Spring 2023

This seminar covers methods for conducting research in human-computer interaction (HCI). These topics will be pursued through independent reading, assignments, and class discussion. The seminar comprises four assignments that not just apply HCI research methods but push the envelope of what has been done before. The assignments are designed to be meaningful and potentially discover something new in the field, and students will also attend HCI faculty candidate talks this semester as part of this course. We will have readings that teach HCI methods and provide examples of research contributions, sometimes alongside the reviews of those papers as they were evaluated for publication. The goal of this course is to provide students with the background necessary to perform research in HCI and the skills required to conduct human-centric research. Students who take this course should have a particular interest in HCI research, or wish to learn fundamental skills that will help them with a user interface design or usability evaluation career. There will be little or no content in this course about interface design, but students will find other topics in CSCI 1300 (User Interfaces) relevant. Enthusiastic students who have not taken CSCI 1300 should have independently gained HCI experience or be a graduate student studying a related topic, and be able to manipulate software and data to investigate the research questions posed in class. The course is capped at about 20 students, and there is no waitlist or addition enrollment possible at this point. The Collaboration Policy should be read and signed in class on February 8.

Main Themes (Spring 2023)

1) HCI methods, especially empirical experimental design 2) social mechanisms in digital communication 3) self-experimentation 4) AI and crowdwork ethics 5) creatively learning and learning creativity

Course Staff

Instructor: Jeff Huang , 245 CIT, jeff at cs dot brown dot edu

Meeting Times

4:30pm-7pm Wednesday at 241 CIT. Office hours on Wed 2:30-3:30pm. The seminar is fully in-person, without a remote option.

Assignments

Evaluating (S)ocial Mechanisms Compare and contrast fast-prototyped social apps that we design together that each apply different norms and constraints using a variety of mechanisms to see how small changes affect wellness, trust, privacy, and enjoyment.

Self-E(x)periment Designs : Rather than conducting generalizable experiments on samples of the population, you will perform an N = 1 experiment (a self-experiment) to see how changing your behavior affects your own outcomes

Constructing an (E)thical Framework : What should modern human subjects review look like for computing studies? Propose a change to the federal "common rule" from which institutional review boards derive their rules, to consider modern perspectives of labor, data ownership, power dynamics, and the risks of deanonymization.

Measuring (C)reativity : We'll be reviewing measures of creativity and inspiration that's typically used for human-generated content, and seeing how they perform on AI-generated content. What is creativity, and is there something there that's unique to humans?

  • 15 points - Readings
  • 13 points - HCI faculty candidate talks
  • 18 points - Evaluating Social Mechanisms assignment
  • 18 points - Self-Experiment Designs assignment
  • 18 points - Constructing an Ethical Framework assignment
  • 18 points - Measuring Creativity assignment

Readings should be done before class on the date a reading is due. For each reading, please write to the Slack channel a short novel comment (not a rephrase of what someone said earlier) about the research contribution/findings from the work, and a short novel comment about your assessment of the work/paper. Comments are encouraged to be in response to existing comments in the channel. Additionally, each reading discussion will be led by two students who will work together to prepare a presentation for the class.

Assignments are due at the beginning of class on the date it is marked "in" in the schedule below, with a midpoint check-in on the dates marked "mid" where we'll discuss progress so far. Students should attend at least 4 faculty candidate talks and submit a combined review of their research quality and potential, with a final comparison between the HCI research work and visions that were presented by each faculty candidate.

Grading is done solely by the instructor. The thresholds for A/B/C cutoffs are 90/80/70.

Time Allocation

Total time spent in and out of class for this course is estimated at 180 hours. Over the 15 weeks of this course, students will spend 2 and a half hours in class each week (or 37.5 hours total). Although specific out-of-class time investments may vary for individual students, a reasonable estimate to support this course's learning outcomes is 145 total out-of class hours, or on average, about 10 hours weekly over a 15-week term. Out-of-class preparation will regularly include about 1-2 hours per class of reading and writing the comments addressing the reading (about 70 hours total), along with presentations. In addition to this ongoing preparation time, students are expected to allocate about 65 hours over the course of the term to writing the four assignments. Finally, approximately 5 hours will be spent attending HCI faculty candidate talks.

Accessibility and Accommodations Statement

Brown University is committed to full inclusion of all students. Please inform me early in the term if you may require accommodations or modification of any of course procedures. You may speak with me after class, during office hours, or by appointment. If you need accommodations around online learning or in classroom accommodations, please be sure to reach out to Student Accessibility Services (SAS) for their assistance ([email protected], 401-863-9588). Undergraduates in need of short-term academic advice or support can contact an academic dean in the College by emailing [email protected]. Graduate students may contact one of the deans in the Graduate School by emailing [email protected].

Classwork Schedule

* We will look at the corresponding reviews for some of these papers in class to see what the original reviewers had to say about it.

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As part of HCI's research process, we invite our members to participate in surveys and provide input on the broad range of issues and concerns they face daily. All strategic talent management professionals are welcome to join HCI's Survey Panel. As a panelist, you will have the opportunity to share your voice and be part of our unique research reports. 

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Women in AI: Krystal Kauffman, research fellow at the Distributed AI Research Institute

hci research work

To give AI-focused women academics and others their well-deserved — and overdue — time in the spotlight, TechCrunch is launching a series of interviews focusing on remarkable women who’ve contributed to the AI revolution. We’ll publish several pieces throughout the year as the AI boom continues, highlighting key work that often goes unrecognized. Read more profiles here .

Krystal Kauffman worked as an organizer on political and issue campaigns for a decade before pursuing a degree in geology. Then, she turned to gig work, which lead her to Turkopticon, a nonprofit organization dedicated to fighting for the rights of gig workers — specifically those using Amazon’s Mechanical Turk (AMT) platform.

Now the lead organizer at Turkopticon, Kauffman recently started as a research fellow with the Distributed AI Research Institute (DAIR) Institute, working alongside others to build — in her words — “a community of workers united in righting the wrongs of the big-tech marketplace platforms.”

Briefly, how did you get your start in AI ? What attracted you to the field?

In 2015, I became ill, and couldn’t work outside of my home. While doctors were trying to sort things out, I found the AMT platform. For the next two years, I was able to support myself doing data work in which I completed tasks that helped program AI , build LLMs and so on. During my time working on AMT, I became very passionate about solving issues with the platform and taking on the ethics of data work in general.

What work are you most proud of ( in the AI field)?

When I first started data work nine years ago, very few people knew that there was a global workforce quietly programming smart devices, developing AI and building datasets from their homes. Over the last several years, I’ve spoken out about this workforce and the ethical challenges that come with data work through interviews, conference panels, articles, forums, aiding legislators, speaking engagements, workshops and social media. It’s an honor to be in a position in which I can help educate the general public, congressional leaders and labor advocates about this workforce and all that comes with it.

How do you navigate the challenges of the male-dominated tech industry, and, by extension, the male-dominated AI industry?

I consider myself very fortunate because I have a great support system that includes my colleagues and mentors. I choose to surround myself with people who want to see female and non-binary folks succeed. My mentors are women and I also seek advice from supportive men. One thing that has to continue, however, is speaking up about inequity and moving the conversation forward to change it.

What advice would you give to women seeking to enter the AI field?

I would tell any woman wanting to enter the AI field to go for it! Finding a good mentor or mentors is so important. Look to the many strong women and non-binary folks in the field for guidance when needed. Forge relationships with supportive men. Lastly, don’t be afraid to speak up. Great ideas come from confronting some of the hardest questions!

What are some of the most pressing issues facing AI as it evolves?

One of the most pressing issues facing the evolution of AI is accessibility. Who has access to the tools? Who’s providing the data and maintaining the system? Who’s benefiting from AI ? What populations are being left behind and how do we change that? How are the workers behind the system being treated?

The other issue I would raise here would be bias. How do we create systems completely free from bias?

What are some issues AI users should be aware of?

I would always tell users to look at how the workers training AI are being treated. That’s an indicator of so many things.

What is the best way to responsibly build AI?

It’s imperative that we involve underrepresented populations in the creation of AI . The people who will be impacted by the tech should always have a seat at the table. Similarly, the creation of AI legislation has to involve data workers. They are the foundation of these systems and to have the discussion without them would be irresponsible.

How can investors better push for responsible AI ?

I will just say what I have been saying: Nothing is set in stone. We do not have to accept what is being presented to us. The only way things improve is to speak up and act. Look for other organizations pushing for responsible AI . Challenge working conditions, challenge implementation, usage, etc. Challenge anything that feels unfair or irresponsible.

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Stanford Medicine study identifies distinct brain organization patterns in women and men

Stanford Medicine researchers have developed a powerful new artificial intelligence model that can distinguish between male and female brains.

February 20, 2024

sex differences in brain

'A key motivation for this study is that sex plays a crucial role in human brain development, in aging, and in the manifestation of psychiatric and neurological disorders,' said Vinod Menon. clelia-clelia

A new study by Stanford Medicine investigators unveils a new artificial intelligence model that was more than 90% successful at determining whether scans of brain activity came from a woman or a man.

The findings, published Feb. 20 in the Proceedings of the National Academy of Sciences, help resolve a long-term controversy about whether reliable sex differences exist in the human brain and suggest that understanding these differences may be critical to addressing neuropsychiatric conditions that affect women and men differently.

“A key motivation for this study is that sex plays a crucial role in human brain development, in aging, and in the manifestation of psychiatric and neurological disorders,” said Vinod Menon , PhD, professor of psychiatry and behavioral sciences and director of the Stanford Cognitive and Systems Neuroscience Laboratory . “Identifying consistent and replicable sex differences in the healthy adult brain is a critical step toward a deeper understanding of sex-specific vulnerabilities in psychiatric and neurological disorders.”

Menon is the study’s senior author. The lead authors are senior research scientist Srikanth Ryali , PhD, and academic staff researcher Yuan Zhang , PhD.

“Hotspots” that most helped the model distinguish male brains from female ones include the default mode network, a brain system that helps us process self-referential information, and the striatum and limbic network, which are involved in learning and how we respond to rewards.

The investigators noted that this work does not weigh in on whether sex-related differences arise early in life or may be driven by hormonal differences or the different societal circumstances that men and women may be more likely to encounter.

Uncovering brain differences

The extent to which a person’s sex affects how their brain is organized and operates has long been a point of dispute among scientists. While we know the sex chromosomes we are born with help determine the cocktail of hormones our brains are exposed to — particularly during early development, puberty and aging — researchers have long struggled to connect sex to concrete differences in the human brain. Brain structures tend to look much the same in men and women, and previous research examining how brain regions work together has also largely failed to turn up consistent brain indicators of sex.

test

Vinod Menon

In their current study, Menon and his team took advantage of recent advances in artificial intelligence, as well as access to multiple large datasets, to pursue a more powerful analysis than has previously been employed. First, they created a deep neural network model, which learns to classify brain imaging data: As the researchers showed brain scans to the model and told it that it was looking at a male or female brain, the model started to “notice” what subtle patterns could help it tell the difference.

This model demonstrated superior performance compared with those in previous studies, in part because it used a deep neural network that analyzes dynamic MRI scans. This approach captures the intricate interplay among different brain regions. When the researchers tested the model on around 1,500 brain scans, it could almost always tell if the scan came from a woman or a man.

The model’s success suggests that detectable sex differences do exist in the brain but just haven’t been picked up reliably before. The fact that it worked so well in different datasets, including brain scans from multiple sites in the U.S. and Europe, make the findings especially convincing as it controls for many confounds that can plague studies of this kind.

“This is a very strong piece of evidence that sex is a robust determinant of human brain organization,” Menon said.

Making predictions

Until recently, a model like the one Menon’s team employed would help researchers sort brains into different groups but wouldn’t provide information about how the sorting happened. Today, however, researchers have access to a tool called “explainable AI,” which can sift through vast amounts of data to explain how a model’s decisions are made.

Using explainable AI, Menon and his team identified the brain networks that were most important to the model’s judgment of whether a brain scan came from a man or a woman. They found the model was most often looking to the default mode network, striatum, and the limbic network to make the call.

The team then wondered if they could create another model that could predict how well participants would do on certain cognitive tasks based on functional brain features that differ between women and men. They developed sex-specific models of cognitive abilities: One model effectively predicted cognitive performance in men but not women, and another in women but not men. The findings indicate that functional brain characteristics varying between sexes have significant behavioral implications.

“These models worked really well because we successfully separated brain patterns between sexes,” Menon said. “That tells me that overlooking sex differences in brain organization could lead us to miss key factors underlying neuropsychiatric disorders.”

While the team applied their deep neural network model to questions about sex differences, Menon says the model can be applied to answer questions regarding how just about any aspect of brain connectivity might relate to any kind of cognitive ability or behavior. He and his team plan to make their model publicly available for any researcher to use.

“Our AI models have very broad applicability,” Menon said. “A researcher could use our models to look for brain differences linked to learning impairments or social functioning differences, for instance — aspects we are keen to understand better to aid individuals in adapting to and surmounting these challenges.”

The research was sponsored by the National Institutes of Health (grants MH084164, EB022907, MH121069, K25HD074652 and AG072114), the Transdisciplinary Initiative, the Uytengsu-Hamilton 22q11 Programs, the Stanford Maternal and Child Health Research Institute, and the NARSAD Young Investigator Award.

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Research grant aimed at improving wastewater monitoring for diseases in rural Appalachian communities

  • Kevin Myatt

15 Feb 2024

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Two people testing water in rural Appalachia.

Testing wastewater to assess the spread of the COVID-19 virus became common and well-publicized during the pandemic, but it has been focused mostly on urban areas.

The Appalachian Regional Commission (ARC) has awarded $400,000 to Virginia Tech, with an additional $50,000 to Virginia Tech from the Virginia Department of Health, for a two-year project to identify and implement improved and new methods to detect pathogens for multiple diseases in the wastewater of rural communities.

“My work and research have primarily been focused on rural areas, and prior to the pandemic, most of my research was on drinking water and health-related challenges,” said Alasdair Cohen , assistant professor of environmental epidemiology in the Department of Population Health Sciences at the Virginia-Maryland College of Veterinary Medicine . 

Cohen is the principal investigator on this new project that will build on research Cohen’s team has been conducting since 2022 in collaboration with a wastewater utility in Southwest Virginia and led by Amanda Darling, a Ph.D. student in Cohen’s group. 

“Dr. Cohen does important work on drinking water and health, locally and globally,” said Laura Hungerford , head of the Department of Population Health Sciences . “During COVID, he jumped in to help develop improved methods for wastewater surveillance. This let the university and Virginia better track and manage diseases. With ARC funding, he and his community partners will bring this science to benefit rural communities.”

Early in the pandemic, Virginia Tech researchers in the College of Engineering began testing campus wastewater for COVID-19 . Cohen was part of this team and led the statistical analyses of the data, finding that they were able to predict future COVID-19 cases at scales as small as one residence hall. The team published its findings in the journal Environmental Science and Technology Water , and this campuswide research collaboration also piqued Cohen’s interest in the use of wastewater surveillance in rural settings. 

He is joined in the ARC grant by two co-investigators from the Charles E. Via, Jr. Department of Civil and Environmental Engineering in the College of Engineering : Amy Pruden , University Distinguished Professor in Civil and Environmental Engineering, and Peter Vikesland , the Nick Prillaman Professor in civil and environmental engineering, as well as Leigh-Anne Krometis , associate professor of biological systems engineering in the College of Agriculture and Life Sciences .

Concurrent with the grant funding, Cohen’s team recently published “Making Waves: The Benefits and Challenges of Responsibly Implementing Wastewater-based Surveillance for Rural Communities” in the journal Water Research. The article calls attention to the potential public health benefits of wastewater surveillance for rural communities and to methodological and ethical challenges that Cohen and his colleagues are working to address.

“ARC’s grant of $400,000 will help Virginia Tech expand their work to detect pathogens in wastewater from rural communities,” U.S Rep. Morgan Griffith said in a press release announcing the grant. “This work is aimed at improving our country’s public health through better community health monitoring and outbreak forecasting.” 

The Virginia Department of Health (VDH) monitors wastewater at sites across the commonwealth for pathogens causing COVID-19, influenza A, influenza B, hepatitis A and respiratory syncytial virus. The department found though that results from some smaller rural communities are challenging to interpret. 

“This project aims to complement VDH's efforts in using wastewater-based surveillance to advance public health in rural towns in Appalachian Virginia,” said Rekha Singh, the department's Wastewater Surveillance Program manager. “The VDH has initiated wastewater surveillance for COVID-19 in communities statewide since September 2021. This new project will help identify the best practices for sampling in small communities and will assist VDH in implementing effective wastewater surveillance in similar communities.”

Infrastructure is often part of the challenge in testing rural wastewater, Cohen said. 

“You have fewer people but over a larger space, so you have more wastewater collection infrastructure per person than you would in an urban setting,” Cohen said. “Many rural towns, and especially older rural towns, are going to have sewage collection infrastructure with a lot of breaks and cracks in the pipes. That means sewage could get out into the ground and it means water can get into the pipes.”

Especially after periods of heavier rain, runoff seeping into sewage systems could dilute the results of wastewater testing in rural areas. It can also mean tax dollars down the drain with sewage plants treating rainwater alongside wastewater.

“We have enough preliminary data from our pilot research to show that this can be a problem,” Cohen said.

The grant will allow Cohen’s team to take on wastewater surveillance in new Southwest Virginia communities, gaining efficiency as experiences from prior studies are applied.

“The goal is we want to try to develop an approach so that rural utilities and public health agencies can determine if wastewater surveillance is something that makes sense for a given rural community,” Cohen said. “And if so, how could it best be implemented?”

Andrew Mann

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Weekly Research Update: Thursday, February 22, 2024

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The second annual Research Core Fair is three weeks away!

The University of South Carolina is hosting a Research Core Fair on Friday, March 15, 2024, to spotlight the wealth of resources at the University that are available to researchers. The Research Core Fair is open to all USC students, faculty and staff. New schedule updates and talk titles are available on our website now. Students and postdocs who wish to present a poster at the fair should submit their abstract by Friday, March 1, 2024. We encourage USC graduate and professional students, Principal Investigators, and those from other institutions who are interested in learning more about the USC Research Cores to register for the fair by March 8, 2024.

Reviewers needed for Discover USC 2024

This year, Discover USC will be held on Friday, April 19, 2024, at the Columbia Metropolitan Convention Center. It is not too late to get involved! Organizers are still seeking eligible participants to serve as reviewers, please register here by Friday, March 22 to be a reviewer. Reviewers must be employed by USC/Prisma Health as a faculty member, staff member or postdoc, enrolled in a graduate degree program at USC, and/or a USC alum. Registration is open for presenters until Friday, March 1.

ASPIRE program seeks 2024 faculty research proposals

The Office of the Vice President for Research is pleased to announce a 2024 ASPIRE funding program request for proposals (RFP). Visit our website for complete details about applying for ASPIRE . ASPIRE 2024 applications are due via USCeRA before 5:00 p.m., on Thursday, April 4, 2024. For questions about ASPIRE, please contact Beth Herron or Julie Morris with the Research and Grant Development Office, [email protected] or [email protected] .

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22 February 2024

Challenge the conventional. Create the exceptional. No Limits.

Four-day week made permanent for most UK firms in world’s biggest trial

Research shows 51% that took part permanently adopted the change, while 89% still operating policy one year on

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Most of the UK companies that took part in the world’s biggest ever four-day working week trial have made the policy permanent, research shows.

Of the 61 organisations that took part in a six-month UK pilot in 2022, 54 (89%) are still operating the policy a year later, and 31 (51%) have made the change permanent.

More than half (55%) of project managers and CEOs said a four-day week – in which staff worked 100% of their output in 80% of their time – had a positive impact on their organisation, the report found.

For 82% this included positive effects on staff wellbeing, 50% found it reduced staff turnover, while 32% said it improved job recruitment. Nearly half (46%) said working and productivity improved.

The report’s author, Juliet Schor, professor of sociology at Boston College, said the results showed “real and long lasting” effects. “Physical and mental health, and work-life balance are significantly better than at six months. Burnout and life satisfaction improvements held steady,” she said.

But Matthew Percival, a director at the Confederation of British Industry, said the four-day week was not a “one size fits all answer” and would be “unlikely to pay for itself in many industries”.

He said: “If businesses have the budget to add to their offer to employees, then they will be considering the relative merits of reducing working hours compared to increasing pay, pensions or paid parental leave, as well as better supporting health and wellbeing.”

The four-day working week report, by the thinktank Autonomy and researchers from the University of Cambridge, the University of Salford and Boston College in the US, found that “many of the significant benefits found during the initial trial have persisted 12 months on”, although they noted that it was a small sample size.

Almost all (96%) of staff said their personal life had benefited, and 86% felt they performed better at work, while 38% felt their organisation had become more efficient, and 24% said it had helped with caring responsibilities.

Organisations reduced working hours by an average of 6.6 hours to reach a 31.6-hour week. Most gave their staff one full day off a week, either universal or staggered. The report found that protected days off were more effective than those on which staff were “on call” or sometimes expected to work.

The most successful companies made their four-day week “clear, confident and well-communicated”, and co-designed their policies between staff and management, thinking carefully about how to adapt work processes, the authors wrote.

Challenges encountered by some companies included working with clients and stakeholders where four-day weeks were not the norm, or where the policy was implemented unevenly, leading to resentment among some staff.

This month, the Scottish government launched a four-day working week trial for some public services. Autonomy is calling for the Westminster government to introduce policies that would enable its wider take-up, including giving workers the right to request a four-day week with no loss of pay, a public sector trial, and funding to support the shift in the private sector.

Paul Oliver, chief operating officer at Citizens Advice Gateshead, said that a four-day week helped his employees cope with a “demanding role”, and improved retention as the charity was unable to pay high salaries. “We wanted to see a way to improve staff conditions so they would be better rested and could give more to work,” he added.

The greater efficiency introduced by the pilot meant it exceeded its targets, including improving the quality of advice and the number of clients spoken to, expanding to a seven-day service thanks to greater flexibility, increasing profitability and reducing levels of staff sickness. “We’re breaking out of the nine to five model, which doesn’t work for our society or our clients,” Oliver said.

Mark Downs, chief executive of the Royal Society of Biology, said his organisation was keeping the policy – in which staff divvied up Mondays and Fridays off between them – because it had been positively received by staff and external partners.

One unexpected benefit he encountered was that days when he was working and most other staff were off were much more productive. He also felt it made RSB a more attractive employer, with applicants citing the four-day week as a draw.

Anthony Painter, director of policy at the Chartered Management Institute, said he was “following the four-day week trials with interest” since CMI research had shown that employees valued flexible working above all else, including pay rises.

He added that managers would need to be better trained to implement the changes. “They will need the very best managers in place to ensure that flexibility and productivity can be two sides of the same coin – better ways of working,” Painter said.

A government spokesperson said: “We have no plans to introduce a four-day working week. Ultimately it is for employers and employees to agree what working arrangements work best for them, and we will be making changes to our flexible working legislation in April, including the right to request flexible working from day 1 of a new job.”

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IMAGES

  1. 1: The Multidisciplinary Field of HCI, Human-Computer Interaction (HCI

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  5. An overview of HCI research that uses machine learning. (a) An

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COMMENTS

  1. What is Human-Computer Interaction (HCI)?

    Human-computer interaction (HCI) is a multidisciplinary field of study focusing on the design of computer technology and, in particular, the interaction between humans (the users) and computers. While initially concerned with computers, HCI has since expanded to cover almost all forms of information technology design. video transcript

  2. 1

    1 - Approaches and Frameworks for HCI Research Published online by Cambridge University Press: 24 February 2021 John Long Chapter Get access Cite Summary The chapter introduces human-computer Interaction (HCI) and HCI research and describes their current states.

  3. Human-Computer Interaction

    Human-Computer Interaction (HCI) is a rapidly expanding area of research and development that has transformed the way we use computers in the last thirty years. Research topics and areas include augmented-reality, collective action, computer-mediated communication, computer-supported collaborative work, crowdsourcing and social computing, cyberlearning and future learning technologies ...

  4. Human-Computer Interaction and Visualization

    Human-Computer Interaction and Visualization HCI researchers at Google have enormous potential to impact the experience of Google users as well as conduct innovative research. Grounded in user behavior understanding and real use, Google's HCI researchers invent, design, build and trial large-scale interactive systems in the real world.

  5. Human Computer Interaction

    From desktops and laptops to phones and tablets to virtual reality, wearable devices, the Internet of Things, and robotics, technologies based on computing are all around us. The field of human-computer interaction (HCI) studies how we interact with these technologies, and how those technologies in turn shape our world. HCI researchers seek to improve how humans interact with technology, to ...

  6. Research

    Our research includes innovation in user-interface software tools, studies of computer-supported cooperative work and tools to support it, gesture recognition, data visualization, intelligent agents, human-robot interaction, visual interface design, intelligent tutoring systems, cognitive models, and understanding and building platforms that max...

  7. PDF Research Methods for Human-Computer Interaction

    Library of Congress Cataloging-in-Publication data. Research methods for human-computer interaction / Edited by Paul Cairns and Anna L. Cox. p. cm. Includes bibliographical references and index. ISBN 978--521-87012-2 (hardback) 1. Human-computer interaction.

  8. CS376: Research Topics in Human-Computer Interaction

    This course is a broad graduate-level introduction to HCI research. The course begins with seminal work on interactive systems, and moves through current and future research areas in interaction techniques and the design, prototyping, and evaluation of user interfaces. Topics include computer-supported cooperative work; audio, speech, and ...

  9. PDF Approaches and Frameworks for HCI Research

    HCI is interpreted inclusively and is considered to comprise ease of use/usability, applied psychology, engi-neering, human-centred design, cognitive engineering, interaction design, user experience (UX) design, technical art, graphic design and digital interaction, along with others.

  10. Reflections on emerging HCI-AI research

    Human computer interaction (HCI) has grown into a mature field of research. With artificial intelligence (AI) finding ubiquitous applications, HCI research is now moving ahead towards accommodating and integrating these approaches. A part of the research community is of the opinion that HCI and AI are fundamentally opposed to each other: with AI-powered devices being demonic and humans are to ...

  11. Artificial intelligence assisted improved human-computer interactions

    Analysis of current research work on HCI with AI. Chao Zhang et al. (2021) [10] proposed a stochastic human simulator for producing interactive user data based on cognitive models (CM). Various cognitive models may shape the human learning and decision-making processes that may suggest future behaviours and retroactions of target users. Firstly ...

  12. Human-Centered HCI Practices Leading the Path to Industry 5.0: A

    Using a systematic literature review, we analyze human-centered HCI practices in the industry and focus on SMEs. Table 3 offers a structured overview of the literature in the following categories: technology, contribution, user group, research design, and practical setting. Regarding the technologies which were used, most use cases in our review involved assistance systems or augmented reality.

  13. What do HCI Researchers do?

    What do HCI Researchers do? 2020 I'm a post-doctoral researcher in Human Computer Interaction (HCI), and here is my parents' answer when somebody asks them what I do for a living: "she is doing computer science". Although this is not not completely wrong, it is still… a bit vague.

  14. Top Research Laboratories in Human-Computer Interaction (HCI)

    Even though good HCI research occurs at hundreds of worldwide locations, a few research labs have defined the field and nurtured the most important work. Here's my list of the best. In This Article: The Dawn of Time: 1945-1979 The 1980s The 1990s A First Look: 2000-2010 Making the List: Criteria Long-Term Trend: The Fall of the Good

  15. Human-Computer Interaction (HCI) Meaning, Importance, and ...

    Human-computer interaction (HCI) is defined as the field of study that focuses on optimizing how users and computers interact by designing interactive computer interfaces that satisfy users' needs. This article explains the fundamentals of HCI, its goals, importance, and examples. Table of Contents What Is HCI? Importance of HCI Examples of HCI

  16. Science Fiction—An Untapped Opportunity in HCI Research ...

    Abstract. This work open up a conversation about the opportunities that Science Fiction offers to Human-Computer Interaction (HCI) and Design research. In doing so, first, it briefly challenges the term Design Fiction, an emerging concept with increasing popularity in HCI and Design research. Design Fictions are either, manifest design ...

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    You will work with the research team that is investigating the link between behavioral, cognitive, and affective aspects of students and their engagement with the Stoich Tutor. ... Human-Computer Interaction Institute The main office of the HCII is located on the 3rd floor of Newell-Simon Hall. 4804 Forbes Avenue Carnegie Mellon University 5000 ...

  18. Human-Computer Interaction Seminar Spring 2023

    Students should attend at least 4 faculty candidate talks and submit a combined review of their research quality and potential, with a final comparison between the HCI research work and visions that were presented by each faculty candidate. Grading is done solely by the instructor. The thresholds for A/B/C cutoffs are 90/80/70. Time Allocation

  19. 143 Hci researcher jobs in United States

    143 Hci researcher jobs in United States Most relevant Redcloud Consulting 4.9 Usability Researcher Redmond, WA $67K - $130K (Employer est.) An MA/MS or PhD in Psychology, HCI/HFE, HCDE, or related field is preferred. A user research specialist designs and carries out qualitative studies to…… 30d+ Credit Karma 4.5 Principal Product Researcher

  20. Human Computer Interaction Hci jobs

    Job details Here's how the job details align with your profile. Pay $94,300 - $182,600 a year Job type Full-time Location One Microsoft Way, Redmond, WA 98052 The Prose team is looking to hire a Researcher II - Human-Computer Interaction (HCI), experienced with human-computer interaction and high-impact research.

  21. Strategic HR Training and HR Conferences

    The guest speakers were excellent in their delivery and were experts on the Discussion topics. HCI is keeping current with trending statisitics and relevent topics. Love how you can go back and view the videos and presentations if by chance you were distracted by work during the conference. Read more. Trevor Glanz, October 26.

  22. Talent Pulse

    Director, Global Talent Acquisition, Delta Air Lines. Talent Pulse explores the latest trends and challenges in strategic human capital management. Through quarterly research reports, Talent Pulse provides practitioners and decision-makers with insights and tools to work better today and prepare for the future of work.

  23. Women in AI: Krystal Kauffman, research fellow at the Distributed AI

    When I first started data work nine years ago, very few people knew that there was a global workforce quietly programming smart devices, developing AI and building datasets from their homes. Over ...

  24. Stanford Medicine study identifies distinct brain organization patterns

    Brain structures tend to look much the same in men and women, and previous research examining how brain regions work together has also largely failed to turn up consistent brain indicators of sex. Vinod Menon. In their current study, Menon and his team took advantage of recent advances in artificial intelligence, as well as access to multiple ...

  25. Research grant aimed at improving wastewater monitoring for diseases in

    "ARC's grant of $400,000 will help Virginia Tech expand their work to detect pathogens in wastewater from rural communities," U.S Rep. Morgan Griffith said in a press release announcing the grant. "This work is aimed at improving our country's public health through better community health monitoring and outbreak forecasting."

  26. Weekly Research Update: Thursday, February 22, 2024

    The second annual Research Core Fair is three weeks away! The University of South Carolina is hosting a Research Core Fair on Friday, March 15, 2024, to spotlight the wealth of resources at the University that are available to researchers. The Research Core Fair is open to all USC students, faculty and staff.

  27. 3

    The resulting core HCI research framework comprises discipline (as an academic field of study), general problem (as the design of human-computer interactions), particular scope (as the design of human-computer interactions to do something as desired), research (as the diagnosis of design problems and the prescription of design solutions, as they...

  28. Four-day week made permanent for most UK firms in world's biggest trial

    A government spokesperson said: "We have no plans to introduce a four-day working week. Ultimately it is for employers and employees to agree what working arrangements work best for them, and we will be making changes to our flexible working legislation in April, including the right to request flexible working from day 1 of a new job."