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Research Projects

Below is the list of projects offered for the summer 2022 program. These will be updated in late October with the projects available for the summer 2023. The projects below should help give you an idea of what type of projects are available, the skills our faculty look for and other information that may help you prepare a successful application.

 

Accessible Notifications for Wheelchair-based Sensing Applications

Lead Mentor: Patrick Carrington

Project Description: People with motor impairments often use manual or power wheelchairs for mobility purposes. However, there exist myriad challenges due to the use of wheelchairs in various daily activities (e.g., health and injury prevention, social interactions, digital communication). For example, people with spinal cord injuries often suffer from pressure ulcers due to a the lack of sense on their lower body and in extreme cases can be fatal. In this project, we are aiming to explore sensing and notification approaches that empower people with motor impairments during specific daily activities by improving awareness, communication, and self-expression.

Skills or Requirements:

  • Hardware and software prototyping
  • Quantitative and/or qualitative analysis
  • Communication and Writing Skills

Research Areas in Which This Project Falls:

  • Accessibility
  • Context-Aware Computing
  • Sensors
  • Wearables
Advancing Metamaterials by exploring novel structures, developing design tools and fabrication methods

Lead Mentor: Alexandra Ion

Project 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.

Skills or Requirements:

  • 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

Research Areas in Which This Project Falls:

  • Accessibility
  • Computer Aided Manufacturing
  • Enabling Technologies
  • Tools
AI-Caring: Trust and Interpersonal Relationships

Lead Mentor: John Zimmmerman

Project Description: AI-Caring is one of the new NSF AI Institutes. It 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 to aid elders and their families when a family member begins to suffer cognitive decline.

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 a user and their social relationships in order to provide socially sophisticated support. The work will involve fieldwork to understand how agents can support people's presentation of self, envisioning of new applications where agents leverage a deeper understanding of relationships, and assessment of how people react to more socially sophisticated agents.

Skills or Requirements (or desire to learn):

  • Fieldwork including observations, interviews, and directed storytelling
  • Brainstorming and sketching of new services
  • Understanding of human social psychology: social interaction, identity, self-presentation
  • Design and execution of user studies
  • Theater craft skills including script writing and set dressing

Research Areas in Which This Project Falls:

  • Accessibility
  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Context-Aware Computing
  • Design Research
  • Enabling Technologies
  • Healthcare
  • Human Assistance
  • Service Design
  • Social Good
  • Societal Problems
  • User Experience (UX)
  • Voice
Annotations for lightweight note taking

Lead Mentor: Brad Myers

Project Description: When learning a new skill or completing a complex task, learners amass a large set of contextualized knowledge that could benefit later users. However, the process of writing down and synthesizing that knowledge into something that could be understood by others in the future is a time-consuming process that many learners are not interested in doing. We hypothesize that supporting short notes through in-context annotations will make the process of jotting down information and sharing this information with others easier while benefiting the original author through providing features to help learners organize their information and manage their tasks. We have had success with our annotation tool, Adamite (see www.adamite.net), a Chrome extension that helps developers share information when using programming documentation, but we are interested in generalizing our approach to other kinds of content, including integrating with other platforms such as Google Docs, Gmail or Notion where people make comments, supporting operating system-level notes such as notes on folders or files, and supporting code annotations in the IDE (we currently have an in-development VS Code extension). Participating in this research project may result in being an author on a publication at a prestigious conference such as CHI, UIST, or CSCW, and we are hoping to release Adamite as an open source project for general use.

Skills or Requirements:

  • Required skills: we prefer significant web development or significant JavaScript experience
  • Preferred skills: It would also be preferable to also have experience using React and/or Typescript, and some design and prototyping experience (e.g., experience using Figma or Adobe Creative suite tools) or experience performing user studies (e.g., interviews, survey design, A/B lab studies)

Research Areas in Which This Project Falls:

  • Crowd Sourcing
  • End-User Programming
  • Tools
Augmented Reality Meets Computational Interaction 

Lead Mentor: David Lindlbauer

Project Description: Augmented Reality and Virtual Reality offer interesting platforms to re-define how users interact with the digital world. It is unclear, however, what the requirements in terms of usability and interaction are to avoid overloading users with unnecessary information. In this project, we will build on existing machine learning approaches such as saliency prediction that leverage insights into human visual perception. The goal is to create computational approaches to improve the applicability and usefulness of AR and VR systems.

Skills or Requirements:

  • Strong technical background
  • Some familiarity with Computer Vision
  • Some experience with 3D editors and programming (e.g., Unity, Unreal)

Research Areas in Which This Project Falls:

  • Augmented Reality (AR)
  • Context-Aware Computing
  • Enabling Technologies
  • Virtual Reality (VR)
Chemistry Tutor Designer and Programmer 

Lead Mentor: Bruce McLaren

Project Description: Interested in a stiff programming challenge? This project is for you! The Stoich Tutor (https://stoichtutor.cs.cmu.edu/) is an intelligent tutor created by the McLearn Lab (PI Bruce McLaren) that is used to help high school kids learn stoichiometry, a subarea of chemistry. This tutor has been successfully used for many classroom studies. The REU intern on this project will port the tutor from Flash to HTML5/CSS3/JavaScript. This intern will be a crack programmer, optional skills in chemistry, and will have a computer science background with skills in HTML5/CSS3/JavaScript, as well as familiarity with Angular or AngularJS. The intern will learn about code repositories and good software engineering methodology and practice.

Skills or Requirements:

  • Programming skills (e.g., Python, Java)
  • Knowledge of HTML5/CSS3/JavaScript
  • Knowledge of Angular or AngularJS
  • A desire to work with a fun research team!

Research Areas in Which This Project Falls:

  • Education
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
Computational Understanding of User Interfaces

Lead Mentor: Jeffrey Bigham

Project Description: Machines that understand and operate user interfaces (UIs) on behalf of users could offer many benefits. For example, a screen reader (e.g., VoiceOver and TalkBack) could facilitate access to UIs for blind and visually impaired users, and task automation agents (e.g., Siri Shortcuts and IFTTT) could allow users to automate repetitive or complex tasks with their devices more efficiently. The benefits of these systems are gated on how well they can understand the content and interactions of underlying applications. We apply machine learning and data-driven approaches to build models that predict useful semantics: visual/layout patterns, UI design motifs, and interaction flows. Using this information, we aim to build tools for UI design and enhance the usability and accessibility of existing applications. Students will work with existing datasets of mobile UIs (e.g., https://interactionmining.org/rico) to design and develop model-driven systems for automated understanding and interaction. Students may also take part in the evaluation of these systems with end-users using qualitative (e.g., interviews) and quantitative methods.

Skills or Requirements:

  • Python programming experience
  • Experience or interest in machine learning
  • Experience or interest in mobile programming
  • Experience or interest in accessibility
  • Experience or interest in UI design

Research Areas in Which This Project Falls:

  • Accessibility
  • Applied Machine Learning
  • Artificial Intelligence (AI)
Decimal Learning Game Designer and Programmer

Lead Mentor: Bruce McLaren

Project Description: Interested in digital games and learning? This project is for you! Decimal Point (http://www.cs.cmu.edu/~bmclaren/projects/DecimalPoint/) is a digital learning game developed by the McLearn Lab (PI Bruce McLaren) to help middle school children learn decimals. The REU intern on this project will write and revise code to alter Decimal Point, to prepare it for new classroom studies in the Fall of 2022. The intern will learn about code repositories and good software engineering methodology and practice. This intern will have a computer science background with skills in HTML5/CSS3/JavaScript, as well as familiarity with Angular or AngularJS.

Skills or Requirements:

  • Programming skills (e.g., Python, Java)
  • Knowledge of HTML5/CSS3/JavaScript
  • Knowledge of Angular or AngularJS
  • A desire to work with a fun research team!

Research Areas in Which This Project Falls:

  • Education
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
Design Rationale Capture and Use Plugin

Lead Mentor: Nikolas Martelaro

Project Description: Why do interfaces end up the way they do? In this project we are looking to build a software plugin for a design tool such as Figma that helps designers track their decisions, go back to previous decisions, and improve their collaboration with each other by know why they are designing things the way they are. We ask how we can efficiently capture design rationale in ways that fit with designer's workflows and what could designers do when they have their rationale captured. In the project, the student will work with our team to develop a plugin based on initial design ideas for new rationale capture interfaces. As development progresses, the student will test their design for usability and usefulness with interface designers.

Skills or Requirements:

  • Programming experience in Javascript and HTML
  • Basic understanding of the the user interface design process
  • Experience building software and testing with end users
  • Experience managing complex development tasks over the course of a project
  • Effective communication with team members and interest in interfacing with designers

Research Areas in Which This Project Falls:

  • Design Research
  • Enabling Technologies
  • Tools
  • User Experience (UX)
Diversity and Inclusion in Open Source Software

Lead Mentor: Laura Dabbish

Project 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.

Skills or Requirements:

  • 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), front end programming

Research Areas in Which This Project Falls:

  • Social Computing
  • Social Good
  • Societal Problems
Empowering and Enhancing Workers Through Building A Community-Centered Gig Economy

Lead Mentor: Haiyi Zhu

Project Description: The gig economy is characterized by short-term contract work performed by independent workers who are paid in return for the "gigs" they perform. Example gig platforms include Uber, Lyft, Postmates, Instacart, UpWork, and TaskRabbit. Gig economy platforms bring about more job opportunities, lower barriers to entry, and improve worker flexibility. However, growing evidence suggests that worker wellbeing and systematic biases on the gig economy platforms have become significant societal problems. For example most gig workers lack financial stability, have low earning efficiency and lack autonomy, and many have health issues due to long work hours and limited flexibility. Additionally, gig economy platforms perpetuate biases against already vulnerable populations in society. To address these problems, this project aims to build a community-centered, meta-platform to provide decision support and data sharing for gig workers and policymakers, in order to develop a more vibrant, healthy, and equitable gig economy. The project involves three major research activities. (1) Working with gig workers and local policymakers to understand their concerns, challenges, and considerations related to gig worker wellbeing, as well as the current practices, problems, and biases of existing gig economy platforms. (2) Developing a data-driven and human-centered decision-assistance environment to help gig workers make "smart" decisions in navigating and selecting gigs,and provide a macrolevel perspective for policymakers working to balance their diverse set of objectives and constraints. (3) Deploying and evaluating whether and how the above environment addresses the fundamental problems of worker wellbeing and systematic biases in the gig economy.

Skills or Requirements:

  • We have a few sub-projects. You will be able to choose which direction suits your interest and ability most.

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Social Computing
  • Societal Problems
Enabling Adaptive Practice of Prior Knowledge towards Promoting Education Equity

Lead Mentor: Vincent Aleven

Project Description: Students will learn the best when offered the timely, proper scaffoldings that correspond to their current knowledge level. With AI-based intelligent tutoring systems that can calculate students current skill mastery of certain knowledge, it is possible to offer personalized, adaptive practice based on each students’ prior knowledge. This may better prepare students up to the next-to-be-learned knowledge, reduce the time of them struggling unproductively or practicing knowledge they have already mastered, and increase their learning efficiency through more personalized, focused and targeted practice. Such adaptive practice of prior knowledge also holds the potential to bridge the knowledge gap between different students, and promote education equity. In this project, we are interested in exploring the design space of building such a system/ algorithm.

Skills or Requirements:

  • Preferred skills in web-based technologies development
  • Preferred skills HCI/design skills, especially related to web-applications
  • Preferred skills in AI/machine learning/data mining

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Design Research
  • Education
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
  • Social Good
  • User Experience (UX)
Equitable new mobility: Community-driven mechanisms for designing and evaluating personal delivery device deployments

Lead Mentor: Sarah Fox

Project Description: New mobility technologies are on the rise in cities across the United States, with micromobility platforms and autonomous delivery robots occupying the sidewalks of many mid-to-large municipalities. New mobility encompasses a wide range of shared, small-scale transportation technologies (up to 500 kg) used to aid in moving people and their belongings (e.g., e-scooters and delivery robots) at low to moderate speeds (maximum 45 km/hour). Amid the enthusiasm around what these devices could mean for the future of transportation and the circulation of essential goods, there are also concerns on who stands to benefit most from these technologies. This is especially the case in Pennsylvania, as recently passed state-wide legislation classifies personal delivery devices (PDDs) as “pedestrians,” bestowing them the same legal rights as human residents. In response, Pittsburgh government officials and members of advocacy organizations have come together as a coalition with the aim of developing municipal standards on current delivery devices to ensure continued accessibility of public space, and strategies for planning proactively for future new mobility deployments in the area. To contribute to the design and development of new mobility technology that truly serves residents, this research builds on a partnership with the City of Pittsburgh’s Department of Mobility and Infrastructure (DOMI) and local advocacy organizations to develop community-driven approaches to the deployment and governance of new mobility technologies.

Skills or Requirements:

  • Experience and/or strong interest in ethnographic observations and participatory design
  • Qualitative data analysis
  • Motivated to explore creative approaches to systems design/systems engineering
  • Experience with or strong motivation to collaborate with community organizations and local government

Research Areas in Which This Project Falls:

  • Accessibility
  • Design Research
  • Human-Robot Interaction (HRI)
  • User Experience (UX)
Exploring voice-based tools for learning

Lead Mentor: Julia Cambre

Project Description: Voice interfaces have become an increasingly ubiquitous presence in our everyday lives, with voice assistants like Siri, Alexa, and the Google Assistant helping people to accomplish common tasks like setting timers, asking for the weather, and controlling music. At the same time, however, the powerful affordances that voice provides have been less explored within educational contexts. In this project, we are interested in understanding the design space at the intersection of voice and education, and designing new web-based products that help to facilitate learning through voice interfaces. Working closely with a PhD student mentor and faculty advisor, Chinmay Kulkarni, interns working on this project will form an integral part of the design and development team. Depending on the intern’s skillset and desired learning goals, the work we conduct over the summer will involve needfinding and co-designing with teachers and students (likely in the context of language learning, though we may broaden to other topics), creating prototypes at varying levels of fidelity, developing and deploying a fully-functional voice-based learning tool, and writing academic papers about our work.

Skills or Requirements:

  • We are seeking students who have a background in at least one of the following, and interest in learning more about others:
    • Conducting usability studies and interviews
    • Front-end web development (e.g. HTML, CSS, Javascript)
    • Design and prototyping (visual, voice, and/or interaction)
    • Industry and academic trends in voice interfaces and education technology)

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Design Research
  • Education
  • Learning Sciences and Technologies
  • Tools
  • Voice
Gamified Conceptual Math Learning with AI-based Tutoring

Lead Mentor: Vincent Aleven

Project Description: In research studies, we found out that Lynnette and Gwynnette, AI-based tutoring systems for middle-school algebra, are very effective in helping students learn. These two tutoring systems share similar core instructional principles, but Lynnette is designed for supporting students’ conceptual learning while Gwynnette is designed for more engaging learning using many gamification elements such as a space theme, alien character, and a narrative context. To take Lynnette and Gwynnette to the next level, we would like to develop an even more powerful tutoring system that helps students learn important concepts while keeping them fully engaged. This would be achieved through integrating design principles used in Lynnette and Gwynnette and also through improving the design using existing data from middle-school students. Students will engage in the entire design-research process through brainstorming, need-finding, co-design with teachers and children, prototyping, and user testing. They may also conduct quantitative data analyses to inform design improvements based on student data.

Skills or Requirements:

  • Preferred skills: Design/HCI, prototyping, web development
  • Experience with game design, educational technology, and designing for teenagers is not required but would be considered a plus
  • Quantitative research skill is not required but would be considered as a plus

Research Areas in Which This Project Falls:

  • Design Research
  • Education
  • Games
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
  • User Experience (UX)
Human-AI co-orchestration of dynamically-differentiated, collaborative classrooms

Lead Mentor: Kexin (Bella) Yang

Project Description: Our research in K-12 classrooms equipped with AI-based tutoring systems, shows that teachers sometimes team up students on the fly (e.g., a student who has learned a lot already with one who is struggling), for brief one-on-one extra aid. For teachers to be most effective, however, they must be able, in real time, to see how their students are doing (struggling, disengaged, very far into covering the learning objectives, etc.). This information will enable them to take action to aid those who need help. We create tools by which middle-school teachers can effectively orchestrate combinations of individual and collaborative activities. The tools use tablets and mobile devices with artificial intelligence to turn the voluminous data into actionable diagnostic information and recommendations for teachers. We plan to further prototype and test these tools, to enhance the effectiveness of the spontaneous teaming up of students we have observed. We seek student interns interested in any of the many efforts needed to make these technologies work, which mainly include prototyping, testing and refining collaborative ITSs and orchestration tools through working with K-12 students and teachers; conducting piloting study in K-12 classroom; doing data mining to create new learning analytics that inform teachers about how their students are doing; and design-based research for designing and prototyping intuitive, comprehensible visualizations for teachers, for different hardware options, and trying them out with teachers.

Skills or Requirements:

  • HCI/design skills (preferred)
  • Design-based research (preferred)
  • Web technologies (preferred)
  • Experience with education technology is not required but would be considered a plus
  • Skills with AI/machine learning/data mining is not required but would be considered a plus

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Data Visualization
  • Design Research
  • Education
  • Learning Sciences and Technologies
  • Tools
  • User Experience (UX)
Innovation with AI

Lead Mentor: John Zimmerman

Project Description: In current AI innovation processes, design teams propose things that cannot be built and data science teams propose things that users do not want. To address this challenge, we have developed a taxonomy of AI capabilities as well as several artifacts that make these capabilities understandable to innovators who are not data scientists (service designers, product managers, domain experts, users). In addition, we have developed several boundary objects that help data scientists and non-data scientists reach a shared understanding of what is possible and what is desirable. Over the summer, we want to assess these things with innovation teams and understand how they do and do not support and improve collaboration. This will involve designing and running assessment studies as well as redesign of the communicative artifacts and boundary objects.

Skills or Requirements:

  • We are looking for students that have experience with (or at least interest in learning about) conducting product assessment user studies, envisioning and prototyping AI products and services, user experience and service design, lean startup innovation processes, customer discovery, development and refinement of an MVP.

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Artificial Intelligence (AI)
  • Design Research
  • Service Design
  • User Experience (UX)
Interactive Visualizations for Developing Fair and Responsible AI Systems

Lead Mentor: Alex Cabrera

Project Description: AI systems are being deployed in a growing number of domains, from self-driving cars to cancer screening models. While these systems can outperform humans, they can also encode or exacerbate issues like societal biases and safety concerns. Discovering and fixing these issues is challenging since modern AI systems are often large black-box models with billions of parameters. To tackle these challenges we are building interactive, human-centered tools and visualizations that help AI/ML developers both better understand and improve how AI systems behave. Examples of this work include FairVis (https://cabreraalex.com/#/paper/fairvis), a visual analytics system for discovering biases in AI models. We are looking for students who are interested in creating human-centered data science tools that help ML practitioners create safe, fair, and performant intelligent systems. As part of this program, you will interview ML developers to understand their needs, prototype and build web-based tools for AI development and testing, and evaluate your system with practitioners.

Skills or Requirements:

  • Required: Some experience with JavaScript
  • Required: Interest in human-centered data science tools
  • Preferred: Experience with front-end frameworks like Svelte.js and React
  • Preferred: Experience with machine learning libraries like PyTorch and Tensorflow

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Data Visualization
  • Tools
Modeling free choice game exploration behavior in afterschool programs

Lead Mentor: Erik Harpstead

Project Description: Multi-game collections like Roblox and Dreambox are increasingly popular with youth audiences. How do students in afterschool settings discover and decide on which games to play? Do methods differ between sites? This project will analyze video data of K-8 youth exploring collections of games in 5 free-choice afterschool settings to collect evidence and build theory about how they explore these collections in search of games to play, both individually and collectively. Findings from this study will stand alone and be given opportunity for publication, and will also inform the design of an educational multi-game collection we are building as part of a larger NSF project.

Skills or Requirements:

Some subset of these skills would be useful:

  • Candidates must be able to obtain required clearances to work with data from minor participants (standard for educational research and we will guide you through the process.
  • Experience or professional interest in mixed methods research for educational technology and/or social sciences is helpful but not required.

Research Areas in Which This Project Falls:

  • Education
  • Games
  • Learning Sciences and Technologies
Negotiation Toolkit

Lead Mentor: Laura Dabbish

Project Description: Research shows women negotiate less often than men across a variety of situations and this tendency perpetuates inequality such as the leadership and wage gap between men and women. One way to work towards equity is by teaching and providing scalable access to training tools that will empower women to advocate on behalf of themselves. This independent study will involve working to implement and evaluate an interactive toolkit for learning about and practicing everyday negotiation skills in a mobile app. In this project, we will work with PROGRESS (Program for Research and Outreach on Gender Equity in Society) a CMU founded organization which addresses gender inequity by providing negotiation tools to empower women and girls. Students will work through a user-centered design process, developing a high fidelity prototype, and conducting evaluation sessions with women as we refine the design.

Skills or Requirements:

  • Required: Experience with mobile app development.
  • Desired: Experience and/or coursework in interaction design, user research, and ability to use Figma, inVision, Sketch, or other visual design and prototyping tools. Strong organizational and interpersonal skills.

Research Areas in Which This Project Falls:

  • Social Computing
  • Social Good
  • Societal Problems
Non-programmer Authoring of AI-based Tutoring Software (CTAT)

Lead Mentor: Vincent Aleven

Project Description: Past research shows that AI-based tutoring systems--software that coaches students step-by-step as they try to solve complex problems--can be very helpful aids to learning, for example, middle school and high school mathematics. The effectiveness of tutoring software has been shown in many different subject areas; some systems have reached commercial markets and are in daily use in many schools. Inspired by these results, we have developed authoring tools that make the creation of tutoring software much easier: in many cases, it can be done entirely without programming, thus opening the door to a wide range of authors. Instructors in fields such as math and physics have used our tools to create tutoring software for their classes. We are now creating a new version of our authoring tools with the knowledge we have gained over the 20 years since their first release. We seek to make them intuitive, clear, efficient and readily available--without requiring complicated installation or advance instruction. We want to improve both of the principal activities of tutor-building--the creation of the student-facing user interface and the specification of the tutoring knowledge and behavior behind it. We want to support teams of teachers collaboratively creating these self-coaching, self-grading online activities that they might assign instead of conventional homework.

Skills or Requirements:

  • The work involves user-centered design of authoring tools, web programming, building tool prototypes, and trying them out with tutor authors of various backgrounds. As has occurred in past summers, we anticipate that a team of interns will work together and report jointly on their efforts.

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Education, End-User Programming
  • Intelligent Tutoring Systems
  • Learning Sciences and Technologies
  • Tools
  • User Experience (UX)
Practical activity and behavior recognition

Lead Mentor: Mayank Goel

Project Description: We will develop new sensing and machine learning approaches to recognize a user's actions and behavior in their environments. The goal is to use this information to aid users with their health outcomes. Some example applications we are working on are: (1) mental health assessment, (2) recovery from injuries, and (3) guiding through care tasks.

Skills or Requirements:

  • Subset of following skills:
    • Machine learning
    • Embedded computing
    • Hardware prototyping
    • Mobile application development

Research Areas in Which This Project Falls:

  • Applied Machine Learning
  • Healthcare
  • Human Assistance
  • Internet of Things (IoT)
  • Sensors
  • Societal Problems
  • Wearables
Privacy by Design: Example gathering and Taxonomy development

Lead Mentor: Jodi Forlizzi

Project Description: In this grant, we propose to introduce and develop Privacy through Design (PtD), a novel research methodology to help creators of consumer-facing AI technologies: (i) model how acute, use-case specific privacy concerns among end-users among stakeholders trade-off against the envisioned utility or value of proposed AI concepts; and, (ii) understand how to (re-)design those concepts in a manner that respects the privacy-concerns of stakeholder groups while retaining the envisioned value or utility of their concept. A first step in this work is to develop a taxonomy of algorithmic privacy intrusions to operationalize the unique privacy harms entailed by consumer AI and map those harms onto the unique capabilities and requirements of AI. A summer REU student will contribute this work.

Skills or Requirements:

  • Search and basic literature review skills
  • Develop a spreadsheet
  • Basic analysis skills

Research Areas in Which This Project Falls:

  • Artificial Intelligence
Skeema: Supporting Complex Sensemaking on the Web

Lead Mentor: Niki Kittur

Project Description: People spend approximately a trillion hours a year worldwide trying to make sense of the web for complex research tasks such as deciding on a new digital camera, learning about a new scientific domain, or making sense of a medical symptom. While search engines are good at helping people find useful sources, the subsequent activities of sensemaking – collecting, extracting, and structuring information – remain poorly supported by today’s tools such as browser tabs, spreadsheets, and docs. Furthermore, after each sensemaking episode in which an individual develops a useful mental representation of the domain for themselves, their work is essentially lost, with no one else benefiting. To put this in perspective, about twice the amount of effort put into creating all of Wikipedia is being lost every hour online. The primary objective of the project is to design and develop tools and techniques to reduce the friction of collecting information, synthesizing it into useful structures, and managing the myriad sensemaking tasks that users engage in every day.

Skills or Requirements:

  • Candidates should have web development OR interaction design skills
  • [Web Dev] proficient in React
  • [IxD] experience in designing new interactions and detailed interaction flows (preferably have experience in Figma)

Research Areas in Which This Project Falls:

  • Social Computing
  • Tools
Social Commerce: The Role of Social Media in Product Design and Development for Small-business Owners

Lead Mentor: Yasmine Koturri

Project Description: Increasingly, individual creators and creative small businesses turn to various online spaces (such as online creative communities, crowds, forums) seeking feedback to facilitate their design processes and inform decisions for what products to make. To date, the role of social media in this online feedback loop is relatively uncharted, yet simultaneously of growing importance as "social commerce'' is on the rise. In this project, we are exploring how these individual creators leverage their social media to solicit feedback, as well as probe ways to make such solicitations more effective. To make such exchanges more effective, we are leveraging a participatory design approach to build feedback software tools with and for creative small businesses. Interested students should be keen to learn about design methodologies, alongside enhancing their technical and research skills.

Skills or Requirements:

  • Object-oriented programming and data structures
  • Javascript
  • React, Node.js, Express, GraphQL, MongoDB (a plus, not required)

Research Areas in Which This Project Falls:

  • Social Computing
  • Tools
  • User Experience (UX)
Social Cybersecurity Games

Lead Mentor: Isadora Krsek

Project Description: This project leverages theory from psychology and known social influence principles to improve cybersecurity behavior and enhance security tool adoption. Students on this project will work on designing and developing web-based security-related mini games or interventions that incorporate cybersecurity training and information into people’s everyday workflows. They may also have an opportunity to conduct evaluations of these mini games or interventions.

Skills or Requirements:

  • Interest in interaction design, psychology and/or cybersecurity
  • Web programming (front-end or back-end)
  • Familiarity with inVision, Sketch, or other graphic design tools
  • Familiarity with Python or Javascript
  • Data analysis

Research Areas in Which This Project Falls:

  • Design Research
  • Games
  • Security and Privacy
  • Social Computing
  • Societal Problems
Studying the Effect of Social Influences on Cybersecurity Interventions

Lead Mentor: Isadora Krsek

Project Description: Research on the human factors of cybersecurity often treats people as isolated individuals rather than as social actors within a web of relationships and social influences. We are developing a better understanding of social influences on security and privacy behaviors across contexts. Students on this project will conduct interviews and experiments on people's cybersecurity behaviors. They will also be working to help develop a iOS mobile app with the goal of improving user's cybersecurity tool adoption based on the research findings.

Skills or Requirements:

  • Experience programming apps in xcode with Swift
  • Experience with Firebase
  • Coursework in psychology, design or cybersecurity
  • Experience with statistical analysis techniques or packages such as R
  • Interest in developing interviewing and survey design skills

Research Areas in Which This Project Falls:

  • Design Research
  • Security and Privacy
  • Social Computing
  • Societal Problems
  • User Experience (UX)
Toward Participatory Live Streaming Interfaces

Lead Mentor: Noor Hammad

Project Description: This project aims to bring audience participation games and stream aware interfaces to the Twitch live streaming platform. A toolkit is being developed to support these features, enabling the creation of novel participatory experiences by game developers. The goals of the project are to 1.) finalize the toolkit development so that it adheres to modern web development standards and 2.) evaluate the toolkit by providing it to game developers. This evaluation will be a mixed methods study in the form of a "game jam". Game jams are game design and development events where participants must create a game in a short amount of time (usually up to 72 hours). We will use this game jam to evaluate the toolkit's performance and its design potential.

Skills or Requirements:

  • Web development
  • Experience with qualitative research
  • Organization skills
  • Familiarity with Twitch

Research Areas in Which This Project Falls:

  • Design Research
  • Games
  • Tools
Upskilling Workers and Re-designing Workplaces for the Future of Automation in the Hospitality Industry

Lead Mentor: Sarah Fox

Project Description: This multi-institutional collaborative research project seeks to envision, design and engage in worker-oriented research and training related to the proliferation of automation in the hospitality industry, which has been accelerated by the COVID-19 pandemic. Large numbers of hospitality workers, who are majority women and from underrepresented groups, are being displaced by these technological changes. Workers’ positions are currently being augmented with algorithmic management and robotic assistance, replacing some jobs and transforming others that cannot be completely automated. The research team will investigate ways that technological innovations of the future can be developed and implemented with input from the workers who are best suited to understand their benefits and pitfalls. It is expected that this project will positively impact the hospitality workforce by preserving jobs, giving people more job satisfaction, reducing the way technology drives inequality, and developing policies and training programs that will generalize to other high-touch service industries. This project brings together several disciplines, including hospitality, human-computer interaction, service design, learning science, labor economics, and industrial relations. The research team has partnered with UNITE HERE, the largest hospitality union in the United States, which will provide a unique opportunity to research, prototype, and evaluate the research outcomes in training facilities and hotels, casinos, and food service establishments.

Skills or Requirements:

  • Co-design, user-centered design
  • Contextual inquiry
  • User research synthesis and analysis

Research Areas in Which This Project Falls:

  • Artificial Intelligence (AI)
  • Design Research
  • Service Design