Research Projects

Below is the list of projects offered for the summer 2023 program.

Adaptive Learning Technology in Special Education

Lead Mentor: Haiyi Zhu & Naomie Williams

Project Description: Despite the growing body of evidence showing Artificial Intelligence (AI) systems do not provide equitable outcomes for individuals with disabilities, they are rapidly being integrated into society. AI’s ability to intensify exclusion is concerning in light of surging demand, particularly in education. The global e-learning market size is expected to grow by $93.64B over the next four years, partially a result of COVID-19. This rise of AI systems and increased demand for e-learning software has the potential to further inequitable learning outcomes for students with disabilities. True inclusion, particularly in STEM fields, requires addressing the ways in which software has the potential to reify and expand existing inequities or, if well-designed, limit them.This summer we will be investigating the design challenges and opportunities of adaptive learning software for students with learning disabilities. We will explore potential design adaptations, while balancing various stakeholder values (i.e. teachers, students, and administrators) in our creation process.

Student Involvement: Students will be involved in data collection, analysis, and prototyping.

Skills or Requirements:

Preferred skills: Design/HCI, prototyping, web development, qualitative research methods
Experience or interest in accessibility
Experience or interest in educational technology
Experience or interest with AI/machine learning

Research Areas in Which This Project Falls:

Accessibility
Applied Machine Learning
Artificial Intelligence (AI)
Design Research, Education
Intelligent Tutoring Systems
Learning Sciences and Technologies
Social Good
Societal Problems
User Experience (UX)

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.

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!

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:

Computer Aided Manufacturing
Enabling Technologies
Human-Robot Interaction (HRI)
Tools
Wearables

AI-Caring: Agents, 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.

Student Involvement: Student research assistants will aid researchers in designing and executing studies that provoke participants with possible futures. This includes helping participants critically reflect on what they desire and fear about how technology might function within their homes.

Skills or Requirements (or desire to learn):

Fieldwork including observations, interviews, and directed storytelling
Brainstorming
Design of conversational interfaces
Understanding of social psychology: social interaction, identity, self-presentation
Design and execution of user studies

Research Areas in Which This Project Falls:

Accessibility
Applied Machine Learning
Artificial Intelligence (AI)
Design Research
Enabling Technologies
Healthcare
Human Assistance
Human-Robot Interaction (HRI)
Service Design
Social Good
Societal Problems
User Experience (UX)
Voice

Building Novel Interfaces for Live Streaming

Lead Mentor: Noor Hammad

Project Description: This project focuses on envisioning the future of live streaming interfaces. Using our toolkit, GameAware, which is built for the Twitch streaming platform, we are able to design and develop live streaming experiences that were not possible before. Thus, the goal of this project is to move beyond developing the toolkit and into examining what prototypes and design are made possible by GameAware. More specifically, this REU project will have a student design and develop Unity games, as well as design interfaces visible on Twitch, using the GameAware toolkit. Additionally, the student will help organize a "game jam", where other developers and designers will use our tools to make their own live streaming experiences.

Student Involvement: The student will work closely with the project lead and will be involved in every aspect of the project as described above. This means the student will get exposure to Unity game development, front end web development (using Javascript/HTML/CSS/other web technologies), and the chance to organize and a user study (in the form of a game jam).

Skills or Requirements:

Experience in software development, and in particular the ability (and eagerness!) to learn new technologies
Familiarity with web technologies such as JavaScript is preferred.
Familiarity with either Unity game development is preferred.
Highly motivated and able to collaborate with others

Research Areas in Which This Project Falls:

Games
User Experience (UX)

Chemistry Tutor Designer and Programmer

Lead Mentor: Bruce McLaren

Project Description: Two REU interns will work together and be responsible for re-designing and extending the Stoich Tutor (https://stoichtutor.cs.cmu.edu/), an intelligent tutor the McLearn Lab at CMU uses for studies with high school students. The specific way in which the tutor will be extended will be determined by results from an initial study that will occur in the spring of 2023, in which we will investigate the link between behavioral, cognitive, and affective aspects of students and their engagement with the Stoich Tutor. The interns will have a computer science background with skills in HTML5/CSS3/JavaScript, an optional background in chemistry, as well as familiarity with Angular or AngularJS. The interns will work with Prof. Bruce McLaren and research programmers Hayden Stec and Leah Teffera, with Stec and Teffera as the primary mentors.

Student Involvement: Technical development and classroom study preparation

Skills or Requirements:

Preferred: CS (or other technical) major, HTML5/CSS3/JavaScript skills;
Optional: Background and interest in chemistry; Familiarity with Angular or AngularJS

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Education
Intelligent Tutoring Systems

Closing the AI Innovation Gap

Lead Mentor: J ohn Zimmerman

Project Description: Today, almost every AI initiative started within a company fails. 85% or more never get to deployment, and many that do get deployed fail when users fail to adopt them or when they create unintended problems.

In working on this challenge, we repeatedly hear from companies that data science teams think of AI services customers do not want while UX design teams think of AI services that cannot be built. This is the AI innovation Gap. Our work focuses on trying to close this gap.

We are developing new tools, innovation methods, and resources that make it easier for interdisciplinary teams of data scientists, domain experts, product managers, and designers to envision AI services that are technically achievable, financially viable, and acceptable/desired by end users and customers. Over the summer, we will work with our industry partners to understand if our approach to ideation and selection of projects produces a more effective exploration of the entire opportunity space and selection of more viable solutions (high value, low risk).

Student Involvement: Student researcher assistants will help coordinate with our industry partners including their design teams and ML teams to arrange and execute brainstorming and ideation sessions. They will also help with analysis of the workshop data we collect.

Skills or Requirements:

Professional demeanor and ability to work with and develop trust with industry professionals;
Brainstorming and facilitation of brainstorming;
Design and execution of user studies;
Analysis of qualitative data using thematic analysis

Research Areas in Which This Project Falls:

Applied Machine Learning
Artificial Intelligence (AI)
Design Research
Methods
Service Design
User Experience (UX)

Computer Supported Collaborative Learning Programmer

Lead Mentor: B ruce McLaren

Project Description: In this project, you will be involved in extensions to AI-enabled support for learning during collaborative software development. Depending on your skills and interests, this work may involve basic research in automated hint generation for code, development of new dialogue agent strategies, or development of collaborative programming experiences embedded in an existing curriculum. The skills you should have include solid programming skills in Python and possibly Java, exposure to machine learning, and experience programming in cloud-based software development environments. This intern will work with Prof. Carolyn Rosé and members of her research team.

Student Involvement: Research on collaborative learning and programming of collaborative learning systems

Skills or Requirements:

Preferred: CS or IT major, Python programming skills;
Optional: Java programming skills, Exposure to machine learning, Cloud-based development

Research Areas in Which This Project Falls:

Applied Machine Learning
Education
Social Good

Designing AI Recommendations for Treatment Decisions in Healthcare

Lead Mentor: Venkat Sivaraman

Project Description: Sepsis, a life-threatening medical condition in which the body damages its own internal organs, represents a major cause of death in hospitals. We are working on building interactive tools to help physicians and other healthcare providers diagnose and treat sepsis more effectively using artificial intelligence (AI) algorithms. These tools leverage historical patient trajectories to identify and recommend optimal treatment plans to clinicians in real-time. However, providing these recommendations to clinicians is no simple task - clinicians often dismiss them as untrustworthy, or pick and choose aspects of the recommendation to follow. We are looking for a motivated student to work with us and our clinical collaborators to understand how best to deliver AI-generated recommendations.

Student Involvement: Students will develop and conduct interviews or surveys with healthcare experts, as well as analyzing the findings. The ideal student for this position is someone with a strong passion for healthcare, and experience or interest in decision making and/or qualitative data analysis.

Skills or Requirements:

Some prior experience in the healthcare domain strongly encouraged (shadowing, working with clinicians, and/or coursework in biology or healthcare)
Experience with interaction design and/or qualitative research (prototyping, interviewing, qualitative coding, thematic analysis) is preferred
Prior programming experience in Python or JavaScript would also be considered, but is not the main focus of the project

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Healthcare

Designing Inclusive Collaboration Environments

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.

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.

Skills or Requirements:

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).

Research Areas in Which This Project Falls:

Social Computing
Social Good
Societal Problems
User Experience (UX)

Designing the Future of Transit Work

Lead Mentor: Sarah Fox

Project Description: Research and deployment in autonomous vehicle (AV) technology has advanced quickly and has been explored for public transit operation. The evolution of public transit has additionally automated many forms of transit work, such as ticket checking and stop enunciation. For transit workers and unions, the deployment of automated technology presents a drastic shift in the future of operation and control management, and poses questions around safety and service. This project works closely with transit advocates and workers to explore how transit work may transform as autonomous vehicle (AV) technology is potentially applied to the complex environment of public transit. The Summer 2023 stage of the project draws upon our stage 1 and 2 findings and will involve facilitating a series of participatory design workshops with transit union members and leaders, technologists, and members of transit advocacy groups. These engagements will allow us to gain a deeper understanding of the concerns of bus operators around the development of AVs, collaboratively generate concepts for the design of technology and transit policy, and re-imagine future roles such that bus operators’ experiences and expertise are centered.

Student Involvement: Students will assist in generating workshop protocols, embark on participant recruitment and workshop design, and facilitate a series of participatory design workshops that allow us to explore future operator roles under different autonomy limitations and requirements for human interaction.

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
User Experience (UX)

Doing for learning and assessment

Lead Mentor: Paulo Carvalho

Project Description: A lot of instruction is based on passive approaches such as watching videos and reading textbook instruction complemented by active approaches such as worksheets and educational technology. How much of the passive instruction is necessary to benefit from practice and educational technology work? And how can we leverage existing educational technology data to develop continuous assessment that includes models of learner variability without interrupting natural student learning activities.

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

Skills or Requirements:

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

Research Areas in Which This Project Falls:

Education
Intelligent Tutoring Systems
Learning Sciences and Technologies

EduSense: Classroom Sensing Towards More Inclusive & Equitable Teaching Practices

Lead Mentor: Tricia Ngoon

Project Description: Instructors at the college level often receive very little teaching professional development (PD) nor do they have time to participate in extensive PD activities, leading to suboptimal learning experiences for students, particularly in STEM fields. This project will explore the use of classroom sensing technologies to collect data to help instructors recognize when and how to implement equitable learning strategies. Research activities will include prototyping, storyboarding, user interviews, and data analysis. There are numerous design and research challenges in these broad directions, and we welcome any undergraduates who have an interest in design, learning technologies, and user research.

Student Involvement: The student will meet with the mentors and team weekly and assist with study design, prototyping, user interviews, data analysis, and writing.

Skills or Requirements:

Students should have knowledge and experience in design research and methodologies such as user interviews, storyboarding, and prototyping
Experience in Figma and programming (C++, Python, JavaScript) preferred, but not required)

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Education
Learning Sciences and Technologies
Sensors

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.

Student Involvement: Participate in research activities and paper writing.

Skills or Requirements:

HCI/design skills, especially related to web-applications
Interested in AI/machine learning/data mining

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Social Computing
Societal Problems

Equitable New Mobility

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. 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. This work seeks to develop community-driven approaches to the deployment and governance of new mobility technologies, ensuring that interventions truly serve residents.

Student Involvement: The REU students will be closely involved in the next phase of the project, focusing specifically on developing and piloting design activities for a series of participatory workshops with residents, advocates, and municipal representatives. Based on findings from these engagements, REU students will also contribute to the design of participatory planning tools and activities that could be taken up by local organizations and government agencies.

Skills or Requirements:

Experience or strong interest in ethnographic observation and participatory design OR VR/simulation
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
Ethics
Human-Robot Interaction (HRI)

Future of work in the hospitality industry

Lead Mentor: Jodi Forlizzi

Project Description: Automation is proliferating in the hospitality industry, and will continue to do so, accelerated by the COVID-19 pandemic. Large numbers of hospitality workers, who are majority female and 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 — for example, high-touch, face-to-face service interactions which are critical to the success of hospitality workers. Too often, technological innovations are developed and implemented without input from the workers who are best suited to understand their benefits and pitfalls. We will address the lack of worker voice on the impact of future automation technology in the hospitality industry, and to make suggestions for enhancing future workers and future work. We will develop a novel co-design process to empower workers in having a voice in creating their future work, and validate it in the hospitality industry.

Student Involvement: Interviews and observations, data analysis, scenario development, design of training materials and algorithmic services

Skills or Requirements:

Interviews
Data analysis
UX design, service design

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Service Design
User Experience (UX)

Incorporating and Balancing Stakeholder Values in Algorithm Design

Lead Mentor: Haiyi Zhu

Project Description:

"This project will create a general method for value-sensitive algorithm design and develop tools and techniques to help incorporate the tacit values of stakeholders, balance multiple stakeholders' values, and achieve collective goals in the development of an algorithm. The research community has paid increasing attention to the role of human values in algorithm design and development. For example, fairness-aware machine learning research attempts to translate fairness notions into formal algorithmic constraints and develop algorithms subject to such constraints. Despite the mathematical rigor of these approaches, prior research suggests a disconnect between the current discrimination-aware machine learning research and stakeholders' realities, context, and constraints; this disconnect is likely to undermine practical initiatives. Furthermore, studies have suggested that there are often tensions among a diverse set of values relevant to the design of the algorithm. A new general method will be developed in the context of Redesigning Wikipedia's Objective Revision Evaluation Service (ORES), a machine learning-based service designed to generate real-time predictions on edit quality and article quality, which will benefit vast numbers of people who consume the Wikipedia content either directly or indirectly through other applications.

There are four major goals of this research. The first is to articulate and demonstrate a general method for creating algorithmic systems that respect and balance stakeholders' values. The second goal is to create techniques for generating an algorithmic system's value report and explaining the value trade-offs. The third goal to create, deploy, and evaluate social and technical innovations to address fundamental trade-offs between different values. The final goal is to design and implement improvements to ORES, which will improve a wide variety of applications that rely on ORES, and Wikipedia's content and community as a whole. For an example of the kinds of problems that must be solved, quality control algorithms that prioritize efficiency in deleting low quality content incur the risk of undermining the motivation of contributors in peer production communities, particularly new contributors who are still learning how to contribute. To date, however, little work has been conducted to create solutions to address tensions and trade-offs between different values in algorithm design. The research will be performed through multiple studies by stepping through the process for a diverse set of tasks, each of which will allow interaction with multiple stakeholders, who have different (and perhaps conflicting) values."

Skills or Requirements:

Preferred (not required) skills: HCI/design skills, especially related to web-applications. Have interests in AI/machine learning/data mining

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Social Computing
Societal Problems

Intelligent Tutor Programmer

Lead Mentor: Bruce McLaren

Project Description: In this project you will design and write code to develop intelligent tutors that will help community college students better understand programming and computational thinking. You will learn about conducting research studies with college-age students who use educational technology to support their education. You will also learn about code repositories and good software engineering methodologies and practices, as well as gain exposure to and engage in learning sciences and educational technology research. This intern will work with Prof. Bruce McLaren, the head of the McLearn Lab, and research programmer Leah Teffera, with Teffera as the primary mentor.

Skills or Requirements:

Preferred: CS major, HTML5/CSS3/JavaScript skills
Optional: Familiarity with Angular or AngularJS

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Education
Intelligent Tutoring Systems

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, 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:

Applied Machine Learning
Artificial Intelligence (AI)
Data Visualization
Ethics
Social Good
Tools

Learning Game Programmer (for the game "Angle Jungle")

Lead Mentor: Bruce McLaren

Project Description:
You will write and revise code to alter and extend the existing angle learning game, Angle Jungle, to prepare it for new classroom studies in the fall of 2023. The precise way in which Angle Jungle will be modified and extended will be determined by classroom studies that will occur during the 2022-2023 academic year. You will learn about code repositories, state-of-the-art software engineering methodology, and good software practice. You should have a computer science background with skills in HTML5/CSS3/JavaScript, as well as familiarity with Angular or AngularJS. You will work with Professor Bruce McLaren and Research Programmer Hayden Stec, with Stec as the primary mentor.

Skills or Requirements:

Preferred: CS (or other technical) major, HTML5/CSS3/JavaScript skills
Optional: Familiarity with Angular or AngularJS

Research Areas in Which This Project Falls:

Education
Games
Intelligent Tutoring Systems

Learning Game Programmer (for the game “Decimal Point")

Lead Mentor: Bruce McLaren

Project Description:
You will write and revise code to alter and extend the existing decimal learning game, Decimal Point, to prepare it for new classroom studies. The precise way in which Decimal Point will be modified and extended will be determined by classroom studies that will occur during the 2022-2023 academic year. You will learn about code repositories, state-of-the-art software engineering methodology, and good software practice. You will work with Prof. Bruce McLaren and programmers Hayden Stec and Leah Teffera, with Stec as the primary mentor.

Skills or Requirements:

Preferred: CS (or other technical) major, HTML5/CSS3/JavaScript skills;
Optional: Familiarity with Angular or AngularJS

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Education
Games
Intelligent Tutoring Systems

Privacy by Design

Lead Mentor: Jodi Forlizzi

Project Description:

We are developing Privacy through Design (PtD), a novel research methodology to help creators of consumer-facing AI technologies model privacy concerns among end-users in the development of consumer products, and understand how to re-design those concepts in a manner that respects the privacy concerns of stakeholders while retaining the envisioned value or utility of their concept. In this project, we will develop a taxonomy of algorithmic privacy intrusions, incorporating experts and practitioners in industry and academia to develop PtD. We will conduct a comparative evaluation of PtD and Google’s PAIR guidebook with student teams to determine if and how PtD helps creators reduce privacy risk.

Skills or Requirements:

Preferred skills: Conducting interviews, analyzing data, developing scenarios

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Design Research

Researching favorable conditions for middle school math homework on smartphones

Lead Mentor: Conrad Borchers

Project Description:

This project aims to research favorable math homework conditions for middle school students learning with intelligent tutoring systems. We plan to conduct design-based research with students, parents, and teachers to create a data-optimized tutoring system for smartphones for deliberate math practice, combined with a new system for motivational nudges to support homework. A potential project the student could get involved in is developing a tailored nudging intervention for middle school students, parents, and teachers. Open research questions include: What type of nudges and degrees of data transparency do teachers, parents, and students prefer? How can we select the most effective nudges given a particular student’s current learning environment and habits? We are looking for 2-3 motivated students to help with design-based research OR the technical implementation of homework interventions, including the opportunity for research article co-authorship.

Skills or Requirements:

Required: Prior experience with and relevant skills in lo-fi prototyping and UX design (e.g., Figma) OR prior experience with and relevant skills in web application development, including at least one framework for front-end and one for back-end development

Preferred: Prior experience conducting user research and design-based interventions OR prior experience with or knowledge of server deployment

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Design Research
Education
Intelligent Tutoring Systems
Learning Sciences and Technologies

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

Lead Mentor: Nikolas Martelaro

Project Description:

As modern design tasks grow increasingly challenging, artificially intelligent (AI) design tools have the potential to provide new support to designers and engineers. This project will work to enable a future of computational co-creation, in which humans and AI collaborate and learn from each other to create new designs. The project addresses a vital national need: to prepare the emerging workforce in design, engineering, and manufacturing to better solve the complex problems of today by collaborating with AI design tools. Our research will explore how designers learn to collaborate with such AI design tools and how we can develop strategies and tools to support them in working better with AI.

Skills or Requirements:

1) Tool development: programming experience, user interface design experience, rapid prototyping and testing
2) Learning measurement: experience running user studies, experience with qualitative analysis, experience with survey and questionnaire design and analysis

Research Areas in Which This Project Falls:

Artificial Intelligence (AI)
Design Research
Intelligent Tutoring Systems
Learning Sciences and Technologies
Tools

Transforming makers into creative entrepreneurs

Lead Mentor: Nikolas Martelaro

Project Description:

Many makers are starting businesses to sell their goods. Much of this is mediated with digital technology. While makers are creative they often don’t have business training. How can we help them run successful businesses? Our project will look to understand the need of maker entrepreneurs to develop new computational tools to help them transition from makers to successful business owners.

Skills or Requirements:

Interviewing
Qualitative analysis
Design ideation
User testing

Research Areas in Which This Project Falls:

Design Research
Human Assistance
User Experience (UX)

Understanding The Personas of Streamers in Educational Live Streaming

Lead Mentor: Noor Hammad

Project Description:

The goal of this project is to understand the personalities and traits that streamers of educational content use in their streams. Not much is known about the "personas" that streamers take on in order to stream educational content. Hence, the focus of this qualitative project is to begin understanding these personas. In particular, the project is interested in these questions: 1. What streamer personas exist in educational live streaming? 2. How do streamers decide on their persona? 3. What personas/traits contribute to a successful educational live stream? Students involved in this project will take part in organizing/executing interviews with streamers, observing educational live streams, and analyzing qualitative data.

Skills or Requirements:

Familiarity with qualitative research is preferred, but more importantly an interest in conducting qualitative research is a must
Organized and motivated to work in a less-defined research area
Ability to collaborate with others

Research Areas in Which This Project Falls:

Education
Games