Tessa Eagle

Tessa Eagle

UX Researcher and HCI PhD interested in Digital Health

Portfolio

  1. Survey of Body Doubling
  2. Digital Ethnography of ADHD Social Media
  3. ADHD Content Creator and Clinician Interviews
  4. Crowdsourcing Classroom Accessibility Improvements

A Survey of Body Doubling

What is body doubling? It’s not cloning - it’s a task initiation and completion strategy used by neurodivergent communities. To do what? Click to find out.

Exploratory Research. Survey of “Body Doubling”. Eliciting a community-driven definition of a task-completion phenomenon. Exploratory, Community-Based, Mixed Methods, Survey

Digital Ethnography of ADHD Social Media

ADHD has been sensationalized by the media. ‘Everyone has it now’ and yet it remains underdiagnosed. Social media is actually providing a service to many who have gone undiagnosed their entire lives, wondering why they feel different. A different take on social media and ADHD.

Exploratory Research. Ethnography of ADHD Social Media. Conceptualizing the Unbounded Social Media Community for Identity Discovery. Ethnography, Community-Based, Grounded Theory, Qualitative

Crowdsourcing Classroom Accessibility Improvements

This project uses crowdsourced data from neurodivergent Twitter users to examine changes that could be made to higher education courses to increase accessibility. By combining user-generated suggestions with Universal Design for Learning and guidelines from accessibility organizations, I develop a workbook for course staff to use as a resource to build accommodations into their class design.

Exploratory Research. Crowdsourcing Classroom Accessibility Improvements. Developing a workbook for improving higher education course accessibility through crowdsourced recommendations. Community-Based, Crowdsourcing, Qualitative, Accessibility

Comparing App Recommendation Systems

Interactive recommender prototypes designed to guide users through a set of questions to present them with a personalized set of suggested mental health apps

Evaluative Research. Comparing App Recommendation Systems. Usability testing of three methods for app searching. Usability Testing, Personas, Mixed-Methods

Trust in Chatbots and Taxonomy of Breakdowns

This project evaluated two chatbot apps for mental health with three participants over the course of ten days. The chatbot with fewer communication breakdowns led to higher scores on Trust and Competence as well as stronger feelings of Working Alliance.

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Data Visualization Explorations

Repository of my participation in R for Data Science’s Tidy Tuesday community of practice. Each week, a new dataset is released for people to practice their data visualization skills and receive help and feedback from the R community. I primarily work with {ggplot2} for graphics.

Design. Data Visualization Explorations. Playing with ways of presenting quantitative and qualitative data. Data Visualization, Data Cleaning, R + ggplot2

Recommender System Conversation Design

Interactive recommender prototypes designed to guide users through a set of questions to present them with a personalized set of suggested mental health apps

Design Research. Recommender Conversation Design. Iterative design of a mental health app recommender system website and chatbot. Iterative, Exploratory

Machine Learning on User Reviews

This project involves identifying predatory behaviors in mental health apps using training data to generate a model for analyzing large datasets of user reviews.

Technical Research. Applying Machine Learning to App User Reviews. Detecting predatory app behavior from NLP on user reviews. Machine Learning, Supervised Learning

Generative AI Projects

Two projects completed using generative AI. First, implementing the Wave Function Collapse algorithm to explore the generation of computational constellation art using 77 individual tiles designed in Photoshop. Second, developing a Twitterbot using the Tracery text generation and bot creation tool to post GPT-2-generated and expandable grammar content.

Design. Generative AI Explorations. Two genAI projects - one text-based and one image-based. Data Visualization, Text Generation, GPT

Shiny Application

Stemming from a prior static data visualization, I developed an interactive Shiny web application using R to explore historical (1997-2016) government spending on children.