Research
The questions the lab is working on, from how faculty think about generative AI to how engineers weigh sustainability in design. Each one links to its project, its people, and its papers.
Lines of inquiryhow our questions grew out of each other
Latest finding
An open-model workflow for thematic analysis found nearly all the themes planted in synthetic test data
Thematic analysis with open-source generative AI and machine learning: A new method for inductive qualitative codebook development (2026)
Each line is an area of inquiry running through time; each stop is a paper. Where a line branches, a new question grew out of an older one. Ringed stops are papers shared by two lines, joined by a transfer when the lines run side by side. Dashed track runs ahead to the end of current funding.
- Shared paper
- Published finding
- Tool built on it
Every paper on this map, by area
The field and its institutions
- Curriculum comparison: chemical and mechanical engineering education in the United States and Turkey (2025)
- Advanced Considerations in Quantitative Methods for New Directions in Engineering Education Research (2023)
- Analysis of Advances in Engineering Education Publications (2007-2020) to Examine Impact and Coverage of Topics (2022)
- Applying concepts from political science and economics to advance the study of engineering education (2022)
- Factors associated with collaboration networks in ASEE conference papers (2021)
- Taking stock: An Analysis of IJEE publications from 1996--2020 to examine impact and coverage of topics (2021)
- Learning from failures: Engineering education in an age of academic capitalism (2018)
- The revealing effects of disaster: A case study from Tulane University (2016)
Ethics, equity, and responsibility
- How do ethics and diversity, equity, and inclusion relate in engineering? A systematic review (2024)
- Collateral Damage: Investigating the Impacts of COVID on STEM Professionals with Caregiving Responsibilities (2022)
- Using Natural Language Processing to Explore Undergraduate Students’ Perspectives of Social Class, Gender, and Race (2022)
- Engineering ethics in engineering design courses: A preliminary investigation (2021)
- The correlation between undergraduate student diversity and the representation of women of color faculty in engineering (2021)
- Your views can be my views: Understanding differences in paradigms held by traditionally marginalized students in engineering (2021)
- An Investigation of When and Where Ethics Appears in Undergraduate Engineering Curricula (2020)
- Overcoming Challenges to Enhance a First Year Engineering Ethics Curriculum (2020)
- Monetizing Life May Be the Ethical Thing to Do (2019)
- Investigating influences on first-year engineering students’ views of ethics and social responsibility (2018)
- Factors related to faculty views of undergraduate engineering ethics education (2017)
- Telling it like it was: Histories of change in engineering ethics education (2017)
- Shadow codes of engineering ethics: An experiment in ethics imaginaries (2016)
- Educating for a revolution: Discerning together the Highlander idea and its lessons for ESJP’s work (2015)
How faculty think, teach, and assess
- Understanding instructor decision-making in engineering education for sustainable development: a comparison of institutions in Denmark and the United States (2025)
- Paradigm Shift? Preliminary Findings of Engineering Faculty Members’ Mental Models of Assessment in the Era of Generative AI (2024)
- Exploring Faculty Members' Conceptualizations of Diversity, Equity, and Inclusion in Engineering Education (2023)
- Promoting Research Quality to Study Mental Models of Ethics and Diversity, Equity, and Inclusion (DEI) in Engineering (2023)
- WIP: Faculty Use of Metaphors When Discussing Assessment (2023)
- Defining Assessment: Foundation Knowledge Toward Exploring Engineering Faculty’s Assessment Mental Models (2022)
How students learn and experience engineering
- Exploring the Impact of Engineering Projects in Community Service on Engineering Students’ Perspectives about Engineering as a Major (2023)
- How Participating in Extracurricular Activities Supports Dimensions of Student Wellness (2023)
- Development of hybrid laboratory sessions during the COVID-19 Pandemic (2022)
- Students’ Feedback About Their Experiences in EPICS Using Natural Language Processing (2022)
- Understanding First-year Engineering Students’ Perceptions of Working with Real Stakeholders on a Design Project: A PBL Approach (2022)
- Using Sentiment Analysis to Evaluate First-year Engineering Students Teamwork Textual Feedback (2022)
- Harvesting tweets for a better understanding of engineering students' first-year experiences (2020)
- Using Chatbots as Smart Teaching Assistants for First-Year Engineering Students (2020)
Sustainability and climate
- Inspiring Sustainability in Undergraduate Engineering Programs (2024)
- A Thematic and Trend Analysis of Engineering Education for Sustainable Development (2022)
- Augmented Reality for Sustainable Collaborative Design (2022)
- Civil Engineering Students’ Beliefs about Global Warming and Misconceptions about Climate Science (2021)
- Higher perceived design thinking traits and active learning in design courses motivate engineering students to tackle energy sustainability in their careers (2021)
- Predicting engineering students’ desire to address climate change in their careers: An exploratory study using responses from a U.S. National survey (2021)
- Civil Engineering Students’ Beliefs about the Technical and Social Implications of Global Warming and When Global Warming Will Impact Them Personally and Others (2020)
Careers and the workforce
- Using generative AI for large-scale qualitative analysis of social media posts to understand why people leave computer science (2025), read the finding
- Engineering students' interests in nonprofit and public policy careers: Applying a data-driven approach to identifying contributing factors (2025), read the finding
- Skill Development of Engineering and Physical Science Doctoral Students: Understanding the Role of Advisor, Faculty, and Peer Interactions (2024)
- What engineering employers want: An analysis of technical and professional skills in engineering job advertisements (2024)
- An Empirical Study of Programming Languages Specified in Engineering Job Postings (2022)
Technology policy
Language technology for education research
- Extending Minimal Pairs with Ordinal Surprisal Curves and Entropy Across Applied Domains (2026)
- Automated Analysis of Knowledge Types in Computer Science Textbooks: A Natural Language Processing Approach to Understanding Epistemic Climate (2025)
- A Reinforcement Learning Framework for N-Ary Document-Level Relation Extraction (2024)
- Exploring NLP-based Methods for Generating Engineering Ethics Assessment Qualitative Codebooks (2023)
- Pushing Ethics Assessment Forward in Engineering: NLP-Assisted Qualitative Coding of Student Responses (2023)
- Utilizing Natural Language Processing to Examine Self-Reflections in Self-Regulated Learning (2023)
- Clustering-based unsupervised generative relation extraction (2022)
- Work-in-Progress: Using Latent Dirichlet Allocation to uncover themes in student comments from peer evaluations of teamwork (2022)
- Figurative language in computer education: Evidence from YouTube instructional videos (2021)
- Using natural language processing to facilitate student feedback analysis (2021)
- Reinforcement Learning-based N-ary Cross-Sentence Relation Extraction (2020)
Generative AI for qualitative research
- Thematic analysis with open-source generative AI and machine learning: A new method for inductive qualitative codebook development (2026), read the finding
- Advancing Qualitative Analysis in Professional Disaster and Risk Communication: A Comparative Study of an OpenAI ChatGPT 3.5 Model-Enabled Method for Processing Complex Public Posts (2025)
- Expanding possibilities for generative AI in qualitative analysis: Fostering student feedback literacy through the application of a feedback quality rubric (2025), read the finding
- Leveraging Generative Text Models and Natural Language Processing to Perform Traditional Thematic Data Analysis (2025)
- From Manual Coding to Machine Understanding: Students' Feedback Analysis (2024)
- Novel Approach Designing Interview Protocols with Generative Large Language Models to Study Mental Models and Engineering Design (2024)
- Stumbling Our Way Through Finding a Better Prompt: Using GPT-4 to Analyze Engineering Faculty’s Mental Models of Assessment (2024)
- Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching (2024)
- Advancing qualitative analysis: An exploration of the potential of generative AI and NLP in thematic coding (2023)
- Exploring the Efficacy of ChatGPT in Analyzing Student Teamwork Feedback with an Existing Taxonomy (2023)
- The Utility of Large Language Models and Generative AI for Education Research (2023)
Funded, active
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How do engineering faculty understand generative AI, and how do those mental models shape instructional decisions?
CAREER: Minds and Machines: Exploring Engineering Faculty Member Mental Models of Generative AI and Instructional Decisions
Investigating faculty mental models of generative AI in engineering education
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How do mental models of social-ecological systems influence engineering design decisions for sustainability?
Design for Sustainability: How Mental Models of Social-Ecological Systems Shape Engineering Design Decisions
Modeling social-ecological systems in engineering design decisions
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How can researchers combine qualitative judgment with open-source generative AI to scale thematic analysis without hiding methodological choices?
Using Large Language Models and Generative AI to Scale Qualitative Data Analysis
Leveraging open-source large language models and generative AI to create workflows to conduct large-scale qualitative data analysis
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What do US colleges and universities’ generative AI policies permit, prohibit, and leave unaddressed, and how have those policies changed since 2023?
Structures and Machines: An Interdisciplinary Approach to Mapping the Policy Implications of Generative AI in Higher Education
Analyzing existing policies related to AI in higher education across the US
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What do employers ask of engineers with master’s degrees, how has that changed over the past decade, and how well does it match what master’s students want from their careers?
The Engineering Master's Workforce: Leveraging Natural Language Processing Techniques to Understand Employer Demands and Student Goals
Studying labor market trends by analyzing job postings with natural language processing to understand employer demands and how they align with engineering master's student goals.
Completed
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How can NLP methods help engineering education researchers and instructors analyze text-rich learning data responsibly and at scale?
EAGER: Natural Language Processing for Teaching and Research in Engineering Education (NLPTREE)
Developing NLP pipelines for engineering education research
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Can language technology read medical students’ written work closely enough to assess their health systems citizenship reliably and at scale?
Operationalizing, Validating, and Scaling Health Systems Citizenship Assessment in Undergraduate Medical Education
Developing NLP and AI-based tools to support assessment of health systems citizenship and to characterize medical students' mental models of health systems.
Seed projects
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How has generative AI changed what students say and do in campus online communities since ChatGPT arrived?
Exploring student perceptions of generative AI expressed on social media
Large-scale qualitative analysis of opinions and perspectives about generative AI expressed on social media (e.g., Reddit). We will use NLP and LLM-assisted workflows to sample, code, and synthesize themes across communities over time.
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How are US states legislating on artificial intelligence, and how are they responding to the electricity demand of data centers?
A Scalable Approach to Policy Analysis
Use NLP and LLM-based techniques to analyze policy documents and legislation from state legislature sources (e.g., the National Conference of State Legislatures website), with a focus on workforce development, environmental, and energy policy.
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Which metaphors and analogies do instructors reach for when explaining difficult ideas, and does that change with how abstract the topic is?
Figurative Language in Educational Contexts
Analyze transcripts from course recordings (e.g., YouTube) to identify figurative language such as metaphors and analogies used by instructors when explaining difficult or abstract concepts. Use NLP and LLMs to facilitate identification and classification.
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Can an AI assistant grounded in self-regulated learning theory help students plan, monitor, and reflect on their learning without doing that thinking for them?
Scaffolding Student Self-Regulated Learning with Large Language Models
Use LLMs and self-regulated learning (SRL) theory to build a full-stack web app that scaffolds students across forethought, performance, and self-reflection phases (e.g., goal-setting, planning, monitoring, reflection).
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What drives the decisions engineering designers make, and can language models map those decisions and their causes from designers’ own words?
Characterizing Design Decisions with LLMs
Use LLMs to identify design decisions and the factors that influence them from qualitative text (e.g., interviews, design notebooks, reports). One outcome is constructing causal influence diagrams that represent decisions and relationships.
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Can vision language models read students’ concept maps of social-ecological systems as reliably as trained researchers, so systems thinking can be studied at scale?
Using Vision Language Models to Analyze Concept Maps
Use vision language models (VLMs) to analyze concept maps and other visualizations of complex systems. One application is to study how students represent and reason about social-ecological systems in engineering design.