Andrew Katz
Associate professor
Andrew Katz is an associate professor of Engineering Education at Virginia Tech, where he founded the IDEEAS Lab in 2019. He holds a PhD in Engineering Education from Purdue University.
His research asks how people in engineering reason, learn, and decide, and how AI can help researchers study those questions at scale without hiding the judgment calls along the way. The lab's work spans engineering ethics, how faculty think about teaching and assessment, student experience, sustainability, careers and the workforce, technology policy, and public perceptions of AI.
Much of the lab's methods work builds open, auditable workflows that use language models to read large bodies of text, such as the GATOS workflow for thematic analysis. His NSF CAREER project studies how engineering faculty understand generative AI and how those understandings shape what they teach. When a method works, the lab builds it into software others can use.
Research areas
- AI in engineering education
- Natural language processing
- Decision making systems
Advising
Projects
- How do engineering faculty understand generative AI, and how do those mental models shape instructional decisions?
- How do mental models of social-ecological systems influence engineering design decisions for sustainability?
- How can NLP methods help engineering education researchers and instructors analyze text-rich learning data responsibly and at scale?
- How can researchers combine qualitative judgment with open-source generative AI to scale thematic analysis without hiding methodological choices?
- What do US colleges and universities’ generative AI policies permit, prohibit, and leave unaddressed, and how have those policies changed since 2023?
Publications
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Extending Minimal Pairs with Ordinal Surprisal Curves and Entropy Across Applied Domains
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Thematic analysis with open-source generative AI and machine learning: A new method for inductive qualitative codebook development
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Using generative AI for large-scale qualitative analysis of social media posts to understand why people leave computer science
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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
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Expanding possibilities for generative AI in qualitative analysis: Fostering student feedback literacy through the application of a feedback quality rubric
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Automated Analysis of Knowledge Types in Computer Science Textbooks: A Natural Language Processing Approach to Understanding Epistemic Climate
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Leveraging Generative Text Models and Natural Language Processing to Perform Traditional Thematic Data Analysis
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Understanding instructor decision-making in engineering education for sustainable development: a comparison of institutions in Denmark and the United States
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Curriculum comparison: chemical and mechanical engineering education in the United States and Turkey
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Engineering students' interests in nonprofit and public policy careers: Applying a data-driven approach to identifying contributing factors
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A Reinforcement Learning Framework for N-Ary Document-Level Relation Extraction
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From Manual Coding to Machine Understanding: Students' Feedback Analysis
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How do ethics and diversity, equity, and inclusion relate in engineering? A systematic review
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Inspiring Sustainability in Undergraduate Engineering Programs
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Novel Approach Designing Interview Protocols with Generative Large Language Models to Study Mental Models and Engineering Design
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Paradigm Shift? Preliminary Findings of Engineering Faculty Members’ Mental Models of Assessment in the Era of Generative AI
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Skill Development of Engineering and Physical Science Doctoral Students: Understanding the Role of Advisor, Faculty, and Peer Interactions
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Stumbling Our Way Through Finding a Better Prompt: Using GPT-4 to Analyze Engineering Faculty’s Mental Models of Assessment
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Thematic Analysis with Open-Source Generative AI and Machine Learning: A New Method for Inductive Qualitative Codebook Development
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Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching
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Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching
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What engineering employers want: An analysis of technical and professional skills in engineering job advertisements
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Advanced Considerations in Quantitative Methods for New Directions in Engineering Education Research
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Advancing qualitative analysis: An exploration of the potential of generative AI and NLP in thematic coding
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Exploring Faculty Members' Conceptualizations of Diversity, Equity, and Inclusion in Engineering Education
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Exploring NLP-based Methods for Generating Engineering Ethics Assessment Qualitative Codebooks
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Exploring the Efficacy of ChatGPT in Analyzing Student Teamwork Feedback with an Existing Taxonomy
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Exploring the Impact of Engineering Projects in Community Service on Engineering Students’ Perspectives about Engineering as a Major
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How Participating in Extracurricular Activities Supports Dimensions of Student Wellness
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Promoting Research Quality to Study Mental Models of Ethics and Diversity, Equity, and Inclusion (DEI) in Engineering
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Pushing Ethics Assessment Forward in Engineering: NLP-Assisted Qualitative Coding of Student Responses
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The Utility of Large Language Models and Generative AI for Education Research
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Utilizing Natural Language Processing to Examine Self-Reflections in Self-Regulated Learning
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WIP: Faculty Use of Metaphors When Discussing Assessment
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A Thematic and Trend Analysis of Engineering Education for Sustainable Development
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An Empirical Study of Programming Languages Specified in Engineering Job Postings
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Analysis of Advances in Engineering Education Publications (2007-2020) to Examine Impact and Coverage of Topics
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Applying concepts from political science and economics to advance the study of engineering education
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Augmented Reality for Sustainable Collaborative Design
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Clustering-based unsupervised generative relation extraction
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Collateral Damage: Investigating the Impacts of COVID on STEM Professionals with Caregiving Responsibilities
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Defining Assessment: Foundation Knowledge Toward Exploring Engineering Faculty’s Assessment Mental Models
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Development of hybrid laboratory sessions during the COVID-19 Pandemic
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Students’ Feedback About Their Experiences in EPICS Using Natural Language Processing
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Understanding First-year Engineering Students’ Perceptions of Working with Real Stakeholders on a Design Project: A PBL Approach
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Using Natural Language Processing to Explore Undergraduate Students’ Perspectives of Social Class, Gender, and Race
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Using Sentiment Analysis to Evaluate First-year Engineering Students Teamwork Textual Feedback
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Work-in-Progress: Using Latent Dirichlet Allocation to uncover themes in student comments from peer evaluations of teamwork
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Civil Engineering Students’ Beliefs about Global Warming and Misconceptions about Climate Science
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Engineering ethics in engineering design courses: A preliminary investigation
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Factors associated with collaboration networks in ASEE conference papers
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Figurative language in computer education: Evidence from YouTube instructional videos
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Higher perceived design thinking traits and active learning in design courses motivate engineering students to tackle energy sustainability in their careers
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Predicting engineering students’ desire to address climate change in their careers: An exploratory study using responses from a U.S. National survey
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Taking stock: An Analysis of IJEE publications from 1996--2020 to examine impact and coverage of topics
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The correlation between undergraduate student diversity and the representation of women of color faculty in engineering
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Using natural language processing to facilitate student feedback analysis
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Your views can be my views: Understanding differences in paradigms held by traditionally marginalized students in engineering
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An Investigation of When and Where Ethics Appears in Undergraduate Engineering Curricula
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Civil Engineering Students’ Beliefs about the Technical and Social Implications of Global Warming and When Global Warming Will Impact Them Personally and Others
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Clustering-based Unsupervised Generative Relation Extraction
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Harvesting tweets for a better understanding of engineering students' first-year experiences
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Overcoming Challenges to Enhance a First Year Engineering Ethics Curriculum
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Reinforcement Learning-based N-ary Cross-Sentence Relation Extraction
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Using Chatbots as Smart Teaching Assistants for First-Year Engineering Students
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Monetizing Life May Be the Ethical Thing to Do
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Investigating influences on first-year engineering students’ views of ethics and social responsibility
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Learning from failures: Engineering education in an age of academic capitalism
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Factors related to faculty views of undergraduate engineering ethics education
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Telling it like it was: Histories of change in engineering ethics education
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Addressing the state of higher education in State of the Union Addresses
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Shadow codes of engineering ethics: An experiment in ethics imaginaries
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The revealing effects of disaster: A case study from Tulane University
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Educating for a revolution: Discerning together the Highlander idea and its lessons for ESJP’s work
Education
- Ph.D. in Engineering Education, Purdue University
- M.S. in Environmental Engineering, Texas A&M University
- B.S. in Chemical Engineering, Tulane University