Research & Publications
Research Strands
My work moves across three interconnected strands. Click a circle to explore how they relate:
Educators define learning, for people and for machines.
Methodology
I combine large-scale evidence synthesis with in-depth qualitative inquiry and iterative design. Each method feeds the next: reviews surface gaps, mixed methods explore them, statistics test claims, and design-based research translates findings into tools educators can actually use.
Meta-analyses
Surveys · Interviews · Interventions
ONA · effect sizes
In-vivo prototyping
Journal Articles & Book Chapters
Google Scholar · Citation: 240 · h-index: 2
2026
Tutor, Not Solver: Designing a Guardrailed AI Assistant for Learning in Higher Education: A Design Case of PeteChat arXiv preprint
Li, B., *Tan, L., Zakharov, W., Qiu, Q., & Acton, C. · arXiv:2606.09845
From Answer Bot to Course Tutor: A Practical Design Case of a Guardrailed AI Assistant in Higher Education In Press
Li, B., *Tan, L., Zakharov, W., Qiu, Q., & Acton, C. · Invited book chapter, Springer
Doubao as a GenAI Scaffold in Senior High School EFL Writing Q2
Wang, S. & *Tan, L. · Psicologia Educativa, 14, 19–33
2025
Two Years of Innovation: A Systematic Review of Empirical GenAI Research in Language Learning Q1 · IF = 23.4
Li, B., *Tan, L.Y., Wang, C., & Lowell, V. · Computers and Education: AI, 9, 100445
Pointing to Context from a Relevance Theory Perspective: Human vs. Machine Interpreting
*Tan, L.Y. & Gao, L. · Mediterranean Journal of Social Sciences, 16(3), 1
Earlier version presented at the XXIInd International CALL Conference, Tokyo, Japan (2024).
Conference Presentations & Invited Talks
Conf Scaffolding Extramural GAI-mediated Informal Digital Learning of English for Pragmatic Competence: An Epistemic Network Analysis Upcoming
*Tan, L., Lowell, V., Li, B., & Fei, X. · AECT International Convention, Chicago, IL · Oct 2026
Conf A Design Case of PeteChat: Designing AI Tutors That Teach Students How to Think, Not What to Answer Upcoming
Li, B., Tan, L., Zakharov, W., Qiu, Q., & Acton, C. · AECT International Convention, Chicago, IL · Oct 2026
Talk Clawdbot Unboxed: What It Does, Why It’s Hot, and Where It Breaks
Tan, L. · Invited talk, AI Lunch and Learn Series, Purdue College of Education
A hands-on unboxing of Clawdbot for the College of Education AI community · poster and slides on the talk page.
Conf Assessing the Effects of Extramural GAI-mediated IDLE on Pragmatic Competence
Tan, L., Lowell, V. & Li, B. · Purdue AI in P-12 Conference, West Lafayette, IN
Conf Artificial Authenticity and Academic Integrity in an Age of Generative AI
Li, B., Wang, J., & Tan, L. · AECT International Convention, Las Vegas, NV
Conf Pointing to Context from a Relevance Theory Perspective: A Comparative Study of Human and Machine Interpreting
Tan, L. · XXIInd International CALL Conference, Tokyo, Japan · Sep 2024
Conf Exploring the Extracurricular Development of AI-Assisted English Learners: A Phenomenological Exploration
Tan, L. & Zhang, Y. · 3rd International Conference on Sociocultural Theory and Foreign Language Research, Guangdong, China · May 2024
Research Training
Modern Meta-Analysis Research Institute (MMARI) NSF-funded
Chicago, IL · July 2026
Selected participant in an NSF-funded training institute on modern meta-analysis hosted by Georgia State University, learning from Terri Pigott, Ryan Williams, and Elizabeth Tipton, together with the institute’s graduate students. The program covered effect-size computation and synthesis workflows in R/RStudio and Open Science practices for transparent, reproducible evidence synthesis. This training directly supports my evidence-synthesis research line.
