6 papers
Large Language Models as Students Who Think Aloud: Overly Coherent, Verbose, and Confident
Conrad Borchers, Jill-Jênn Vie, Roger Azevedo
Large language models (LLMs) are increasingly embedded in AI-based tutoring systems. Can they faithfully model novice reasoning and metacognitive judgments? Existing evaluations em…
Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modelling
Danial Hooshyar, Gustav Å Ãr, Yeongwook Yang +6
The growing use of artificial intelligence (AI) in education, particularly large language models (LLMs), has increased interest in intelligent tutoring systems. However, LLMs often…
Unlocking Open-Player-Modeling-enhanced Game-Based Learning: The Open Player Socially Analytical Intelligence Architecture
Zhiyu Lin, Boyd Fox, Devon Mckee +7
Game-Based Learning (GBL) is a learner-engaging pedagogical methodology, yet adapting games to heterogeneous learners requires transparent, real-time Open Player Models (OPMs). We…
Problems With Large Language Models for Learner Modelling: Why LLMs Alone Fall Short for Responsible Tutoring in K--12 Education
Danial Hooshyar, Yeongwook Yang, Gustav Å ÃÅ +4
The rapid rise of large language model (LLM)-based tutors in K--12 education has fostered a misconception that generative models can replace traditional learner modelling for adapt…
Towards responsible AI for education: Hybrid human-AI to confront the Elephant in the room
Danial Hooshyar, Gustav Å Ãr, Yeongwook Yang +5
Despite significant advancements in AI-driven educational systems and ongoing calls for responsible AI for education, several critical issues remain unresolved -- acting as the ele…
Towards Responsible and Trustworthy Educational Data Mining: Comparing Symbolic, Sub-Symbolic, and Neural-Symbolic AI Methods
Danial Hooshyar, Eve Kikas, Yeongwook Yang +4
Given the demand for responsible and trustworthy AI for education, this study evaluates symbolic, sub-symbolic, and neural-symbolic AI (NSAI) in terms of generalizability and inter…