45 citations · 64 across the 7 of their papers we have counts for
4 papers · 1 filter
Neural-Symbolic Knowledge Tracing: Injecting Educational Knowledge into Deep Learning for Responsible Learner Modelling
Danial Hooshyar, Gustav Šír, 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…
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 Šíř +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 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…
Augmenting deep neural networks with symbolic knowledge: Towards trustworthy and interpretable AI for education
Danial Hooshyar, Roger Azevedo, Yeongwook Yang
Artificial neural networks (ANNs) have shown to be amongst the most important artificial intelligence (AI) techniques in educational applications, providing adaptive educational se…