22 citations · 37 across the 20 of their papers we have counts for
21 papers
The Correct Answer Trap: Pedagogically-Grounded Detection and Feedback for Hidden Misconceptions
Moiz Imran, Sahan Bulathwela
Automated feedback systems that rely on answer correctness will reinforce, rather than address, misconceptions when students reach the correct answer through flawed reasoning. We i…
Tool Calling is Linearly Readable and Steerable in Language Models
Zekun Wu, Ze Wang, Seonglae Cho +4
Language-model agents can take real actions by calling tools, so choosing the wrong tool can cause errors that are difficult to undo. Most evaluations only observe the tool choice…
Catching The Correct Answer Trap: Characterising AI Tutor Blind Spots When Analysing Student Reasoning
Moiz Imran, Sahan Bulathwela
Intelligent tutoring systems increasingly provide automated feedback on student work, but robust feedback requires assessing reasoning, not only final answers. We study a failure m…
Mix and Match: Context Pairing for Scalable Topic-Controlled Educational Summarisation
Nathikan Yodthapa, Thanapong Intharah, Sahan Bulathwela
Topic-controlled summarisation enables users to generate summaries focused on specific aspects of source documents. This paper investigates a data augmentation strategy for trainin…
Gaze to Insight: A Scalable AI Approach for Detecting Gaze Behaviours in Face-to-Face Collaborative Learning
Junyuan Liang, Qi Zhou, Sahan Bulathwela +1
Previous studies have illustrated the potential of analysing gaze behaviours in collaborative learning to provide educationally meaningful information for students to reflect on th…
Examining Student Interactions with a Pedagogical AI-Assistant for Essay Writing and their Impact on Students Writing Quality
Wicaksono Febriantoro, Qi Zhou, Wannapon Suraworachet +4
The dynamic nature of interactions between students and GenAI, as well as their relationship to writing quality, remains underexplored. While most research has examined how general…
Scaffolding Reshapes Dialogic Engagement in Collaborative Problem Solving: Comparative Analysis of Two Approaches
Kester Wong, Feng Shihui, Sahan Bulathwela +1
Supporting learners during Collaborative Problem Solving (CPS) is a necessity. Existing studies have compared scaffolds with maximal and minimal instructional support by studying t…
Towards Synergistic Teacher-AI Interactions with Generative Artificial Intelligence
Mutlu Cukurova, Wannapon Suraworachet, Qi Zhou +1
Generative artificial intelligence (GenAI) is increasingly used in education, posing significant challenges for teachers adapting to these changes. GenAI offers unprecedented oppor…
Next Token Knowledge Tracing: Exploiting Pretrained LLM Representations to Decode Student Behaviour
Max Norris, Kobi Gal, Sahan Bulathwela
Modelling student knowledge is a key challenge when leveraging AI in education, with major implications for personalised learning. The Knowledge Tracing (KT) task aims to predict h…
Exploring Human-AI Complementarity in CPS Diagnosis Using Unimodal and Multimodal BERT Models
Kester Wong, Sahan Bulathwela, Mutlu Cukurova
Detecting collaborative problem solving (CPS) indicators from dialogue using machine learning techniques is a significant challenge for the field of AI in Education. Recent studies…
Rethinking the Potential of Multimodality in Collaborative Problem Solving Diagnosis with Large Language Models
K. Wong, B. Wu, S. Bulathwela +1
Detecting collaborative and problem-solving behaviours from digital traces to interpret students' collaborative problem solving (CPS) competency is a long-term goal in the Artifici…
A Novel Approach to Scalable and Automatic Topic-Controlled Question Generation in Education
Ziqing Li, Mutlu Cukurova, Sahan Bulathwela
The development of Automatic Question Generation (QG) models has the potential to significantly improve educational practices by reducing the teacher workload associated with creat…
Towards Auditing Large Language Models: Improving Text-based Stereotype Detection
Wu Zekun, Sahan Bulathwela, Adriano Soares Koshiyama
Large Language Models (LLM) have made significant advances in the recent past becoming more mainstream in Artificial Intelligence (AI) enabled human-facing applications. However, L…
TrueLearn: A Python Library for Personalised Informational Recommendations with (Implicit) Feedback
Yuxiang Qiu, Karim Djemili, Denis Elezi +3
This work describes the TrueLearn Python library, which contains a family of online learning Bayesian models for building educational (or more generally, informational) recommendat…
Scalable Educational Question Generation with Pre-trained Language Models
Sahan Bulathwela, Hamze Muse, Emine Yilmaz
The automatic generation of educational questions will play a key role in scaling online education, enabling self-assessment at scale when a global population is manoeuvring their…
Pre-Training With Scientific Text Improves Educational Question Generation
Hamze Muse, Sahan Bulathwela, Emine Yilmaz
With the boom of digital educational materials and scalable e-learning systems, the potential for realising AI-assisted personalised learning has skyrocketed. In this landscape, th…
Towards Proactive Information Retrieval in Noisy Text with Wikipedia Concepts
Tabish Ahmed, Sahan Bulathwela
Extracting useful information from the user history to clearly understand informational needs is a crucial feature of a proactive information retrieval system. Regarding understand…
Can Population-based Engagement Improve Personalisation? A Novel Dataset and Experiments
Sahan Bulathwela, Meghana Verma, Maria Perez-Ortiz +2
This work explores how population-based engagement prediction can address cold-start at scale in large learning resource collections. The paper introduces i) VLE, a novel dataset t…
Watch Less and Uncover More: Could Navigation Tools Help Users Search and Explore Videos?
Maria Perez-Ortiz, Sahan Bulathwela, Claire Dormann +6
Prior research has shown how 'content preview tools' improve speed and accuracy of user relevance judgements across different information retrieval tasks. This paper describes a no…
Semantic TrueLearn: Using Semantic Knowledge Graphs in Recommendation Systems
Sahan Bulathwela, María Pérez-Ortiz, Emine Yilmaz +1
In informational recommenders, many challenges arise from the need to handle the semantic and hierarchical structure between knowledge areas. This work aims to advance towards buil…
Could AI Democratise Education? Socio-Technical Imaginaries of an EdTech Revolution
Sahan Bulathwela, María Pérez-Ortiz, Catherine Holloway +1
Artificial Intelligence (AI) in Education has been said to have the potential for building more personalised curricula, as well as democratising education worldwide and creating a…