31 citations · 79 across the 20 of their papers we have counts for
21 papers
"Piecing Data Connections Together Like a Puzzle": Effects of Increasing Task Complexity on the Effectiveness of Data Storytelling Enhanced Visualisations
Mikaela Elizabeth Milesi, Paola Mejia-Domenzain, Laura Brandl +6
The emerging concept of data storytelling (DS) suggests that enhancing visualisations with annotations and narratives can make complex data more insightful than conventional visual…
Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes
Paola Mejia-Domenzain, Jibril Frej, Seyed Parsa Neshaei +5
Writing high-quality procedural texts is a challenging task for many learners. While example-based learning has shown promise as a feedback approach, a limitation arises when all l…
EduFair-Bench: Evaluating Pedagogical Fairness of LLM Tutors Across Student Demographics
Jiaxu Zhao, Bahar Radmehr, Fares Fawzi +2
Large language models (LLMs) are increasingly deployed as tutors, but it is unclear whether they support all students equally well. We introduce \textbf{EduFair-Bench}, a benchmark…
From Substitution to Scaffolding: Breaking the Self-Reinforcing Harm Cycle of AI in Education (and Beyond)
Lucile Favero, Juan Antonio Pérez-Ortiz, Tanja Käser +1
Artificial intelligence is being adopted in educational settings faster than its consequences are understood. We argue that the central risk is misalignment: AI that eliminates hum…
PIVOT: Preference-based Intervention Vectors for Pedagogical Tutor Steering
Fares Fawzi, Jiaxu Zhao, Tanya Nazaretsky +1
LLMs are increasingly used for conversational tutoring, but effective tutoring requires more than correct answers. Tutors must choose when to scaffold reasoning, hint, give feedbac…
Tracing Persona Vectors Through LLM Pretraining
Viktor Moskvoretskii, Dominik Glandorf, Jorge Medina Moreira +2
How large language models internally represent high-level behaviors is a core interpretability question with direct relevance to AI safety: it determines what we can detect, audit,…
Tailoring Scaffolding to Diagnostic Strategies: Theory-Informed LLM-Based Agents
Fatma Betul Gures, Tanya Nazaretsky, Tanja Kaser
Learning analytics systems increasingly integrate large language models (LLMs) to provide adaptive scaffolding in complex learning environments, yet personalization is often driven…
Structuring versus Problematizing: How LLM-based Agents Scaffold Learning in Diagnostic Reasoning
Fatma Betül Güreş, Tanya Nazaretsky, Seyed Parsa Neshaei +1
Supporting students in developing diagnostic reasoning is a key challenge across educational domains. Novices often face cognitive biases such as premature closure and over-relianc…
Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection
Isadora Salles, Paola Mejia-Domenzain, Vinitra Swamy +2
Clustering in education, particularly in large-scale online environments like MOOCs, is essential for understanding and adapting to diverse student needs. However, the effectivenes…
Graph Reasoning for Explainable Cold Start Recommendation
Jibril Frej, Marta Knezevic, Tanja Kaser
The cold start problem, where new users or items have no interaction history, remains a critical challenge in recommender systems (RS). A common solution involves using Knowledge G…
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning
Elena Grazia Gado, Tommaso Martorella, Luca Zunino +4
Intelligent Tutoring Systems (ITS) enhance personalized learning by predicting student answers to provide immediate and customized instruction. However, recent research has primari…
Towards Generalizable Agents in Text-Based Educational Environments: A Study of Integrating RL with LLMs
Bahar Radmehr, Adish Singla, Tanja Käser
There has been a growing interest in developing learner models to enhance learning and teaching experiences in educational environments. However, existing works have primarily focu…
Generative AI for Education (GAIED): Advances, Opportunities, and Challenges
Paul Denny, Sumit Gulwani, Neil T. Heffernan +4
This survey article has grown out of the GAIED (pronounced "guide") workshop organized by the authors at the NeurIPS 2023 conference. We organized the GAIED workshop as part of a c…
Intrinsic User-Centric Interpretability through Global Mixture of Experts
Vinitra Swamy, Syrielle Montariol, Julian Blackwell +3
In human-centric settings like education or healthcare, model accuracy and model explainability are key factors for user adoption. Towards these two goals, intrinsically interpreta…
Finding Paths for Explainable MOOC Recommendation: A Learner Perspective
Jibril Frej, Neel Shah, Marta Knežević +2
The increasing availability of Massive Open Online Courses (MOOCs) has created a necessity for personalized course recommendation systems. These systems often combine neural networ…
The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations
Vinitra Swamy, Jibril Frej, Tanja Käser
Explainable Artificial Intelligence (XAI) plays a crucial role in enabling human understanding and trust in deep learning systems. As models get larger, more ubiquitous, and pervas…
Understanding Revision Behavior in Adaptive Writing Support Systems for Education
Luca Mouchel, Thiemo Wambsganss, Paola Mejia-Domenzain +1
Revision behavior in adaptive writing support systems is an important and relatively new area of research that can improve the design and effectiveness of these tools, and promote…
Visualizing Self-Regulated Learner Profiles in Dashboards: Design Insights from Teachers
Paola Mejia-Domenzain, Eva Laini, Seyed Parsa Neshaei +2
Flipped Classrooms (FC) are a promising teaching strategy, where students engage with the learning material before attending face-to-face sessions. While pre-class activities are c…
RIPPLE: Concept-Based Interpretation for Raw Time Series Models in Education
Mohammad Asadi, Vinitra Swamy, Jibril Frej +3
Time series is the most prevalent form of input data for educational prediction tasks. The vast majority of research using time series data focuses on hand-crafted features, design…
Generalisable Methods for Early Prediction in Interactive Simulations for Education
Jade Maï Cock, Mirko Marras, Christian Giang +1
Interactive simulations allow students to discover the underlying principles of a scientific phenomenon through their own exploration. Unfortunately, students often struggle to lea…
Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs
Vinitra Swamy, Bahar Radmehr, Natasa Krco +2
Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainab…