31 citations · 79 across the 20 of their papers we have counts for
8 papers · 1 filter
"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…