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