In the age of artificial intelligence (AI), providing learners with suitable and sufficient explanations of AI-based recommendation algorithm's output becomes essential to enable them to make an informed decision about it. However, the rapid development of AI approaches for educational recommendations and their explainability is not accompanied by an equal level of evidence-based experimentation to evaluate the learning effect of those explanations. To address this issue, we propose an experimental web-based tool for evaluating multimodal and large language model (LLM) based explainability approaches. Our tool provides a comprehensive set of modular, interactive, and customizable explainability elements, which researchers and educators can utilize to study the role of individual and hybrid explainability methods. We design a two-stage evaluation of the proposed tool, with learners and with educators. Our preliminary results from the first stage show high acceptance of the tool's components, user-friendliness, and an induced motivation to use the explanations for exploring more information about the recommendation.
Automatic Mind Wandering Detection in Educational Settings: A Systematic Review and Multimodal Benchmarking
Technical University of Munich（慕尼黑工业大学）；Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心）；Leibniz-Institut für Wissensmedien（莱布尼茨知识媒体研究所）；Eberhard Karls University of Tübingen（蒂宾根大学）；Hector Research Institute of Education Sciences and Psychology（海克托教育科学与心理学研究所）
Enhancing Online Learning by Integrating Biosensors and Multimodal Learning Analytics for Detecting and Predicting Student Behavior: A Review
Department of Computer Science Engineering, Universidad Autónoma de Madrid（马德里自治大学计算机科学工程系）；Digital Futures Institute, Teachers College Columbia University（哥伦比亚大学教师学院数字未来研究所）
The Agency Gap in AI-Supported Writing: How Reactive and Proactive Agent Designs Shape Multimodal Reasoning
Centre for Learning Analytics at Monash, Faculty of Information Technology, Monash University（莫纳什大学信息技术学院学习分析中心）；Faculty of Education and School of Computing & Data Science, The University of Hong Kong（香港大学教育学院及计算与数据科学学院）；School of Education, Tsinghua University（清华大学教育学院）
