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Exploring Fairness and Explainability in LLM-Generated Support for Online Learning Discussion Forums
Zifeng Liu; Wanli Xing; Xinyue Jiao; Chenglu Li – Journal of Learning Analytics, 2025
Large language models (LLMs) hold significant potential to enhance online learning by automating responses to learner queries and offering personalized, scalable support. However, concerns about bias in LLM-generated responses present challenges to their ethical and equitable use in educational settings. This study explores fairness and…
Descriptors: Artificial Intelligence, Natural Language Processing, Electronic Learning, Automation
Zifeng Liu; Wanli Xing; Chenglu Li; Fan Zhang; Hai Li; Victor Minces – Journal of Learning Analytics, 2025
Creativity is a vital skill in science, technology, engineering, and mathematics (STEM)-related education, fostering innovation and problem-solving. Traditionally, creativity assessments relied on human evaluations, such as the consensual assessment technique (CAT), which are resource-intensive, time-consuming, and often subjective. Recent…
Descriptors: Creativity, Elementary School Students, Artificial Intelligence, Man Machine Systems
Jonathan K. Foster; Peter Youngs; Rachel van Aswegen; Samarth Singh; Ginger S. Watson; Scott T. Acton – Journal of Learning Analytics, 2024
Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…
Descriptors: Learning Analytics, Automation, Classification, Artificial Intelligence
Rafael Ferreira Mello; Elyda Freitas; Luciano Cabral; Filipe Dwan Pereira; Luiz Rodrigues; Mladen Rakovic; Jackson Raniel; Dragan Gaševic – Journal of Learning Analytics, 2024
Learning analytics (LA) involves the measurement, collection, analysis, and reporting of data about learners and their contexts, aiming to understand and optimize both the learning process and the environments in which it occurs. Among many themes that the LA community considers, natural language processing (NLP) algorithms have been widely…
Descriptors: Literature Reviews, Learning Analytics, Natural Language Processing, Data Collection
Valentina Albano; Donatella Firmani; Luigi Laura; Jerin George Mathew; Anna Lucia Paoletti; Irene Torrente – Journal of Learning Analytics, 2023
Multiple-choice questions (MCQs) are widely used in educational assessments and professional certification exams. Managing large repositories of MCQs, however, poses several challenges due to the high volume of questions and the need to maintain their quality and relevance over time. One of these challenges is the presence of questions that…
Descriptors: Natural Language Processing, Multiple Choice Tests, Test Items, Item Analysis

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