Interactive Workshop: Multimodal, Multiparty Learning Analytics (MMLA)
Year: 2025
Type: conference-paper
Abstract: Multimodal, multiparty learning analytics – combining multi-ple data streams from several participants- has great promise in providing richer insights into learning processes. Yet there are significant technical, measurement and ethical challenges. The objectives of the workshop are to bring together a diverse group of researchers who are researching and developing mul-timodal learning analytics. Through a series of short presenta-tions and collaborative activities, the workshop participants will share their methodologies, illustrate techniques, demon-strate tools, and discuss challenges and solutions.
Authors: Peter Foltz, Gautam Biswas, Sidney D'Mello
Language: English
Subfield: Computer Science Applications
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W6930914618
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