Developing AI into Explanatory Supporting Models: An Explanation-visualized Deep Learning Prototype for Computer Supported Collaborative Learning

Haoyu Chen*, Esther Tan, Yoon Lee, S. Praharaj, M.M. Specht, Guoying Zhao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

Using Artificial Intelligence (AI) and machine learning technologies to automatically mine latent patterns from educational data holds great potential to inform teaching and learning practices. However, the current AI technology mostly works as “black box” - only the inputs and the corresponding outputs are available, which largely impedes researchers from gaining access to explainable feedback. This interdisciplinary work presents an explainable AI prototype with visualized explanations as feedback for computer-supported collaborative learning (CSCL). This research study seeks to provide interpretable insights with machine learning technologies for multimodal learning analytics (MMLA) by introducing two different explanatory machine learning-based models (neural network and Bayesian network) in different manners (end-to-end learning and probabilistic analysis) and for the same goal - provide explainable and actionable feedback. The prototype is applied to the real-world collaborative learning scenario with data-driven learning based on sensor-data from multiple modalities which can assess collaborative learning processes and render explanatory real-time feedback.
Original languageEnglish
Title of host publicationThe Interdisciplinarity of the Learning Sciences Proceedings
PublisherInternational Society of the Learning Sciences
Pages1133-1140
Number of pages8
Volume2
Publication statusPublished - Jun 2020
Event14th international conference of the learning sciences - Online, Nashville, United States
Duration: 19 Jun 202023 Jun 2020
https://www.isls.org/annual-meeting/annual-meetings-highlights/

Conference

Conference14th international conference of the learning sciences
Abbreviated titleICLS 2020
Country/TerritoryUnited States
CityNashville
Period19/06/2023/06/20
Internet address

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