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Hu, Yuanyuan; Donald, Claire; Giacaman, Nasser – International Journal of Artificial Intelligence in Education, 2023
This paper investigates using multi-label deep learning approach to extending the understanding of cognitive presence in MOOC discussions. Previous studies demonstrate the challenges of subjectivity in manual categorisation methods. Training automatic single-label classifiers may preserve this subjectivity. Using a triangulation approach, we…
Descriptors: Classification, MOOCs, Artificial Intelligence, Intelligent Tutoring Systems
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Hu, Yuanyuan; Donald, Claire; Giacaman, Nasser – International Review of Research in Open and Distributed Learning, 2022
As large-scale, sophisticated open and distance learning environments expand in higher education globally, so does the need to support learning at scale in real time. Valid, reliable rubrics of critical discourse are an essential foundation for developing artificial intelligence tools that automatically analyse learning in educator-student…
Descriptors: Validity, Scoring Rubrics, Automation, Classification
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Hu, Yuanyuan; Donald, Claire; Giacaman, Nasser – International Journal of Educational Technology in Higher Education, 2022
Automatic analysis of the myriad discussion messages in large online courses can support effective educator-learner interaction at scale. Robust classifiers are an essential foundation for the use of automatic analysis of cognitive presence in practice. This study reports on the application of a revised machine learning approach, which was…
Descriptors: MOOCs, Philosophy, Artificial Intelligence, Computer Mediated Communication