Predicting the Risk of Ultimate Low Ratings in Online Courses Using Machine Learning: Analyzing Engagement and Complexity for AI-Driven Early Instructional Communication Interventions

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dc.contributor.authorObada Kraishan
dc.contributor.authorKulsawasd Jitkajornwanich
dc.contributor.authorNattadet Vijaranakul
dc.contributor.authorKerk F. Kee
dc.date.accessioned2026-05-08T19:26:23Z
dc.date.issued2026-1-1
dc.identifier.doi10.1007/978-3-032-06658-9_13
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/20595
dc.publisherStudies in computational intelligence
dc.subjectOnline Learning and Analytics
dc.subjectIntelligent Tutoring Systems and Adaptive Learning
dc.subjectExplainable Artificial Intelligence (XAI)
dc.titlePredicting the Risk of Ultimate Low Ratings in Online Courses Using Machine Learning: Analyzing Engagement and Complexity for AI-Driven Early Instructional Communication Interventions
dc.typeBook-chapter

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