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Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
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Henrietta Carbonel; Angelo Belardi; Jen Ross; Jean-Michel Jullien – Online Learning, 2025
The shift to distance education during the COVID-19 pandemic highlighted the potential and preference of online learners for remote assessment. Yet, concerns about academic integrity, especially with tools like ChatGPT, prompted a reevaluation of remote evaluation methods. Universities responded by returning to on-campus exams or relying on…
Descriptors: Distance Education, Computer Assisted Testing, Student Motivation, Integrity