Outputs (2)

MOOCSent: a Sentiment Predictor for Massive Open Online Courses (2021)
Conference Proceeding
Alsheri, M. A., Alrajhi, L. M., Alamri, A., & Cristea, A. I. (2021). MOOCSent: a Sentiment Predictor for Massive Open Online Courses.

One key type of Massive Open Online Course (MOOC) data is the learners’ social interaction (forum). While several studies have analysed MOOC forums to predict learning outcomes, analysing learners’ sentiments in education and, specifically, in MOOCs,... Read More about MOOCSent: a Sentiment Predictor for Massive Open Online Courses.

Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums (2021)
Conference Proceeding
Yu, J., Alrajhi, L., Harit, A., Sun, Z., Cristea, A. I., & Shi, L. (2021). Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums. In A. I. Cristea, & C. Troussos (Eds.), Intelligent Tutoring Systems (78-90). https://doi.org/10.1007/978-3-030-80421-3_10

Massive Open Online Courses (MOOCs) have become a popular choice for e-learning thanks to their great flexibility. However, due to large numbers of learners and their diverse backgrounds, it is taxing to offer real-time support. Learners may post the... Read More about Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums.