Outputs (129)

Urgency Analysis of Learners’ Comments: An Automated Intervention Priority Model for MOOC (2021)
Book Chapter
Alrajhi, L., Alamri, A., Pereira, F. D., & Cristea, A. I. (2021). Urgency Analysis of Learners’ Comments: An Automated Intervention Priority Model for MOOC. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (148-160). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_18

Recently, the growing number of learners in Massive Open Online Course (MOOC) environments generate a vast amount of online comments via social interactions, general discussions, expressing feelings or asking for help. Concomitantly, learner dropout,... Read More about Urgency Analysis of Learners’ Comments: An Automated Intervention Priority Model for MOOC.

Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification (2021)
Book Chapter
Aljohani, T., & Cristea, A. I. (2021). Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (136-147). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_17

Massive Open Online Courses (MOOCs) have become universal learning resources, and the COVID-19 pandemic is rendering these platforms even more necessary. These platforms also bring incredible diversity of learners in terms of their traits. A research... Read More about Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification.

Predicting Certification in MOOCs based on Students’ Weekly Activities (2021)
Book Chapter
Alshehri, M., Alamri, A., & Cristea, A. I. (2021). Predicting Certification in MOOCs based on Students’ Weekly Activities. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (173-185). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_20

Massive Open Online Courses (MOOCs) have been growing rapidly, offering low-cost knowledge for both learners and content providers. However, currently there is a very low level of course purchasing (less than 1% of the total number of enrolled studen... Read More about Predicting Certification in MOOCs based on Students’ Weekly Activities.

A Recommender System Based on Effort: Towards Minimising Negative Affects and Maximising Achievement in CS1 Learning (2021)
Book Chapter
Pereira, F. D., Junior, H. B., Rodriquez, L., Toda, A., Oliveira, E. H., Cristea, A. I., …Isotani, S. (2021). A Recommender System Based on Effort: Towards Minimising Negative Affects and Maximising Achievement in CS1 Learning. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (466-480). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_51

Programming online judges (POJs) are autograders that have been increasingly used in introductory programming courses (also known as CS1) since these systems provide instantaneous and accurate feedback for learners’ codes solutions and reduce instruc... Read More about A Recommender System Based on Effort: Towards Minimising Negative Affects and Maximising Achievement in CS1 Learning.

Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums (2021)
Presentation / Conference Contribution
Yu, J., Alrajhi, L., Harit, A., Sun, Z., Cristea, A. I., & Shi, L. (2021, June). Exploring Bayesian Deep Learning for Urgent Instructor Intervention Need in MOOC Forums. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual

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.

Wide-Scale Automatic Analysis of 20 Years of ITS Research (2021)
Presentation / Conference Contribution
Hodgson, R., Cristea, A., Shi, L., & Graham, J. (2021, June). Wide-Scale Automatic Analysis of 20 Years of ITS Research. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual

The analysis of literature within a research domain can provide significant value during preliminary research. While literature reviews may provide an in-depth understanding of current studies within an area, they are limited by the number of studies... Read More about Wide-Scale Automatic Analysis of 20 Years of ITS Research.

A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs (2021)
Presentation / Conference Contribution
Sun, Z., Harit, A., Yu, J., Cristea, A. I., & Shi, L. (2021, June). A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs. Presented at Intelligent Tutoring Systems, Athens, Greece / Virtual

Massive Open Online Course (MOOC) systems have become prevalent in recent years and draw more attention, a.o., due to the coronavirus pandemic’s impact. However, there is a well-known higher chance of dropout from MOOCs than from conventional off-lin... Read More about A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs.

Encouraging Teacher-sourcing of Social Recommendations Through Participatory Gamification Design (2021)
Book Chapter
Toda Yacobson, E., Cristea, A., & Alexandron, G. I. (2021). Encouraging Teacher-sourcing of Social Recommendations Through Participatory Gamification Design. In A. Cristea, & C. I. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (418-429). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_46

Teachers and learners who search for learning materials in open educational resources (OER) repositories greatly benefit from feedback and reviews left by peers who have activated these resources in their class. Such feedback can also fuel social-bas... Read More about Encouraging Teacher-sourcing of Social Recommendations Through Participatory Gamification Design.

An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach (2021)
Journal Article
Almuqren, L., Alrayes, F. S., & Cristea, A. I. (2021). An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach. Future Internet, 13(7), Article 175. https://doi.org/10.3390/fi13070175

With the rising growth of the telecommunication industry, the customer churn problem has grown in significance as well. One of the most critical challenges in the data and voice telecommunication service industry is retaining customers, thus reducing... Read More about An Empirical Study on Customer Churn Behaviours Prediction Using Arabic Twitter Mining Approach.

A Survey of Collaborative Reinforcement Learning: Interactive Methods and Design Patterns (2021)
Presentation / Conference Contribution
Li, Z., Shi, L., Cristea, A. I., & Zhou, Y. (2023, June). A Survey of Collaborative Reinforcement Learning: Interactive Methods and Design Patterns. Presented at ACM Designing Interactive Systems (DIS), Virtual

Recently, methods enabling humans and Artificial Intelligent (AI) agents to collaborate towards improving the efficiency of Reinforcement Learning - also called Collaborative Reinforcement Learning (CRL) - have been receiving increasing attention. In... Read More about A Survey of Collaborative Reinforcement Learning: Interactive Methods and Design Patterns.