Outputs (5)

Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model (2021)
Journal Article
Pereira, F. D., Fonseca, S. C., Oliveira, E. H., Cristea, A. I., Bellhauser, H., Rodrigues, L., …Carvalho, L. S. (2021). Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model. IEEE Access, 9, 117097-117119. https://doi.org/10.1109/access.2021.3105956

Predicting student performance as early as possible and analysing to which extent initial student behaviour could lead to failure or success is critical in introductory programming (CS1) courses, for allowing prompt intervention in a move towards all... Read More about Explaining Individual and Collective Programming Students’ Behavior by Interpreting a Black-Box Predictive Model.

Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations (2021)
Journal Article
Aljohani, T., & Cristea, A. I. (2021). Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations. Frontiers in Research Metrics and Analytics, 6, Article 673928. https://doi.org/10.3389/frma.2021.673928

Massive Open Online Courses (MOOCs) have become universal learning resources, and the COVID-19 pandemic is rendering these platforms even more necessary. In this paper, we seek to improve Learner Profiling (LP), i.e. estimating the demographic charac... Read More about Learners Demographics Classification on MOOCs During the COVID-19: Author Profiling via Deep Learning Based on Semantic and Syntactic Representations.

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.

AraCust: a Saudi Telecom Tweets corpus for sentiment analysis (2021)
Journal Article
Almuqren, L., & Cristea, A. (2021). AraCust: a Saudi Telecom Tweets corpus for sentiment analysis. PeerJ Computer Science, 7, Article e510. https://doi.org/10.7717/peerj-cs.510

Comparing Arabic to other languages, Arabic lacks large corpora for Natural Language Processing (Assiri, Emam & Al-Dossari, 2018; Gamal et al., 2019). A number of scholars depended on translation from one language to another to construct their corpus... Read More about AraCust: a Saudi Telecom Tweets corpus for sentiment analysis.

Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs (2021)
Journal Article
Alshehri, M., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021). Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs. International Journal of Artificial Intelligence in Education, 31(2), 215-233. https://doi.org/10.1007/s40593-021-00246-2

Since their ‘official’ emergence in 2012 (Gardner and Brooks 2018), massive open online courses (MOOCs) have been growing rapidly. They offer low-cost education for both students and content providers; however, currently there is a very low level of... Read More about Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs.