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All Outputs (13)

A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data (2021)
Conference Proceeding
Sun, Z., Harit, A., Yu, J., Cristea, A., & Al Moubayed, N. (2021). A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data. . https://doi.org/10.1109/ijcnn52387.2021.9533981

This research focuses on semi-supervised classification tasks, specifically for graph-structured data under datascarce situations. It is known that the performance of conventional supervised graph convolutional models is mediocre at classification ta... Read More about A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data.

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.

Forum-based Prediction of Certification in Massive Open Online Courses (2021)
Conference Proceeding
Alsheri, M. A., Alamri, A., Cristea, A. I., & Stewart, C. D. (2021). Forum-based Prediction of Certification in Massive Open Online Courses.

Massive Open Online Courses (MOOCs) have been suffering a very level of low course certification (less than 1% of the total number of enrolled students on a given online course opt to purchase its certificate), although MOOC platforms have been offer... Read More about Forum-based Prediction of Certification in Massive Open Online Courses.

A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs (2021)
Conference Proceeding
Sun, Z., Harit, A., Yu, J., Cristea, A. I., & Shi, L. (2021). A Brief Survey of Deep Learning Approaches for Learning Analytics on MOOCs. In A. Cristea, & C. Troussas (Eds.), . https://doi.org/10.1007/978-3-030-80421-3_4

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.

Wide-Scale Automatic Analysis of 20 Years of ITS Research (2021)
Conference Proceeding
Hodgson, R., Cristea, A., Shi, L., & Graham, J. (2021). Wide-Scale Automatic Analysis of 20 Years of ITS Research. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (8-21). https://doi.org/10.1007/978-3-030-80421-3_2

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.

Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students (2021)
Conference Proceeding
Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021). Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (211-223). https://doi.org/10.1007/978-3-030-80421-3_23

The classroom environment is a major contributor to the learning process in schools. Young students are affected by different details in their academic progress, be it their own characteristics, their teacher’s or their peers’. The combination of the... Read More about Agent-based Simulation of the Classroom Environment to Gauge the Effect of Inattentive or Disruptive Students.

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.

A Survey of Collaborative Reinforcement Learning: Interactive Methods and Design Patterns (2021)
Conference Proceeding
Li, Z., Shi, L., Cristea, A. I., & Zhou, Y. (2021). A Survey of Collaborative Reinforcement Learning: Interactive Methods and Design Patterns. . https://doi.org/10.1145/3461778.3462135

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.

Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours (2021)
Conference Proceeding
Alharbi, K., Cristea, A. I., Shi, L., Tymms, P., & Brown, C. (2021). Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours. In I. Roll, M. Danielle, S. Sergey, L. Rose, & D. Vania (Eds.), Artificial Intelligence in Education Lecture Notes in Computer Science (48-53). https://doi.org/10.1007/978-3-030-78270-2_8

Schoolchildren's academic progress is known to be affected by the classroom environment. It is important for teachers and administrators to under-stand their pupils' status and how various factors in the classroom may affect them, as it can help them... Read More about Agent-based Classroom Environment Simulation: the Effect of Disruptive Schoolchildren’s Behaviour versus Teacher Control over Neighbours.

Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners (2021)
Conference Proceeding
Pereira, F. D., Oliveira, E. H. T. D., Oliveira, D. B. F. D., Carvalho, L. S. G. D., & Cristea, A. I. (2021). Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners. . https://doi.org/10.5753/educomp_estendido.2021.14853

Building predictive models to estimate the learner performance in the beginning of CS1 courses is essential in education to allow early interventions. However, the educational literature notes the lack of studies on early learner behaviours that can... Read More about Interpretable AI to Understand Early Effective and Ineffective Programming Behaviours from CS1 Learners.

COVID-19’s Impact on the Telecommunications Companies (2021)
Conference Proceeding
Almuqren, L., & Cristea, A. I. (2021). COVID-19’s Impact on the Telecommunications Companies. In Á. Rocha, H. Adeli, G. Dzemyda, F. Moreira, & A. M. R. Correia (Eds.), WorldCIST 2021: Trends and Applications in Information Systems and Technologies (318-327). https://doi.org/10.1007/978-3-030-72654-6_31

Now the world is witnessing most significant challenges due the Covid-19 crisis. Beyond health effects, it has social and economic effects. With the enormous amount of data available and the widespread use of social web globally, research can and sho... Read More about COVID-19’s Impact on the Telecommunications Companies.

Towards a Human-AI hybrid system for categorising programming problems (2021)
Conference Proceeding
Pereira, F. D., Piris, F., Cristo da Fonseca, S., Cristea, A., Oliveira, E. H., Carvalho, L., & Fernandes, D. (2021). Towards a Human-AI hybrid system for categorising programming problems. In SIGCSE '21: Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (94-100). https://doi.org/10.1145/3408877.3432422

As programming skills are increasingly required world-wide and across disciplines, many students use online platforms that provide automatic feedback through a Programming Online Judge (POJ) mechanism. POJs are very popular e-learning tools, boasting... Read More about Towards a Human-AI hybrid system for categorising programming problems.