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Outputs (32)

Partially-Supervised Metric Learning via Dimensionality Reduction of Text Embeddings using Transformer Encoders and Attention Mechanisms (2024)
Journal Article
Hodgson, R., Wang, J., Cristea, A. I., & Graham, J. (2024). Partially-Supervised Metric Learning via Dimensionality Reduction of Text Embeddings using Transformer Encoders and Attention Mechanisms. IEEE Access, https://doi.org/10.1109/access.2024.3403991

Real-world applications of word embeddings to downstream clustering tasks may experience limitations to performance, due to the high degree of dimensionality of the embeddings. In particular, clustering algorithms do not scale well when applied to hi... Read More about Partially-Supervised Metric Learning via Dimensionality Reduction of Text Embeddings using Transformer Encoders and Attention Mechanisms.

Recommender systems for teachers: The relation between social ties and the effectiveness of socially-based features (2023)
Journal Article
Yacobson, E., Toda, A. M., Cristea, A. I., & Alexandron, G. (2024). Recommender systems for teachers: The relation between social ties and the effectiveness of socially-based features. Computers & Education, 210, Article 104960. https://doi.org/10.1016/j.compedu.2023.104960

Open Educational Resources (OER) repositories provide teachers with a wide range of learning resources (LRs), enabling them to design various learning sequences. However, search & select in large OER repositories can be a daunting task for teachers.... Read More about Recommender systems for teachers: The relation between social ties and the effectiveness of socially-based features.

Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums (2023)
Journal Article
Alrajhi, L., Alamri, A., Pereira, F. D., Cristea, A. I., & Oliveira, E. H. T. (2023). Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums. User Modeling and User-Adapted Interaction, https://doi.org/10.1007/s11257-023-09381-y

In MOOCs, identifying urgent comments on discussion forums is an ongoing challenge. Whilst urgent comments require immediate reactions from instructors, to improve interaction with their learners, and potentially reducing drop-out rates—the task is d... Read More about Solving the imbalanced data issue: automatic urgency detection for instructor assistance in MOOC discussion forums.

Sim-GAIL: A generative adversarial imitation learning approach of student modelling for intelligent tutoring systems (2023)
Journal Article
Li, Z., Shi, L., Wang, J., Cristea, A. I., & Zhou, Y. (2023). Sim-GAIL: A generative adversarial imitation learning approach of student modelling for intelligent tutoring systems. Neural Computing and Applications, 35(34), 24369-24388. https://doi.org/10.1007/s00521-023-08989-w

The continuous application of artificial intelligence (AI) technologies in online education has led to significant progress, especially in the field of Intelligent Tutoring Systems (ITS), online courses and learning management systems (LMS). An impor... Read More about Sim-GAIL: A generative adversarial imitation learning approach of student modelling for intelligent tutoring systems.

Using deep learning to analyze the psychological effects of COVID-19 (2023)
Journal Article
Almeqren, M. A., Almegren, M., Alhayan, F., Cristea, A. I., & Pennington, D. R. (2023). Using deep learning to analyze the psychological effects of COVID-19. Frontiers in Psychology, 14, Article 962854. https://doi.org/10.3389/fpsyg.2023.962854

Problem: Sentiment Analysis (SA) automates the classification of the sentiment of people’s attitudes, feelings or reviews employing natural language processing (NLP) and computational approaches. Deep learning has recently demonstrated remarkable suc... Read More about Using deep learning to analyze the psychological effects of COVID-19.

The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation (2023)
Journal Article
Cristea, A. I., Alamri, A., Alshehri, M., Dwan Pereira, F., Toda, A. M., Harada T. de Oliveira, E., & Stewart, C. (2024). The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation. User Modeling and User-Adapted Interaction, 34(2), 323-374. https://doi.org/10.1007/s11257-023-09374-x

Massive Online Open Course (MOOC) platforms are considered a distinctive way to deliver a modern educational experience, open to a worldwide public. However, student engagement in MOOCs is a less explored area, although it is known that MOOCs suffer... Read More about The engage taxonomy: SDT-based measurable engagement indicators for MOOCs and their evaluation.

Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation (2023)
Journal Article
Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2023). Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation. AI open, 4, 19-32. https://doi.org/10.1016/j.aiopen.2023.05.001

This paper explores deep latent variable models for semi-supervised paraphrase generation, where the missing target pair for unlabelled data is modelled as a latent paraphrase sequence. We present a novel unsupervised model named variational sequence... Read More about Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation.

Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges (2023)
Journal Article
Pereira, F. D., Fonseca, S. C., Wiktor, S., Oliveira, D. B., Cristea, A. I., Benedict, A., …Oliveira, E. H. (2023). Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges. IEEE Access, 11, https://doi.org/10.1109/access.2023.3247189

Online judges (OJ) are a popular tool to support programming learning. However, one major issue with OJs is that problems are often put together without any associated meta-information that could, for example, be used to help classify problems. This... Read More about Toward Supporting CS1 Instructors and Learners With Fine-Grained Topic Detection in Online Judges.

How Personalization Affects Motivation in Gamified Review Assessments (2023)
Journal Article
Rodrigues, L., Palomino, P. T., Toda, A. M., Klock, A. C., Pessoa, M., Pereira, F. D., …Isotani, S. (2023). How Personalization Affects Motivation in Gamified Review Assessments. International Journal of Artificial Intelligence in Education, https://doi.org/10.1007/s40593-022-00326-x

Personalized gamification aims to address shortcomings of the one-size-fits-all (OSFA) approach in improving students’ motivations throughout the learning process. However, studies still focus on personalizing to a single user dimension, ignoring mul... Read More about How Personalization Affects Motivation in Gamified Review Assessments.