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.

Gamification suffers from the novelty effect but benefits from the familiarization effect: Findings from a longitudinal study (2022)
Journal Article
Rodrigues, L., Pereira, F. D., Toda, A. M., Palomino, P. T., Pessoa, M., Carvalho, L. S. G., …Isotani, S. (2022). Gamification suffers from the novelty effect but benefits from the familiarization effect: Findings from a longitudinal study. International Journal of Educational Technology in Higher Education, 19(1), https://doi.org/10.1186/s41239-021-00314-6

There are many claims that gamification (i.e., using game elements outside games) impact decreases over time (i.e., the novelty effect). Most studies analyzing this effect focused on extrinsic game elements, while fictional and collaborative competit... Read More about Gamification suffers from the novelty effect but benefits from the familiarization effect: Findings from a longitudinal study.

Predicting STC Customers' Satisfaction Using Twitter (2022)
Journal Article
Almuqren, L., & Cristea, A. I. (2023). Predicting STC Customers' Satisfaction Using Twitter. IEEE Transactions on Computational Social Systems, 10(1), 204-210. https://doi.org/10.1109/tcss.2021.3135719

The telecom field has changed accordingly with the emergence of new technologies. This is the case with the telecom market in Saudi Arabia, which expanded in 2003 by attracting new investors. As a result, the Saudi telecom market became a viable mark... Read More about Predicting STC Customers' Satisfaction Using Twitter.

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.

Deep learning for early performance prediction of introductory programming students: a comparative and explanatory study (2020)
Journal Article
Pereira, F. D., Fonseca, S. C., Oliveira, E. H., Oliveira, D. B., Cristea, A. I., & Carvalho, L. S. (2020). Deep learning for early performance prediction of introductory programming students: a comparative and explanatory study. Revista Brasileira de Informática na Educação, 28, 723-749. https://doi.org/10.5753/rbie.2020.28.0.723

Introductory programming may be complex for many students. Moreover, there is a high failure and dropout rate in these courses. A potential way to tackle this problem is to predict student performance at an early stage, as it facilitates human-AI col... Read More about Deep learning for early performance prediction of introductory programming students: a comparative and explanatory study.

Investigating users’ experience on social media ads: perceptions of young users (2020)
Journal Article
Al Qudah, D. A., Al-Shboul, B., Al-Zoubi, A., Al-Sayyed, R., & Cristea, A. I. (2020). Investigating users’ experience on social media ads: perceptions of young users. Heliyon, 6(7), Article e04378. https://doi.org/10.1016/j.heliyon.2020.e04378

Social media platforms changed from being socialization platforms to serve businesses through advertisements. This research aims at investigating active young users' experience with social media ads by studying the personalization and the usefulness... Read More about Investigating users’ experience on social media ads: perceptions of young users.

Using learning analytics in the Amazonas: understanding students’ behaviour in introductory programming (2020)
Journal Article
Pereira, F. D., Oliveira, E. H., Oliveira, D., Cristea, A. I., Carvalho, L. S., Fonseca, S., …Isotani, S. (2020). Using learning analytics in the Amazonas: understanding students’ behaviour in introductory programming. British Journal of Educational Technology, 51(4), 955-972. https://doi.org/10.1111/bjet.12953

Tools for automatic grading programming assignments, also known as Online Judges, have been widely used to support computer science (CS) courses. Nevertheless, few studies have used these tools to acquire and analyse interaction data to better unders... Read More about Using learning analytics in the Amazonas: understanding students’ behaviour in introductory programming.

Analysing Gamification Elements in Educational Environments Using an Existing Gamification Taxonomy (2019)
Journal Article
Toda, A. M., Klock, A. C., Oliveira, W., Palomino, P. T., Rodrigues, L., Shi, L., …Cristea, A. I. (2019). Analysing Gamification Elements in Educational Environments Using an Existing Gamification Taxonomy. Smart Learning Environments, 6(1), https://doi.org/10.1186/s40561-019-0106-1

Gamification has been widely employed in the educational domain over the past eight years when the term became a trend. However, the literature states that gamification still lacks formal definitions to support the design and analysis of gamified str... Read More about Analysing Gamification Elements in Educational Environments Using an Existing Gamification Taxonomy.

How to Gamify learning Systems? An Experience Report using the Design Sprint Method and a Taxonomy for Gamification Elements in Education (2019)
Journal Article
Toda, A. M., Palomino, P. T., Oliveira, W., Rodrigues, L., Klock, A. C., Gasparini, I., …Isotani, S. (2019). How to Gamify learning Systems? An Experience Report using the Design Sprint Method and a Taxonomy for Gamification Elements in Education. Journal of Educational Technology & Society, 22(3), 47-60

One of the main goals of gamification in educational settings is to increase student motivation and engagement. To facilitate the design of gamified educational systems, in recent years, studies have proposed various approaches (e.g., methodologies,... Read More about How to Gamify learning Systems? An Experience Report using the Design Sprint Method and a Taxonomy for Gamification Elements in Education.

Lightweight adaptive E-Advertising Model (2018)
Journal Article
Qaffas, A. A., Cristea, A., & Mead, M. A. (2018). Lightweight adaptive E-Advertising Model. Journal of Universal Computer Science, 24(7), 935-974

Adaptive online advertising is a rapidly expanding marketing tool that delivers personalised messages and adverts to Internet users. At a time when the Internet is burgeoning, many websites use an adaptation process to tailor their advertisements, ho... Read More about Lightweight adaptive E-Advertising Model.

Building and evaluating resources for sentiment analysis in the Greek language (2018)
Journal Article
Tsakalidis, A., Papadopoulos, S., Voskaki, R., Ioannidou, K., Boididou, C., Cristea, A., …Kompatsiaris, Y. (2018). Building and evaluating resources for sentiment analysis in the Greek language. Language Resources and Evaluation, 52(4), 1021-1044. https://doi.org/10.1007/s10579-018-9420-4

Sentiment lexicons and word embeddings constitute well-established sources of information for sentiment analysis in online social media. Although their effectiveness has been demonstrated in state-of-the-art sentiment analysis and related tasks in th... Read More about Building and evaluating resources for sentiment analysis in the Greek language.

Cognitive agents and machine learning by example : representation with conceptual graphs (2018)
Journal Article
Gkiokas, A., & Cristea, A. (2018). Cognitive agents and machine learning by example : representation with conceptual graphs. Computational Intelligence, 34(2), 603-634. https://doi.org/10.1111/coin.12167

As machine learning (ML) and artificial intelligence progress, more complex tasks can be addressed, quite often by cascading or combining existing models and technologies, known as the bottom‐up design. Some of those tasks are addressed by agents, wh... Read More about Cognitive agents and machine learning by example : representation with conceptual graphs.