Outputs (13)

Automatic Subject-based Contextualisation of Programming Assignment Lists (2020)
Presentation / Conference Contribution
Fonseca, S. C., Pereira, F. D., Oliveira, E. H., Oliveira, D. B., Carvalho, L. S., & Cristea, A. I. (2020, December). Automatic Subject-based Contextualisation of Programming Assignment Lists. Presented at Educational Data Mining 2020 (EDM), Virtual

As programming must be learned by doing, introductory programming course learners need to solve many problems, e.g., on systems such as ’Online Judges’. However, as such courses are often compulsory for non-Computer Science (nonCS) undergraduates, th... Read More about Automatic Subject-based Contextualisation of Programming Assignment Lists.

For whom should we gamify? Insights on the users intentions and context towards gamification in education (2020)
Presentation / Conference Contribution
Toda, A., Pereira, F. D., Klock, A. C. T., Rodrigues, L., Palomino, P., Oliveira, W., Oliveira, E. H. T., Gasparini, I., Cristea, A. I., & Isotani, S. (2020, December). For whom should we gamify? Insights on the users intentions and context towards gamification in education. Presented at Simpósio Brasileiro de Informática na Educação (SBIE 2020), Porto Alegre, Brazil

Gamification design in educational environments is not trivial and many variables need to be considered to achieve positive outcomes. Often, educators and designers do not know when the students intend on the use of gamified environments might influe... Read More about For whom should we gamify? Insights on the users intentions and context towards gamification in education.

Sequential Recommender via Time-aware Attentive Memory Network (2020)
Presentation / Conference Contribution
Ji, W., Wang, K., Wang, X., Chen, T., & Cristea, A. I. (2020, October). Sequential Recommender via Time-aware Attentive Memory Network. Presented at 29th Conference on Information and Knowledge Management (CIKM), Virtual Event

Recommendation systems aim to assist users to discover desirable contents from an ever-growing corpus of items. Although recommenders have been greatly improved by deep learning, they still face several challenges: (1) behaviours are much more comple... Read More about Sequential Recommender via Time-aware Attentive Memory Network.

GamiCSM: relating education, culture and gamification - a link between worlds (2020)
Presentation / Conference Contribution
Toda, A., Klock, A. C. T., Palomino, P. T., Rodrigues, L., Oliveira, W., Stewart, C., Cristea, A. I., Gasparini, I., & Isotani, S. (2020, October). GamiCSM: relating education, culture and gamification - a link between worlds. Presented at 19th Brazilian Symposium on Human Factors in Computing Systems, Diamantina, Brazil

The potential of gamification to improve users' motivation and engagement influenced many researchers and professionals to analyse its effects in educational settings. While some studies focus on adapting game elements according to demographic and be... Read More about GamiCSM: relating education, culture and gamification - a link between worlds.

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.

Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study (2020)
Presentation / Conference Contribution
Aduragba, O. T., Yu, J., Cristea, A. I., Hardey, M., & Black, S. (2020, December). Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study. Presented at 2020 15th International Conference on Computer Science & Education (ICCSE)

The TechUPWomen programme takes 100 women from the Midlands and North of England, particularly from underrepresented communities, with degrees or experience in any subject area, retrains them in technology and upon graduation guarantees an interview... Read More about Digital Inclusion in Nothern England: Training Women from Underrepresented Communities in Tech: A Data Analytics Case Study.

Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course (2020)
Presentation / Conference Contribution
Yu, J., Aduragba, O. T., Sun, Z., Black, S., Stewart, C., Shi, L., & Cristea, A. (2020, December). Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course. Presented at 2020 15th International Conference on Computer Science & Education (ICCSE), Delft, Netherlands

Social media is ubiquitous, a continuous part of our daily lives; it offers new ways of communication. This is especially crucial in education, where various online systems make use of (perceived) public or private communication, as a means to suppor... Read More about Temporal Sentiment Analysis of Learners: Public Versus Private Social Media Communication Channels in a Women-in-Tech Conversion Course.

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.

Exploring Navigation Styles in a FutureLearn MOOC (2020)
Book Chapter
Shi, L., Cristea, A. I., Toda, A. M., & Oliveira, W. (2020). Exploring Navigation Styles in a FutureLearn MOOC. In V. Kumar, & C. Troussas (Eds.), Intelligent Tutoring Systems (45-55). Springer Verlag. https://doi.org/10.1007/978-3-030-49663-0_7

This paper presents for the first time a detailed analysis of fine-grained navigation style identification in MOOCs backed by a large number of active learners. The result shows 1) whilst the sequential style is clearly in evidence, the global style... Read More about Exploring Navigation Styles in a FutureLearn MOOC.

A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts (2020)
Presentation / Conference Contribution
Alrajhi, L., Alharbi, K., & Cristea, A. I. (2020, December). A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts. Presented at ITS 2020: International Conference on Intelligent Tutoring Systems

In recent years, massive open online courses (MOOCs) have become one of the most exciting innovations in e-learning environments. Thousands of learners around the world enroll on these online platforms to satisfy their learning needs (mostly) free of... Read More about A Multidimensional Deep Learner Model of Urgent Instructor Intervention Need in MOOC Forum Posts.