All Outputs (8)

Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses (2018)
Presentation / Conference Contribution
Cristea, A., Alamri, A., Kayama, M., Stewart, C., Alsheri, M., & Shi, L. (2018). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Designing Digitalization (ISD2018 Proceedings). Lund, Sweden: Lund University

Whilst a high dropout rate is a well-known problem in MOOCs, few studies take a data-driven approach to understand the reasons of such a phenomenon, and to thus be in the position to recommend and design possible adaptive solutions to alleviate it. I... Read More about Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses.

How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers (2018)
Presentation / Conference Contribution
Cristea, A., Alshehri, M., Alamri, A., Kayama, M., Stewart, C., & Shi, L. (2018). How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Proceedings of the 27th International Conference on Information Systems Development (ISD2018), Education Track, Lund, Sweden, August 22-24, 2018

Data-intensive analysis of massive open online courses (MOOCs) is popular. Researchers have been proposing various parameters conducive to analysis and prediction of student behaviour and outcomes in MOOCs, as well as different methods to analyse and... Read More about How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers.

Can Learner Characteristics Predict Their Behaviour on MOOCs? (2018)
Presentation / Conference Contribution
Cristea, A. I., Alamri, A., Alshehri, M., Kayama, M., Foss, J., Shi, L., & Stewart, C. D. (2018). Can Learner Characteristics Predict Their Behaviour on MOOCs?. In 10th International Conference on Education Technology and Computers (119-125). https://doi.org/10.1145/3290511.3290568

Stereotyping is the first type of adaptation in education ever proposed. However, the early systems have never dealt with the numbers of learners that current MOOCs provide. Thus, the umbrella question that this work tackles is if learner characteris... Read More about Can Learner Characteristics Predict Their Behaviour on MOOCs?.

Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses (2018)
Presentation / Conference Contribution
Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Designing Digitalization (ISD2018 Proceedings)

Whilst a high dropout rate is a well-known problem in MOOCs, few studies take a data-driven approach to understand the reasons of such a phenomenon, and to thus be in the position to recommend and design possible adaptive solutions to alleviate it. I... Read More about Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses.

How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers (2018)
Presentation / Conference Contribution
Cristea, A. I., Alamri, A., Kayama, M., Stewart, C., Alshehri, M., & Shi, L. (2018). How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers. In B. Andersson, B. Johansson, S. Carlsson, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Designing Digitalization (ISD2018 Proceedings)

Data-intensive analysis of massive open online courses (MOOCs) is popular. Researchers have been proposing various parameters conducive to analysis and prediction of student behaviour and outcomes in MOOCs, as well as different methods to analyse and... Read More about How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers.

A large-scale category-based evaluation of a visual language for adaptive hypermedia (2018)
Presentation / Conference Contribution
Khan, J., Cristea, A., & Alamri, A. (2018). A large-scale category-based evaluation of a visual language for adaptive hypermedia. In Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018 (94-98). https://doi.org/10.1145/3234825.3234834

Adaptive Hypermedia (AH) provides a personalised and customised approach, enhancing the usability of hypermedia, by building a model of various qualities of a user and applying this information to adapt the content and the navigation to their require... Read More about A large-scale category-based evaluation of a visual language for adaptive hypermedia.

On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs (2018)
Presentation / Conference Contribution
Alshehri, M., Foss, J., Cristea, A. I., Kayama, M., Shi, L., Alamri, A., & Tsakalidis, A. (2018). On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs. In Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018 (73-77). https://doi.org/10.1145/3234825.3234833

Stereotyping is the first type of adaptation ever proposed. However, the early systems have never dealt with the numbers of learners that current Massive Open Online Courses (MOOCs) provide. Thus, the umbrella question that this work tackles is if le... Read More about On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs.

An intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System (2018)
Presentation / Conference Contribution
Alamri, A., Rusby, H., Cristea, A. I., Khan, J., Shi, L., & Stewart, C. (2018). An intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System. In Proceedings of the 2018 the 3rd International Conference on Information and Education Innovations (ICIEI'18) : London, United Kingdom, June 30 - July 02, 2018 (57-61). https://doi.org/10.1145/3234825.3234835

Adaptive Educational Hypermedia (AEH) offers more advanced personalisation and customisation features to the field of e-learning compared to the outdated static systems (where every learner is given the same set of learning materials). AEH can improv... Read More about An intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System.