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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, October). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund, Sweden

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, October). How is learning fluctuating? FutureLearn MOOCs fine-grained temporal Analysis and Feedback to Teachers. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund

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, December). Can Learner Characteristics Predict Their Behaviour on MOOCs?. Presented at 10th International Conference on Education Technology and Computers - ICETC '18, Tokyo

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, August). Earliest Predictor of Dropout in MOOCs: A Longitudinal Study of FutureLearn Courses. Presented at 27th International Conference on Information Systems Development (ISD2018)., Lund, Sweden

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, December). How is Learning Fluctuating? FutureLearn MOOCs Fine-grained Temporal Analysis and Feedback to Teachers and Designers. Presented at 27th International Conference on Information Systems Development (ISD2018), Lund, Sweden

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.

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, June). On the need for fine-grained analysis of Gender versus Commenting Behaviour in MOOCs. Presented at 3rd International Conference on Information and Education Innovations (ICIEI'18), London

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, June). An intuitive Authoring System for a Personalised, Social, Gamified, Visualisation-supporting e-learning System. Presented at 3rd International Conference on Information and Education Innovations (ICIEI'18), London

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.