Alexandra I. Cristea
Can Learner Characteristics Predict Their Behaviour on MOOCs?
Cristea, Alexandra I.; Alamri, Ahmed; Alshehri, Mohammad; Kayama, Mizue; Foss, Jonathan; Shi, Lei; Stewart, Craig D.
Authors
Ahmed Sarhan Alamri ahmed.s.alamri@durham.ac.uk
PGR Student Doctor of Philosophy
Mohammad Alshehri
Mizue Kayama
Jonathan Foss
Lei Shi
Dr Craig Stewart craig.d.stewart@durham.ac.uk
Associate Professor
Abstract
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 characteristics can predict their overall, but also fine-grain behaviour. Earlier results point at differences related to gender or to age. We have also looked into more details into finer-grain analyzing the weekly behavior of females and males. Here, we further expand this, by showing how, depending on the way the comments are counted, significance can be found when comparing female and male commenting behavior, at the level of the week. Moreover, the topic of the course is an important factor in this behavior. These outcomes can help in informing future runs, in terms of potential personalised feedback for teachers and students.
Citation
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
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 10th International Conference on Education Technology and Computers - ICETC '18 |
Online Publication Date | Nov 26, 2018 |
Publication Date | Oct 26, 2018 |
Deposit Date | Jul 3, 2019 |
Publicly Available Date | Jul 4, 2019 |
Pages | 119-125 |
Book Title | 10th International Conference on Education Technology and Computers |
DOI | https://doi.org/10.1145/3290511.3290568 |
Public URL | https://durham-repository.worktribe.com/output/1143867 |
Files
Accepted Conference Proceeding
(815 Kb)
PDF
Copyright Statement
© ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 10th International Conference on Education Technology and Computers (ICETC '18) https://doi.org/10.1145/3290511.3290568
You might also like
Towards Designing Profitable Courses: Predicting Student Purchasing Behaviour in MOOCs
(2021)
Journal Article
MOOC next week dropout prediction: weekly assessing time and learning patterns
(2021)
Book Chapter
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search