The research around eDoer departs from the recent need for high-quality online learning. Nowadays, learners expect online learning environments to support them in 1. developing skills they need for current/future jobs, gaining knowledge about different aspects of life, learning about the areas they are interested in, etc. So to offer the educational services needed by learners, we consider the following research questions:
- How can we extract the topics that need to be covered to gain knowledge about a specific area (e.g., a job or course)?
- How can we support the content curation (and curricula development) processes using AI?
- How can we recommend personalised educational content to learners?
- How do we evaluate the quality of available online educational resources?
- How can we extract properties (e.g. difficulty level, teaching style, and keywords) from educational materials?
- How do we develop and design a dashboard that offers required services for both learners?
- How do we develop and design a dashboard that supports educators create and maintain high-quality curricula effectively?
Here you can find the list of our publications
2022
An AI-based open recommender system for personalized labor market driven education Journal Article
In: Advanced Engineering Informatics, vol. 52, pp. 101508, 2022.
Hybrid human-AI curriculum development for personalised informal learning environments Proceedings Article
In: LAK22: 12th International Learning Analytics and Knowledge Conference, pp. 563–569, 2022.
2021
EduCOR: An educational and career-oriented recommendation ontology Proceedings Article
In: International Semantic Web Conference, pp. 546–562, Springer 2021.
Metadata analysis of open educational resources Proceedings Article
In: LAK21: 11th International Learning Analytics and Knowledge Conference, pp. 626–631, 2021.
2020
A recommender system for open educational videos based on skill requirements Proceedings Article
In: 2020 IEEE 20th International Conference on Advanced Learning Technologies (ICALT), pp. 1–5, IEEE 2020.
Quality prediction of open educational resources a metadata-based approach Proceedings Article
In: 2020 IEEE 20th international conference on advanced learning technologies (ICALT), pp. 29–31, IEEE 2020.
Labour market information driven, personalized, OER recommendation system for lifelong learners Journal Article
In: arXiv preprint arXiv:2005.07465, 2020.
OER recommendations to support career development Proceedings Article
In: 2020 IEEE Frontiers in Education Conference (FIE), pp. 1–5, IEEE 2020.
Quality evaluation of open educational resources Proceedings Article
In: Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, September 14–18, 2020, Proceedings 15, pp. 410–415, Springer 2020.
Extracting topics from open educational resources Proceedings Article
In: Addressing Global Challenges and Quality Education: 15th European Conference on Technology Enhanced Learning, EC-TEL 2020, Heidelberg, Germany, September 14–18, 2020, Proceedings 15, pp. 455–460, Springer 2020.
An oer recommender system supporting accessibility requirements Proceedings Article
In: Proceedings of the 22nd International ACM SIGACCESS Conference on Computers and Accessibility, pp. 1–4, 2020.