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Research Title: Knowledge Driven Approaches to e-Learning Recommendation
Start date: October 2013
Blessing’s research is designed to help learners discover relevant documents in the mass of e-learning materials currently available on the Web. Learners are new to the topic they are researching so they often have difficulty asking the right query in a search engine. Her project has developed an e-learning recommender which learns from topics in e-books in order to focus the search for materials that are relevant to the learner.
Blessing is a research student in the Smart Information Systems group of the School of Computing Science and Digital Media at the Robert Gordon University. She holds an MSc in Computing Information Engineering from the Robert Gordon University.
Her MSc project employed a Case Base Reasoning approach to reuse existing experiences from online visualisation tools, and recommend appropriate visualisation techniques for data. This project won a Best Poster award at the 2013 British Computer Society Women Lovelace Colloquium Poster Competition.
Blessing’s research interests include E-learning Systems, Case-Based Reasoning, Recommender Systems, Knowledge Discovery, and Text Mining.
Her current research enhances recommendation in the e-learning domain by harnessing the knowledge of teaching experts to improve the retrieval of relevant e-learning materials.
Student member of:
- Association for the Advancement of Artificial Intelligence
- British Computer Society
- IEEE Computer Society
- Blessing Mbipom, Susan Craw and Stewart Massie (2018). Improving e-learning recommendation by using background knowledge. Expert Systems, Wiley. http://doi.org/10.1111/exsy.12265 PDF.
- Blessing Mbipom, Stewart Massie and Susan Craw (2018). An e-Learning Recommender that Helps Learners Find the Right Materials. In Proceedings of the 8th Symposium on Educational Advances in Artificial Intelligence (EAAI), New Orleans, LA. AAAI Press. PDF.
- Blessing Mbipom, Susan Craw and Stewart Massie (2016). Harnessing Background Knowledge for E-learning Recommendation. In Proceedings of the 36th SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pages 3–17, Springer. doi:10.1007/978-3-319-47175-4_1 [Best Technical Paper] PDF
- Donald Michie Memorial Award for the Best Technical Paper http://www.rgu.ac.uk/news/rgu-at-forefront-of-uk-artificial-intelligence-research/
- Blessing Mbipom discusses her research project "Enhancing Recommendation in E-learning Systems" at DEMOfest15, held in Edinburgh on 19th November 2015. https://www.youtube.com/watch?v=z8tKxYkC0y4