Profile

Blessing Mbipom
First Name: Blessing
Surname: Mbipom
Position: Research Student
Telephone: 01224 262482
Email:
ORCID: ORCID Icon http://orcid.org/0000-0003-4189-1113

Research Title: Experience-Based Recommendation for Personalised E-learning

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. 

Supervisors

Professor Susan Craw

Dr Stewart Massie

Academic Background

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.

Research Interests

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. 

Professional Memberships

Student member of:

  • Association for the Advancement of Artificial Intelligence
  • British Computer Society  
  • IEEE Computer Society

Publications

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. [Best Technical Paper]  PDF (https://openair.rgu.ac.uk/handle/10059/1663 ) 

Media Coverage