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  7. Research Degree - Helper Agents for Learning in Structured Ontology Interoperability Framework

Research Degree - Helper Agents for Learning in Structured Ontology Interoperability Framework

ken ehimwenma

Research centre

Communication and Computing Research Centre

Date
2012 - current

Tags
Information Technology and Interactions

Insight

Research Degree Project

My PhD project is on the use of a multi-agent system (MAS) in the pre-assessment of prior learning in a learner, in order to identify learning gap (if there is one), between what is known by the learner and what the learner intends to learn.

The key aims and objectives of this research is to design an MAS application that can pre-assess prior learning, identify learning gaps, make recommendation and tutor the learner.

My methodology is system analysis uses FIPA-compliant communication procedure between agents, in which the agents make a recommendation of what is needed to be learnt, after decision making from the pre-assessment of a learner. The agent environment used for experimentation is Jason AgentSpeak.

This project is an application in Intelligent Tutoring System (ITS). Most ITS do not consider individual differences in learning or what the learner brings into the learning at the start. Instead the tutoring begins with the assumption that every learner starts from the same position. This project is trying to address this by considering what the learner already knows before proceeding to the next learning goal or target. Firstly, the learner enters a concept to learn and is pre-assessed on the prerequisite knowledge. The agents then decide, based on the pre-assessment (pass/fail), and make individual recommendations for learning.

This project will be of relevance in the teaching-learning community, and to be of benefit to learners, if the idea of pre-assessment is integrated into ITS. It is to make learning systems more individualised or personalised. For instance, the knowledge and understanding of student A would be different from that of student B even if they have both just been to the same lecture. So in supporting students with intelligent learning systems, the system (just like a teacher) should be certain of what the learner knows/does not know before proceeding on the learning ladder.

By pre-assessing a learner on the prerequisite knowledge to the concept, the system can start the process of identifying a gap in learning, in the learner. The proposed system is not a grading system but uses learning gap identification to recommend learning activities necessary to meet the overall learning goal, and could be readily integrated into existing ITS.

Project Supervisors

  • Dr Paul Crowther (Director of Study)
  • Dr Martin Beer (Second Supervisor)

Researchers involved

Kennedy Ehimwenma- Research Degree Student

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