Effect of Learning Styles on Peer Assessment in an Agent-based Collaborative Learning Environment

In peer assessment, the awarding grades might not accurately reflect the students' achievement due to potential rating bias or individual abilities. The proposed methodology aims at aggregating students' ratings to reduce personal bias using agent negotiation. We consider individual learning styles of assessors into the negotiation process and show by an illustrative example and an experiment how the accuracy of assessment results can be improved through incorporating learning styles. The more accurate feedback provides students a better quality of assessment which enables them to reflect their effort and abilities.