Application of dominance-based Rough Set theory for knowledge discovery in cooperative learning

This paper illustrates a rule induction approach to discover decision patterns by using Dominance-based Rough Set Approach (DRSA) to unravel the intrinsic factors for learning successes and failures in a cooperative group-learning environment. It employs an innovative group quiz method in a university Management Information Systems (MIS) course which induces students into a unique learning process. The survey results enumerate the conditioning factors in terms of multiple criteria ranked in ordinal scale or preference-ordered. The DRSA model is uniquely appropriate when data includes multiple criteria whose domains are preference-ordered. The assessment of the learning success shows how a preference-centric group decision model can be integrated with the dominance-based principle of rough set to derive minimal covering “if.., then..” decision rules. The paper demonstrates that it is possible to develop a formal approximate reasoning scheme to develop group dynamics and discover inherent patterns of the heuristics for group decisions.