Proposal of an Active Course Classification Support system with Exploitation-oriented Learning extended by positive and negative examples

The National Institution for Academic Degrees and University Evaluation is engaged in awarding academic degrees based on the accumulation of academic course credits. These course credits must be classified for designated disciplinary fields according to pre-determined criteria by an applicant. The validity of the applicant´s course classification is judged based on careful reading of course syllabuses by sub-committee members of the institution who are well versed in the particular field. The Active Course Classification Support system (ACCS) aims to assist subcommittee members in the course classification process. As the latest improvement of learning mechanism, Exploitation-oriented Learning (XoL) has been introduced to ACCS. The operation of ACCS has not been considered with the features of XoL, and does not consider the states of other items that are not decided by XoL. We must consider the states of all items in order to output the course properly by ACCS. In this paper, we aim to develop the effective operation of ACCS that includes the states of all items by means of generating sets of positive and negative examples derived from courses that have been judged by the subcommittee members in the past. We show a numerical example to clarify the effectiveness of our proposal.