Apply fuzzy ontology to CMMI-based ASAP assessment system

This paper proposes an ontology-based semantic inference mechanism to apply to Capability Maturity Model Integration (CMMI)-based assessment system for After School Alternative Program (ASAP) in Taiwan. First, the domain experts provide item descriptions to construct the item fuzzy ontology repository. Second, applying the calibration procedures of the 3-parameter item response theory (IRT) model, a T-score scale item map is constructed for each item bank. Third, students' responses stored in the response data repository are processed, reasoned, and then summarized to obtain the semantic descriptions of students' performance level. Then, the summarized descriptions of each student' performance level are presented by the item-map representation. The results are stored into the diagnosis report repository and users like the involved students, teachers, officers, or ASAP administrator can retrieve the reports through the provided ASAP web platform. The preliminary simulation results show that the proposed approach will be feasible and promising for a large scale implementation of the automatic diagnosis reports for the CMMI-based ASAP assessment system.