Abstract
This chapter presents an FML-based semantic inference mechanism for an After School Alternative Program (ASAP) in Taiwan. The Capability Maturity Model Integration (CMMI)-based assessment system for Taiwan’s ASAP is constructed by National University of Tainan (NUTN) from 2007 to 2011. The basic process of the assessment systems is as follows. First, domain experts provide item descriptions to construct the item fuzzy ontology repository. Second, a T − score scale item map is constructed for each item bank by applying the calibration procedures for the 3-parameter Item Response Theory (IRT) model. Third, student responses stored in the response data repository are processed, analyzed, and then summarized to obtain the semantic descriptions of student performance level. The item-map representation then summarizes the performance of each student. Next, the results are stored in the diagnosis report repository so that users such as the involved students, teachers, officers, or the ASAP administrator can retrieve the reports through the provided ASAP web platform. Simulation results indicate that the proposed approach is feasible for large-scale implementation of automatically generated diagnostic reports for the CMMI-based ASAP assessment system.
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Lee, CS., Wang, MH., Hung, PH., Kuo, YL., Wang, HM., Lin, BH. (2013). Apply Fuzzy Markup Language to ASAP Assessment System. In: Acampora, G., Loia, V., Lee, CS., Wang, MH. (eds) On the Power of Fuzzy Markup Language. Studies in Fuzziness and Soft Computing, vol 296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35488-5_5
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DOI: https://doi.org/10.1007/978-3-642-35488-5_5
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