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The National Institution for Academic Degrees and University Evaluation (NIAD-UE) is engaged in the awarding of academic degrees based on the accumulation of credits. These credits must be classified according to pre-determined criteria for the chosen disciplinary field by each applicant. This classification is checked by the sub-committees whose members are well-versed in the syllabus of each course. We have proposed the course classification support system (CCS) and the active course classification support system (ACCS) that can support the course classification by constructing the term-classification databases such that myDB or myDBc. Furthermore, we have combined ACCS with the course examples that are assigned for every fields in NIAD-UE and are used to guide the course classification. However, the combination is not necessarily effective since they are used independently. In this paper, we introduce ACCS to a learning mechanism in order to combine the course examples and the term-classification databases effectively. We show an application example to show the effectiveness of our method.