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Fuzzy signature approach to clarification of subjectivity in assessment of metacognitive skills transfer

Transfer of metacognitive skill can be assessed by experts with the high degree of subjectivity. The gap between the instructor's “process” and the learners' “counter-process” must be identified in order to correct and improve misconception and ineffectual transfer. Fuzzy Signature Approach help to clarify that there are two stages of assessments: value representation and numerical representation. In terms of numerical representation, we propose a method to solve the problem the practical assessment problems, especially the subjectivity, multi-dimensional criteria, and incomplete data, depending on the different context in each student. This paper also attempts to define the linguistic criteria, which suitable for theoretical framework of metacognitive transfer. The input variables will be scored by human opinion, as the subjectivity. In terms of fuzzy inference, the weighted generalized mean is employed to operate the aggregation functions. In this model, certain theoretical criteria become weighting factors when the act of assessment in classroom regard the criteria as the factor. Adjustment of the human discrepancy is probably normal but must be realized. The pattern of learning may not emerge from the order of the competences but a proportional weight of the driving factors.