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Title:
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SELF-EVALUATION OF OPEN ANSWERS AS A BASIS FOR ADAPTIVE LEARNING SYSTEMS |
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Author(s):
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Egon Werlen and Per Bergamin |
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ISBN:
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978-989-8533-81-4 |
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Editors:
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Demetrios G. Sampson, Dirk Ifenthaler and Pedro Isaías |
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Year:
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2018 |
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Edition:
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Single |
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Keywords:
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Self-Evaluation, Validity, Adaptive Learning, Sensors, Measurement |
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Type:
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Short Paper |
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First Page:
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335 |
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Last Page:
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340 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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The continuous measurement of learning behavior or learning outcome by appropriate sensors is fundamental for the implementation of technology-based adaptive learning courses. An adaptive system needs such learning data to adapt the instruction to the needs of students. Depending on the learning objective, the sensors use information generated within tasks as basis for instructional adaptation, such as closed clear answers to learning tasks or more ambiguous open answers. In the second case, the use of self-evaluation concepts is one possibility. However, the automation and corresponding generation of learning data for adaptive systems is difficult because the answers are not clearly correct or incorrect. In a preliminary study we constructed a corresponding self-evaluation scaffold in the context of a Blended-Learning course in health psychology with 60 adult students. The goal of the study was to analyze if self-evaluation delivers valid data for sensors of an intended adaptive learning system, and what influences the accuracy of the self-evaluation. Therefore, we conducted an external evaluation of the students answers. The correlation of the self-evaluation with the external evaluation was moderate (r=.50 |
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