Abstract
The need of developing more efficient educational systems leads to the incorporation of personalized operations. Digital learning focuses mainly on the adaptive content and navigation. However, the provision of a valid assessment tool is essential to an integrated e-learning system, as it indicates the accomplishment of learning goals. One such testing model should be designed based on the new demands to knowledge, skills and attitudes that students have to acquire, and considering the students’ needs. To this direction, this paper introduces an adaptive assessment system where the test items are designed based on Revised Bloom’s Taxonomy and the assessment content is adapted to students. One major advantage of the proposed system is that it provides a better detection of student’s learning gaps, useful for further system adaptivity.
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Krouska, A., Troussas, C., Virvou, M. (2019). Computerized Adaptive Assessment Using Accumulative Learning Activities Based on Revised Bloom’s Taxonomy. In: Virvou, M., Kumeno, F., Oikonomou, K. (eds) Knowledge-Based Software Engineering: 2018. JCKBSE 2018. Smart Innovation, Systems and Technologies, vol 108. Springer, Cham. https://doi.org/10.1007/978-3-319-97679-2_26
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DOI: https://doi.org/10.1007/978-3-319-97679-2_26
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