Knowledge Representation by Analogy for the Design of Learning and Assessment Strategies
Автор: Walid Mestadi, Khalid Nafil, Raja Touahni, Rochdi Messoussi
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 6 vol.9, 2017 года.
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The difficulty of learning a novel knowledge may not be the same for each learner. Often instructors try to find the easiest way to make a new knowledge understandable by most learners, but few of them give importance to the use of analogies which is the common practice in real life situations. This paper attempts to highlight that learning by analogy allows making the understanding of a novel and complicated knowledge easier. We first propose a model that represents the desired knowledge in an abstract way which allows us to find analogies in different domains. Based on these analogies, learning and assessment strategies can be derived in order to improve the learning outcome. Secondly, the design of a computer system that integrates the analogies, learning and assessment strategies into a digital learning environment is proposed.
Learning by Analogy, Analogy Model Design, Learning and Assessment Strategies, Knowledge Structuring, Digital Learning Systems
Короткий адрес: https://sciup.org/15014974
IDR: 15014974
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