Exploring attitudes of learners with respect to different learning strategies and performances using statistical methods
DOI:
https://doi.org/10.3991/ijet.v1i1.13Abstract
In this work the problem of identifying relationships between different learning strategies and learning outcomes is addressed. Classical statistical methods such as p values and chi square test, as well as Multiple Correspondence Analysis are employed; variables to be explained are performances of learners in Multiple Choice Tests (MCT) and Design Tests. It is shown that: the methods are able to detect differences with a different sensitivity; the methods are able to detect characteristics belonging to the metacognitive domain; specific strategies are effective to learn complex skills. Further applications are discussed, especially for what concerns cognitive and metacognitive changes happening in time.
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