Using Concept Maps to Facilitate Deep Learning in a Third Year Geomatics Engineering Course release_c4yrvcwqeva5zkcdhdiwwi4hr4

by Elena Rangelova

Published in Proceedings of the Canadian Engineering Education Association (CEEA) by Queen's University Library.



This paper examines the use of concept maps (a graphical tool used for organizing structured information) to assist students in learning abstract and difficult concepts in a third year geomatics engineering course. Students often describe the material in this course as "difficult to understand" and "it contains lots of complex concepts". Therefore, their learning cannot always be described as deep learning; rather, students tend to resort to surface learning in order to deal with the high complexity of the course material. The term deep learning originates from the fundametal work by Marton and Säljö, who investigate how students respond to academic tasks. Engaging in deep learning means that a student is able to organize new information in a structured way and link it to previous knowledge.
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Type  article-journal
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Date   2018-12-02
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