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Measures for recommendations based on past students' activity

Huptych, Michal; Bohuslavek, Michal; Hlosta, Martin and Zdrahal, Zdenek (2017). Measures for recommendations based on past students' activity. In: LAK '17 Proceedings of the Seventh International Learning Analytics & Knowledge Conference on - LAK '17, pp. 404–408.

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This paper introduces two measures for the recommendation of study materials based on students' past study activity. We use records from the Virtual Learning Environment (VLE) and analyse the activity of previous students. We assume that the activity of past students represents patterns, which can be used as a basis for recommendations to current students.

The measures we define are Relevance, for description of a supposed VLE activity derived from previous students of the course, and Effort, that represents the actual effort of individual current students. Based on these measures, we propose a composite measure, which we call Importance.

We use data from the previous course presentations to evaluate of the consistency of students' behaviour. We use correlation of the defined measures Relevance and Average Effort to evaluate the behaviour of two different student cohorts and the Root Mean Square Error to measure the deviation of Average Effort and individual student Effort.

Item Type: Conference or Workshop Item
Copyright Holders: 2017 ACM
ISBN: 1-4503-4870-X, 978-1-4503-4870-6
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 49661
Depositing User: Kay Dave
Date Deposited: 22 Jun 2017 15:09
Last Modified: 02 May 2019 16:07
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