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2012
Conference Paper
Title

Key action extraction for learning analytics

Abstract
Analogous to keywords describing the important and relevant content of a document we extract key actions from learners' usage data assuming that they represent important and relevant parts of their learning behaviour. These key actions enable the teachers to better understand the dynamics in their classes and the problems that occur while learning. Based on these insights, teachers can intervene directly as well as improve the quality of their learning material and learning design. We test our approach on usage data collected in a large introductory C programming course at a university and discuss the results based on the feedback of the teachers.
Author(s)
Scheffel, M.
Niemann, K.
Leony, D.
Pardo, A.
Schmitz, H.-C.
Wolpers, M.
Kloos, C.D.
Mainwork
21st century learning for 21st century skills. 7th European Conference on Technology Enhanced Learning, EC-TEL 2012  
Conference
European Conference on Technology Enhanced Learning (EC-TEL) 2012  
DOI
10.1007/978-3-642-33263-0_25
Language
English
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
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