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Features students really expect from learning analytics

delete2018-01-01
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PRE
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C
Clara Schumacher *
D
Dirk Ifenthaler
DOI:10.1016/j.chb.2017.06.030delete
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Abstract

Abstract

En 中文
More and more learning in higher education settings is being facilitated through online learning environments. Students' ability to self-regulate their learning is considered a key factor for success in higher education. Learning analytics offer a promising approach to better support and understand students' learning processes. The purpose of this study is to investigate students' expectations towards features of learning analytics systems and their willingness to use these features for learning. A total of 20 university students participated in an initial qualitative exploratory study. They were interviewed about their expectations of learning analytics features. The findings of the qualitative study were complemented by a quantitative study with 216 participating students. The findings show that students expect learning analytics features to support their planning and organization of learning processes, provide self assessments, deliver adaptive recommendations, and produce personalized analyses of their learning activities. (C) 2017 Elsevier Ltd. All rights reserved.
Keywords:
Learning analytics
Self-regulated learning
Feature
Dashboard
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Journal

Computers in Human Behavior cover
Computers in Human Behavior
IF:
8.9
Papers:
9.0K
Citations:
5.8W

Organization

U
University of Mannheim
Scholars:
1.9K
Papers: 2.2K
Citations: 3.2K