University Teachers' and Students' Expectations on Learning Analytics

被引:1
作者
Saks, Katrin [1 ]
Pedaste, Margus [1 ]
Rannastu, Meeli [1 ]
机构
[1] Univ Tartu, Inst Educ, Tartu, Estonia
来源
2018 IEEE 18TH INTERNATIONAL CONFERENCE ON ADVANCED LEARNING TECHNOLOGIES (ICALT 2018) | 2018年
关键词
learning analytics; qualitative analysis; big data; small data; scenario-based approach; contemporary learning approach;
D O I
10.1109/ICALT.2018.00050
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Learning analytics (LA) is a promising tool to support learning and retention in studies; so far, many applications have been developed to make use of big data saved automatically while using online learning management systems. However, it is not clear how different applications support the contemporary learning approach or how they are valued by both teachers and students. Therefore, a qualitative study was conducted to explore university teachers' and students' expectations on LA. Several scenarios were provided to them in order to feed their ideas about the potential of LA. The results were linked to the characteristics of the contemporary learning approach. This showed that while self-regulation is the most often supported objective enhanced by LA, collaboration skills and subjective well-being need much more attention. It was also found that students were more positive than teachers in starting to use LA and teachers' opinions varied greatly.
引用
收藏
页码:183 / 187
页数:5
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