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A systematic meta-Review and analysis of learning analytics research

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成果类型:
期刊论文
作者:
Du, Xui;Yang, Juan*;Shelton, Brett E.;Hung, Jui-Long;Zhang, Mingyan
通讯作者:
Yang, Juan
作者机构:
[Yang, Juan; Zhang, Mingyan; Du, Xui] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
[Hung, Jui-Long; Shelton, Brett E.] Boise State Univ, Dept Educ Technol, Boise, ID 83725 USA.
[Hung, Jui-Long] Cent China Normal Univ, Natl Engn Lab Educ Big Data, Wuhan, Hubei, Peoples R China.
通讯机构:
[Yang, Juan] C
Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan 430079, Hubei, Peoples R China.
语种:
英文
关键词:
Systematic meta-review;learning analytics;educational data mining;big data;prediction of performance;learner modelling
期刊:
Behaviour & Information Technology
ISSN:
0144-929X
年:
2021
卷:
40
期:
1
页码:
49-62
基金类别:
Portions of this paper were presented in the proceedings of the Future Technologies Conference 2018 in Vancouver, BC, Canada. This study was supported by National Natural Science Foundation of China under grant number 61877027.
机构署名:
本校为第一且通讯机构
院系归属:
国家数字化学习工程技术研究中心
摘要:
As an emerging field of research, learning analytics (LA) offers practitioners and researchers information about educational data that is helpful for supporting decisions in management of teaching and learning. While often combined with educational data mining (EDM), crucial distinctions exist for LA that mandate a separate review. This study aims to conduct a systematic meta-review of LA for mining key information that could assist in describing new and helpful directions to this field of inquiry. Within 901 LA articles analyzed, eight reviews were identified and synthesised to identify and d...

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