Unpacking the intertemporal impact of self-regulation in a blended mathematics environment
作者：
Highlights：
• With arrival of learning analytics there are new venues for understanding impact Self-Regulated Learning (SRL).
• In blended learning environment, temporal analytics explored when, what, and how 1035 students were solving 429 tasks.
• SRL learning dispositions linked with learning processes and academic performance.
• Primary predictor of success was when students were engaged with mathematics.
摘要
•With arrival of learning analytics there are new venues for understanding impact Self-Regulated Learning (SRL).•In blended learning environment, temporal analytics explored when, what, and how 1035 students were solving 429 tasks.•SRL learning dispositions linked with learning processes and academic performance.•Primary predictor of success was when students were engaged with mathematics.
论文关键词：Learning analytics,Self-regulated learning,Temporal analytics,Mathematics,Blended learning,Learning dispositions
论文评审过程：Received 9 July 2018, Revised 26 June 2019, Accepted 7 July 2019, Available online 13 July 2019, Version of Record 15 August 2019.
论文官网地址：https://doi.org/10.1016/j.chb.2019.07.007
