Abstract

This paper aims to identify self-regulation strategies from students' interactions with the learning management system (LMS). We used learning analytics techniques to identify metacognitive and cognitive strategies in the data. We define three research questions that guide our studies analyzing i) self-assessments of motivation and self regulation strategies using standard methods to draw a baseline, ii) interactions with the LMS to find traces of self regulation in observable indicators, and iii) self regulation behaviours over the course duration. The results show that the observable indicators can better explain self-regulatory behaviour and its influence in performance than preliminary subjective assessments.
Originalspracheenglisch
TitelProceeding LAK '18 Proceedings of the 8th International Conference on Learning Analytics and Knowledge
Herausgeber (Verlag)Association of Computing Machinery
Seiten191
Seitenumfang200
ISBN (elektronisch)978-1-4503-6400-3
DOIs
PublikationsstatusVeröffentlicht - Mär 2018
Veranstaltung8th International Conference on Learning Analytics and Knowledge - Sydney, Australien
Dauer: 5 Mär 20189 Mär 2018

Konferenz

Konferenz8th International Conference on Learning Analytics and Knowledge
KurztitelLAK '18
LandAustralien
OrtSydney
Zeitraum5/03/189/03/18

Fingerprint

Untersuchen Sie die Forschungsthemen von „Finding traces of self-regulated learning in activity streams“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren