research-article

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Finding traces of self-regulated learning in activity streams

Authors:

Analía Cicchinelli,

Abelardo Pardo,

Viktoria Pammer-Schindler,

Carla Barreiros,

Stefanie LindstädtAuthors Info & Claims

LAK '18: Proceedings of the 8th International Conference on Learning Analytics and Knowledge

Pages 191 - 200

https://doi.org/10.1145/3170358.3170381

Published: 07 March 2018 Publication History

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.

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Cited By

Boulahmel ADjelil FSmits G(2025)Investigating Self-Regulated Learning Measurement Based on Trace Data: A Systematic Literature ReviewTechnology, Knowledge and Learning10.1007/s10758-025-09816-yOnline publication date: 18-Jan-2025
https://doi.org/10.1007/s10758-025-09816-y
Winter MMordel JMendzheritskaya JBiedermann DCiordas-Hertel GHahnel CBengs DWolter IGoldhammer FDrachsler HArtelt CHorz H(2024)Behavioral trace data in an online learning environment as indicators of learning engagement in university studentsFrontiers in Psychology10.3389/fpsyg.2024.139688115Online publication date: 23-Oct-2024
https://doi.org/10.3389/fpsyg.2024.1396881
Lee HBosch N(2024)Subtopic-specific heterogeneity in computer-based learning behaviorsInternational Journal of STEM Education10.1186/s40594-024-00519-x11:1Online publication date: 24-Dec-2024
https://doi.org/10.1186/s40594-024-00519-x
Show More Cited By

Index Terms

Finding traces of self-regulated learning in activity streams
1. Applied computing
  1. Education
2. Social and professional topics
  1. Professional topics
    1. Computing education
      1. Informal education

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Published In

cover image ACM Other conferences

LAK '18: Proceedings of the 8th International Conference on Learning Analytics and Knowledge

March 2018

489 pages

ISBN:9781450364003

DOI:10.1145/3170358

Conference Chairs:
Abelardo Pardo
The University of Sydney, AUS
,
Kathryn Bartimote-Aufflick
The University of Sydney, AUS
,
Grace Lynch
Society for Learning Analytics Research, AUS
,
Program Chairs:
Simon Buckingham Shum
University of Technology Sydney, AUS
,
Rebecca Ferguson
The Open University, UK
,
Agathe Merceron
Beuth University of Applied Sciences, GER
,
Xavier Ochoa
Escuela Superior Politécnica del Litoral, EC

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 March 2018

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European Commission

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LAK '18

LAK '18: International Conference on Learning Analytics and Knowledge

March 7 - 9, 2018

New South Wales, Sydney, Australia

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LAK '18 Paper Acceptance Rate 35 of 115 submissions, 30%;

Overall Acceptance Rate 236 of 782 submissions, 30%

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Cited By

Boulahmel ADjelil FSmits G(2025)Investigating Self-Regulated Learning Measurement Based on Trace Data: A Systematic Literature ReviewTechnology, Knowledge and Learning10.1007/s10758-025-09816-yOnline publication date: 18-Jan-2025
https://doi.org/10.1007/s10758-025-09816-y
Winter MMordel JMendzheritskaya JBiedermann DCiordas-Hertel GHahnel CBengs DWolter IGoldhammer FDrachsler HArtelt CHorz H(2024)Behavioral trace data in an online learning environment as indicators of learning engagement in university studentsFrontiers in Psychology10.3389/fpsyg.2024.139688115Online publication date: 23-Oct-2024
https://doi.org/10.3389/fpsyg.2024.1396881
Lee HBosch N(2024)Subtopic-specific heterogeneity in computer-based learning behaviorsInternational Journal of STEM Education10.1186/s40594-024-00519-x11:1Online publication date: 24-Dec-2024
https://doi.org/10.1186/s40594-024-00519-x
Xu XSu YHong WZhang YZhuang T(2024) The impact of a Personal Learning Environment on Chinese postgraduates’ online self-regulated learning skills / Impacto de un Entorno Personal de Aprendizaje en las aptitudes de aprendizaje autorregulado en línea de estudiantes de posgrado en China Journal for the Study of Education and Development: Infancia y Aprendizaje10.1177/0210370223122538247:1(173-205)Online publication date: 9-Apr-2024
https://doi.org/10.1177/02103702231225382
Bourguet M(2024)Demonstrating the impact of study regularity on academic success using learning analyticsProceedings of the 14th Learning Analytics and Knowledge Conference10.1145/3636555.3636845(736-741)Online publication date: 18-Mar-2024
https://dl.acm.org/doi/10.1145/3636555.3636845
Alhazbi SAl‐ali ATabassum AAl‐Ali AAl‐Emadi AKhattab THasan M(2024) Using learning analytics to measure self‐regulated learning: A systematic review of empirical studies in higher education Journal of Computer Assisted Learning10.1111/jcal.1298240:4(1658-1674)Online publication date: 29-Mar-2024
https://doi.org/10.1111/jcal.12982
Zhang YYe YPaquette LWang YHu X(2024)Investigating the reliability of aggregate measurements of learning process data: From theory to practiceJournal of Computer Assisted Learning10.1111/jcal.1295140:3(1295-1308)Online publication date: 3-Feb-2024
https://doi.org/10.1111/jcal.12951
Tang H(2024)Understanding self-regulated learning and learner performance in MOOCsDistance Education10.1080/01587919.2024.2338712(1-16)Online publication date: 4-Jun-2024
https://doi.org/10.1080/01587919.2024.2338712
Yun HSong HKim Y(2024)Identifying university students’ online self-regulated learning profiles: predictors, outcomes, and differentiated instructional strategiesEuropean Journal of Psychology of Education10.1007/s10212-024-00907-540:1Online publication date: 16-Nov-2024
https://doi.org/10.1007/s10212-024-00907-5
Boulahmel ADjelil FGilliot JLeray PSmits G(2024)Mining Discriminative Sequential Patterns of Self-regulated LearnersGenerative Intelligence and Intelligent Tutoring Systems10.1007/978-3-031-63031-6_12(137-149)Online publication date: 1-Jun-2024
https://doi.org/10.1007/978-3-031-63031-6_12
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