Exploring students' self-regulated learning in online learning environments : The multimodal learning analytics approach

JUHAŇÁK, Libor. Exploring students' self-regulated learning in online learning environments : The multimodal learning analytics approach. Online. In EDULEARN23 Proceedings. Palma, Spain: IATED, 2023, p. 8038-8045. ISBN 978-84-09-52151-7. Available from: https://dx.doi.org/10.21125/edulearn.2023.2084.

Basic information

• Original name: Exploring students' self-regulated learning in online learning environments : The multimodal learning analytics approach
• Authors: JUHAŇÁK, Libor (203 Czech Republic, guarantor, belonging to the institution).
• Edition: Palma, Spain, EDULEARN23 Proceedings, p. 8038-8045, 8 pp. 2023.
• Publisher: IATED

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 50301 Education, general; including training, pedagogy, didactics [and education systems]
• Country of publisher: Czech Republic
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: electronic version available online
• WWW: URL
• RIV identification code: RIV/00216224:14210/23:00134405
• Organization unit: Faculty of Arts
• ISBN: 978-84-09-52151-7
• ISSN: 2340-1117
• Doi: http://dx.doi.org/10.21125/edulearn.2023.2084
• Keywords in English: self-regulated learning;online learning environment;multimodal learning analytics
• Tags: rivok

Abstract

Self-regulated learning (SRL) has received increasing attention in educational research in recent years. However, a number of questions and uncertainties remain when focusing specifically on SRL in the context of online learning environments. Therefore, in order to extend the existing knowledge in this area of research, it seems beneficial to focus attention not only on traditional research methods of measuring SRL, but also on different ways of analyzing the digital traces that learners leave in online learning environments as they use them. One of the possible approaches that seems to be particularly promising is the so-called multimodal learning analytics, which focuses on the use and combination of different types of data to understand the learning process (not only) in online learning environments. This paper presents the results of an analysis focused on a combination of questionnaire data and student data on their behavior in an online learning environment. Data collection was conducted in three waves over three different semesters, with students in different courses being contacted each semester. The questionnaire measured different dimensions of SRL such as goal orientation, effort regulation, planning and organizing, metacognitive self-regulation, elaboration, etc. Data from the questionnaire were then integrated with data from an online learning environment. Primarily, these were so-called logs that recorded the students' behavior in each course in the online learning environment. Several proxy indicators of different aspects of learning and self-regulation were extracted from the records of students' behavior in the online learning environment. These indicators included, for example, the number of visits, the regularity of visits, and the total time spent in the course in the online learning environment. The main objective of this paper is to answer the question of whether it is possible to observe a relationship between the level of different dimensions of students' SRL measured by the questionnaire and their actual behavior in the online learning environment measured by proxy indicators extracted from the log records.

Links

• GA21-08218S, research and development project: Name: Využití multimodální analytiky učení pro studium procesů seberegulovaného učení v systémech pro řízení výuky

Investor: Czech Science Foundation, Multimodal learning analytics to study self-regulated learning processes within learning management systems