Exploring the link between self‐regulated learning and learner behaviour in a massive open online course

Abstract

Background: Learners in Massive Open Online Courses (MOOCs) are presented with great autonomy over their learning process. Learners must engage in self-regulated learning (SRL) to handle this autonomy. It is assumed that learners' SRL, through monitoring and control, influences learners' behaviour within the MOOC environment (e.g., watching videos). The exact relationship between SRL and learner behaviour has however not been investigated.Objectives: We explored whether differences in SRL are related to differences in learner behaviour in a MOOC. As insight in this relationship could improve our understanding of the influence of SRL on behaviour, could help explain the variety in online learner behaviour, and could be useful for the development of successful SRL support for learners.Methods: MOOC learners were grouped based on their self-reported SRL. Next, we used process mining to create process models of learners' activities. These process models were compared between groups of learners.Results and conclusions: Four clusters emerged: average regulators, help seekers, self-regulators, and weak regulators. Learners in all clusters closely followed the designed course structure. However, the process models also showed differences which could be linked to differences in the SRL scores between clusters. Takeaways:The study shows that SRL may explain part of the variability in online learner behaviour. Implications for the design of SRL interventions include the necessity to integrate support for weak regulators in the course structure.

Mapping active and collaborative learning in higher education through annotations in hyper‐video by learning analytics

“…These findings highlight the importance of considering factors affecting acceptance and willingness to engage in collaborative digital tools when implementing them in educational systems (Cheung & Vogel, 2013). Moreover, as mentioned above, the autonomy that is self‐inherent to the system suggests that students require self‐regulation learning skills to utilize the various functions (Jansen et al, 2022). When self‐regulation skills are underdeveloped or unsupported by the instructors, the effectiveness gained from using the hyper‐video system could be compromised.…”

“…For example, instructors can implement directive questions within the videos, inviting students to answer and collaborate with each other (Mirriahi et al, 2021; Tseng, 2021). Such scaffolds were found to promote active and collaborative learning in digital collaborative learning environments (e.g., Shin, et al, 2020; Jansen et al, 2022).…”

“…While students show overall positive attitudes to technology integration, several factors have been implicated in their reluctance to adopt ICT, such as perceived ease of use, technical issues and self‐competency in using technologies (Silin & Kwok, 2017). Moreover, digital environments that allow students to have an autonomy in deciding how and when to utilize the available tools rely heavily on self‐regulated learning skills (e.g., Jansen et al, 2022). Thus, even if students are willing to cooperate with hyper‐video functions, the effectiveness of their utilisation might depend on their self‐regulation skills, or available scaffolds (Guo, 2022).…”

Narrowing down dimensions of e-learning readiness in continuing vocational education — perspectives from the adult learner

“…More precisely, mastery goal-orientation predicts a better use of SRL and supportive online behavior according to Yeh et al (2019) . Learning strategies themselves, specifically SRL strategies, are advantageous for online learning ( Yukselturk and Bulut, 2007 ; Jansen et al, 2022 ). This is supported by Steinkamp (2018) who found that a lack of organization and the ability to prioritize leads to struggling in online learning.…”

Analysis of the Deep Learning Strategies Questionnaire with Ecuadorian students

“…One of the crucial aspects of school learning and lifelong learning is self-regulation, which means that students who use appropriate self-regulation strategies may learn more (Núñez Perez et al, 2006;Badali et al, 2022;Biwer et al, 2022;Jansen et al, 2022;Shin and Song, 2022). A basic premise of self-regulated learning is that there are regulatory processes (i.e., monitoring and control) that are performed on aspects associated with school learning, and can be understood, fostered, and even trained for being transferred to other learning tasks (Bell and Kozlowski, 2008;Usher and Schunk, 2018).…”