Changes in self-regulated learning profiles during an undergraduate peer-based intervention: A latent profile transition analysis

Jeong, Soojeong; Feldon, David F.

doi:10.1016/j.learninstruc.2022.101710

Cited by 8 publications

(7 citation statements)

References 44 publications

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“…While these studies identified different numbers of SRL profiles, other researchers such as Järvelä et al (2019) and Jeong and Feldon (2023) identified the challenges regarding SRL studies and mentioned that SRL is not a state, and it involves a series of contingencies over time. They called for studies that examine the changes in regulatory processes and regulation types over time (i.e., temporality).…”

Section: Literature Reviewmentioning

confidence: 99%

Unfolding self‐regulated learning profiles of students: A longitudinal study

Esnaashari

Gardner

Arthanari

et al. 2023

Computer Assisted Learning

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Background It is vital to understand students' Self‐Regulatory Learning (SRL) processes, especially in Blended Learning (BL), when students need to be more autonomous in their learning process. In studying SRL, most researchers have followed a variable‐oriented approach. Moreover, little has been known about the unfolding process of students' SRL profiles. Objectives We present the insights derived from a study that measured motivation and the learning strategies used by 198 students of a university entry‐level, business school, BL course to develop an understanding of students' SRL processes. Methods The Strategies for Learning Questionnaire (MSLQ) was used to survey 198 students three times during a semester to investigate SRL profiles and how they unfolded as the course progressed using a person‐oriented approach. Through a clustering approach, we focus on MSLQ's motivation aspects as its importance has been emphasised by different SRL theories, and extant research into motivation in learning analytics (LA) is still lacking. Results and Conclusions Through the longitudinal clustering approach, we identified minimally, average, and highly SRL profiles. We acknowledged that students might change their SRL profiles as the course progressed as a result of feedback they received. What are the 1 or 2 Major Takeaways from the Study? This study contributes to the SRL theory by examining students' SRL profiles adaptation longitudinally (addressing the challenge identified regarding the cyclical nature of SRL). This study contributes to LA by investigating motivational constructs currently lacking in the field and bringing forward theory based empirical evidence to inform theory and practice.

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Section: Literature Reviewmentioning

confidence: 99%

Unfolding self‐regulated learning profiles of students: A longitudinal study

Esnaashari

Gardner

Arthanari

et al. 2023

Computer Assisted Learning

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“…In the context of Higher Education, university students are expected to manage a lot of information and tasks in a more autonomous environment than they may have been used to in secondary school ( Sáez et al, 2018 ; Sáez-Delgado et al, 2020 ). They often need to juggle simultaneously the high load of demands in the different courses, with their social life, in addition, in many cases the dedication to a part-time job ( Jeong and Feldon, 2023 ). However, in Higher Education, university students often have insufficient strategies to regulate their own learning independently, suggesting the need for adequate support ( Sáez-Delgado et al, 2020 ; Lobos et al, 2021 ; Jeong and Feldon, 2023 ; Lim et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

“…They often need to juggle simultaneously the high load of demands in the different courses, with their social life, in addition, in many cases the dedication to a part-time job ( Jeong and Feldon, 2023 ). However, in Higher Education, university students often have insufficient strategies to regulate their own learning independently, suggesting the need for adequate support ( Sáez-Delgado et al, 2020 ; Lobos et al, 2021 ; Jeong and Feldon, 2023 ; Lim et al, 2023 ). In fact, research has documented that, most frequently, students do not spontaneously regulate their learning ( Lim et al, 2023 ), and lack sufficient knowledge and strategies to effectively complete and achieve their academic challenges, which highlights the lack of regulation in their study processes ( Jeong and Feldon, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

“…SRL trajectories are likely to be substantially heterogeneous due to the dynamic and multidimensional nature of the self-regulatory process. Indeed, numerous cross-sectional studies have identified distinct profiles among students based on their use of SRL strategies ( Dörrenbächer and Perels, 2016 ; Li et al, 2020 ; Sulisworo et al, 2020 ), suggesting the need for a longitudinal, person-oriented analytic approach to report heterogeneous SRL development ( Jeong and Feldon, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

“…It has even been suggested to analyze self-regulation trajectories considering the different grades of secondary education ( Karademir and Deveci, 2019 ). This would make it possible to answer the knowledge gap regarding the possible variation in self-regulation levels as one progresses through different grades of secondary education ( Jeong and Feldon, 2023 ). It would also facilitate understanding the current preparation of students to face university studies when they graduate from secondary education.…”

Section: Introductionmentioning

confidence: 99%

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Invariant and suboptimal trajectories of self-regulated learning during secondary school: implications focused on quality in higher education

et al. 2023

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It has been shown that self-regulation of learning is a key variable for an adequate transition and adjustment from secondary school to tertiary education, and it is also associated with successful academic results; therefore, it is relevant to analyze its levels of development in the pre-university stage. The aim of this research was to evaluate the trajectories of self-regulation of learning in secondary school students. The method considered a longitudinal design and included a sample of 403 students from 9th to 12th grade in Chile. An instrument with adequate psychometric properties was used to measure the learning self-regulation process (disposition, performance and self-evaluation phases). The results showed that self-regulation is at suboptimal levels in its different phases (M = 4.25 to M = 4.71). Linear mixed models showed: a significant effect of sex on the disposition variable in favor of females; and that the phases of disposition, performance and self-evaluation do not change over time. It is concluded that, if self-regulation of learning is not specifically trained, it does not increase during secondary school. The findings are discussed considering the possible practical implications for educational policies, research, timely intervention and impact on the quality of school and university education.

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Linking self-regulated learning to community of inquiry in online undergraduate courses: A person-centered approach

Na,

Jeong,

Clarke-Midura

et al. 2024

Education Tech Research Dev

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The Community of Inquiry (CoI) framework has gained widespread recognition as a theoretical model for understanding student learning in online environments. Despite its prevalence, CoI has been critiqued for its limited emphasis on learners’ proactive roles in self-regulating their own learning. To address this, researchers have suggested integrating self-regulated learning (SRL) into the CoI framework. This integration calls for empirical research to explore the relationship between SRL and the three established CoI presences: teaching, social, and cognitive. Using a person-centered approach, this study examines how varying SRL skills among 750 undergraduate students in an online introductory mathematics course are related to the three CoI components. Latent profile analyses identified five distinct SRL profiles: minimal regulators, low regulators with limited social skills, low regulators, moderate regulators, and competent regulators. We found that students in higher SRL profiles demonstrated higher perception of CoI, whereas those in relatively lower SRL profiles showed lower levels of perceived CoI. Our findings underscore the importance of incorporating self-regulation in the CoI framework for a more comprehensive understanding of online learning.

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Changes in self-regulated learning profiles during an undergraduate peer-based intervention: A latent profile transition analysis

Cited by 8 publications

References 44 publications

Unfolding self‐regulated learning profiles of students: A longitudinal study

Unfolding self‐regulated learning profiles of students: A longitudinal study

Invariant and suboptimal trajectories of self-regulated learning during secondary school: implications focused on quality in higher education

Linking self-regulated learning to community of inquiry in online undergraduate courses: A person-centered approach

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