Special Issue "Metacognition, Learning Strategies, and Self-Regulated Learning to Promote Sustained Learning"

Dear Colleagues,

Self-regulated learning (SRL) theory posits that SRL encompasses cognition, metacognition, and motivation. Several theoretical accounts of SRL have been proposed in the literature (see Panadero, 2017, for a review). For instance, Zimmerman’s cyclical phases model (CPM) (Zimmerman and Moylan, 2009) describes SRL as a cyclical process involving three parts: (1) forethought (e.g., goal setting, strategic planning, self-efficacy beliefs, and intrinsic motivation); (2) performance and volitional control (e.g., attention focusing, self-instruction, and self-monitoring); and (3) self-reflection (e.g., self-evaluation, attributions, and self-reactions). Similarly, Winne and Hadwin (2008) developed a metacognitive perspective model (MPM) of SRL in which metacognitive processes play a central role. According to the tenets of this model, learners are perceived as being active, involved self-regulated individuals who control their own learning through the implementation of metacognitive monitoring and strategy use and motivational factors such as self-efficacy and task value. Even though all these models vary regarding labels and what aspects to include, they all converge on the conclusion that learning is regulated by a variety of dynamic interacting and cyclical cognitive, metacognitive, and motivational factors (Butler and Winne, 1995; Panadero, 2017).

Thus, the purpose of this Special Issue is to publish the latest research on the dynamic relation between metacognition, learning strategies, and self-regulated learning in academic and non-academic settings. It is my hope that research that emerges from this Special Issue will not only contribute to sustainable education practices through components of SRL theory, but also to the advancement of sustained, enduring learning both within and beyond the classroom. To this end, research studies on these topics employing quantitative, qualitative, and mixed-methods research designs are welcome.

Reference:

1. Ernesto, P. A Review of Self-regulated Learning: Six Models and Four Directions for Research. Front. Psychol. 2017, 8, 422, doi:10.3389/fpsyg.2017.00422
2. Zimmerman, B.J.; Moylan, A.R. Self-regulation: Where metacognition and motivation intersect. In Handbook of metacognition in education; Hacker, D.J., Dunlosky, J., Graesser, A.C., Eds. Routledge/Taylor & Francis Group: Oxford, England, 2009; pp. 299–315.
3. Winne, P.H.; Hadwin, A.F. The weave of motivation and self-regulated learning. In Motivation and self-regulated learning: Theory, research, and applications. D. H. Schunk, D.H., Zimmerman, B.J., Eds. Lawrence Erlbaum Associates Publishers: Mahwah, NJ, USA, 2008; pp. 297–314.
4. Butler, D.L.; Winne, P.H. Feedback and Self-Regulated Learning: A Theoretical Synthesis. Rev. Educ. Res. 1995, 65, 245–281.

Dr. Antonio P. Gutierrez de Blume
Guest Editor

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• learning strategies
• metacognition
• self-regulated learning
• sustained learning

Title: Effects of Online Self-Regulated Learning on Learning Ineffectiveness During the COVID-19 Pandemic
Authors: Yu-Sheng Su
Affiliation: Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung City, Taiwan
Abstract: Under the COVID-19 pandemic and the new normal period, online learning is one of the main options for learning. Previous studies on self-regulated learning have shown that it was a better predictor of online learning effectiveness. However, this discussion has not been extended to the situation of the COVID-19 pandemic. To address this gap, this study adapted the three sub-constructs of self-regulated learning measurement and learning ineffectiveness measurement to explore the relationship between the three phases of self-regulated learning and learning ineffectiveness. The data was collected from 370 high school students involved in online learning during the context of COVID-19 pandemic. Structural equation modeling was used to confirmatory factor analysis on the data. Findings showed that the preparatory phase was positively related to the performance phase and the appraisal phase; the performance phase was positively related to the appraisal phase; on the other hand, the performance phase and the appraisal phase were negatively related to learning ineffectiveness. In addition, the performance phase has no direct relation to the learning ineffectiveness, but the preparatory phase has a correlation with learning ineffectiveness mediated by the performance phase and the appraisal phase. The results suggest that better performance in the preparatory, performance, appraisal phase of self-regulated learning were decreased learners’ online perceived learning ineffectiveness. This understanding can have implications for global education.