Understanding Self-Regulated Learning Dynamics Through Computer Simulation: A Model-Based Approach
Journal Title: International Journal of Knowledge and Innovation Studies - Year 2024, Vol 2, Issue 2
Abstract
Self-regulated learning (SRL) is conceptualized as a series of interrelated cognitive and affective processes rather than as isolated events. To elucidate the relationship between students' cognitive engagement and their comprehension of self-regulation strategies, a conceptual model was developed to examine learner engagement during a hypothetical learning scenario. The model posits that the learning environment can be represented as a social network in which the mechanisms of knowledge diffusion significantly influence a learner's adoption of self-regulatory processes. The results obtained from this model corroborate the modes of cognitive engagement as predicted by the Interactive, Constructive, Active, and Passive (ICAP) framework, manifesting as absorbing-state phase transitions. These transitions are interpreted as self-tuned phase changes associated with self-schema and personal adaptive and reflexive learning thresholds. This framework suggests that learners engage in retrospective monitoring processes that activate SRL mechanisms. It is inferred that learning occurs through continuous change; wherein self-regulated practices can be viewed as processes leading to specific events that subsequently trigger further learning. This conceptualization underscores the dynamic nature of SRL and highlights the potential for computer simulations to model and understand these processes.
Authors and Affiliations
Kyffin Bradshaw
Keywords
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- EP ID EP744658
- DOI https://doi.org/10.56578/ijkis020204
- Views 38
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