OPTIMIZING SELF REGULATED LEARNING THROUGH A GOOGLE SITES BASED ASYNCHRONOUS LEARNING MODEL FOR WORKING STUDENTS
DOI:
https://doi.org/10.21009/ishel.v2i1.68777Keywords:
self regulated learning, working students, asynchronous learning, google sites, adult learners, time poverty, higher educationAbstract
Working students frequently experience severe "time poverty" and cognitive fatigue. This study investigates optimizing SRL among working students by implementing a lightweight, user-friendly asynchronous learning model based on Google Sites. Utilizing a quasi-experimental pretest/posttest non-equivalent control group design, the study examined 120 working students enrolled in an employee class program. Participants were assigned to an experimental group utilizing the Google Sites intervention or a control group utilizing a standard institutional LMS. Data were collected using the Motivated Strategies for Learning Questionnaire (MSLQ) and analyzed via multivariate analysis of covariance (MANCOVA). The findings demonstrate that the experimental group exhibited statistically significant and robust improvements in both motivational beliefs (intrinsic goal orientation and task value) and self-regulated learning strategies (metacognitive self-regulation and time/study environment management) compared to the control group. The structured, linear, and cognitively accessible architectural design of Google Sites effectively scaffolded the forethought and self-reflection phases of Zimmerman’s cyclical model of SRL. The study concludes that deploying lightweight digital platforms significantly reduces extraneous cognitive load, empowering time-poor working students to use effective self-regulatory strategies.
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Copyright (c) 2026 Ahmad Fauzi, Robinson Situmorang, Uwes Anis Chaeruman
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