Self-Regulated Learning Instructional Design to Manage Cognitive Load in Mathematics
DOI:
https://doi.org/10.59211/mjpjetl.v4i1.142Keywords:
ADDIE, Self-Regulated Learning, Cognitive Load, Generative Processing, PLS-SEMAbstract
This study aims to develop an ADDIE-based mathematics instructional design using a Self-Regulated Learning (SRL) approach to control extraneous cognitive load and facilitate students’ generative processing. This study employs the R&D method, utilizing the ADDIE model (consists: analysis, design, development, implementation, and evaluation stage). The research subjects consisted of four validators, one teacher, and 70 students selected through purposive sampling. Research instruments included a validation sheet, an SRL questionnaire, a cognitive load scale, and a test based on generative processing indicators. Data were analyzed descriptively to evaluate validity, practicality, and effectiveness, and inferentially using PLS-SEM to examine relationships among variables. The results indicate that the developed design possesses very high validity with an average score of 85.5, high practicality at 84.25%, and effectiveness as evidenced by an N-Gain score of 0.47 (moderate category). Additionally, students’ extraneous cognitive load was found to be at a low level. The SEM results reveal that Self-Regulated Learning has a positive effect on generative processing and a negative effect on extraneous cognitive load, while extraneous cognitive load acts as a significant mediating variable. Therefore, the ADDIE-based instructional design integrated with SRL is proven to be feasible and effective in improving the quality of mathematics learning.
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