Analysis of the Impact of Job Demands-Resources and Teachers’ Burnout Levels on the Quality of Deep Learning Instruction
DOI:
https://doi.org/10.21009/jtp.v28i1.66094Keywords:
Job Demands–Resources Model, Teacher Burnout, Deep Learning InstructionAbstract
This study examines the relationships between job demands, job resources, burnout, and the quality of deep learning instruction among kindergarten teachers in Jayapura, Papua. Grounded in the Job Demands–Resources (JD-R) model, the research aims to analyze how job characteristics are associated with teacher burnout and instructional quality in an early childhood education context. A quantitative explanatory approach with a cross-sectional survey design was employed. Data were collected from 150 teachers using validated questionnaires and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4.0. The results indicate that job demands are positively associated with burnout, while job resources are negatively associated with burnout and positively related to instructional quality. Burnout is negatively associated with the quality of deep learning instruction and partially mediates the relationships between job characteristics and instructional quality. The model explains 61% of the variance in burnout and 57% in instructional quality. These findings highlight the importance of strengthening job resources, such as autonomy, collegial support, and professional development, to sustain instructional quality and teacher well-being in resource-constrained educational settings.
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