REGULATION AND DIGITAL DISTURBANCE IN ACADEMIC PROCRASTINATION: EVIDENCE FROM A GENDER-INVARIANT STRUCTURAL MODEL - Sa'idah, Nusrotus; Putri, Linda Indiyarti; Saefudin, Ahmad; Husna, Asma’ul; Farida, Yushinta Eka; Ghony, Aris Abdul (LPPM Universitas Jambi, 2026)
Academic procrastination remains prevalent in higher education, and digitally saturated learning environments may amplify students’ task delays. This study aims to test an integrative structural model linking self-regulation and digital disturbance to academic procrastination and to examine whether the measurement model operates equivalently across gender. Using a quantitative ex post facto design, data were collected from 216 Indonesian undergraduate students via validated 5-point Likert instruments measuring self-regulation, digital disturbance, and academic procrastination. Structural Equation Modeling with maximum likelihood estimation was conducted, followed by multi-group confirmatory factor analysis to assess gender measurement invariance. Results showed that self-regulation negatively predicted academic procrastination (β = −0.290, p < .001), while digital disturbance positively predicted academic procrastination (β = 0.544, p < .001); self-regulation was also negatively associated with digital disturbance (β = −0.268, p = .002). The model explained 46.5% of the variance in academic procrastination (R² = 0.465). Measurement invariance testing supported equivalence up to the scalar level across gender, enabling unbiased cross-gender interpretation of the constructs. The novelty of this study lies in combining a digitally relevant predictor (digital disturbance) with gender-invariant measurement validation within a single SEM framework in an Indonesian undergraduate context. Practically, the findings imply that universities should strengthen students’ self-regulated learning while managing digital interruptions through attention-management training and instructional policies to reduce procrastination.