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.
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