REGULATION AND DIGITAL DISTURBANCE IN ACADEMIC PROCRASTINATION: EVIDENCE FROM A GENDER-INVARIANT STRUCTURAL MODEL

Linda Indiyarti Putri; Nusrotus Sa'idah; Ahmad Saefudin; Asma’ul Husna; Yushinta Eka Farida; Aris Abdul Ghony

doi:10.22437/jiituj.v10i2.53029

Authors

Linda Indiyarti Putri Universitas Wahid Hasyim https://orcid.org/0000-0003-3219-7744 (unauthenticated)
Nusrotus Sa'idah Universitas Islam Nahdlatul Ulama https://orcid.org/0000-0002-2234-8476 (unauthenticated)
Ahmad Saefudin Universitas Islam Nahdlotul Ulama Jepara https://orcid.org/0000-0001-5796-3658 (unauthenticated)
Asma’ul Husna Universitas Islam Nahdlotul Ulama Jepara
Yushinta Eka Farida Universitas Wahid Hasyim
Aris Abdul Ghony Universitas Wahid Hasyim https://orcid.org/0000-0002-9764-1028 (unauthenticated)

DOI:

https://doi.org/10.22437/jiituj.v10i2.53029

Keywords:

Academic Procrastination, Digital Disturbance, Gender-Invariant Structural Model, Self-Regulation

Abstract

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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