Beyond Digital Access: Generative Artificial Intelligence and Digital Literacy Predict Vocational Students’ Academic Writing - Ria Ria Candra Dewi; Aziz Azindani; Lily Budinurani; Novita Wulandari (Journal of Education and Teaching Learning, 2026)
This study examined the partial and simultaneous statistical effects of digital literacy and responsible generative artificial intelligence utilization on vocational students’ academic writing skills. A quantitative explanatory-correlational approach with a cross-sectional survey design was employed. The sample comprised 100 students from five vocational study programs selected through proportionate stratified random sampling. Data were collected using two 10-item Likert questionnaires measuring digital literacy and generative artificial intelligence utilization, together with a source-based academic essay performance test assessed using an analytic rubric. Pearson correlation and multiple linear regression were applied. Digital literacy had a positive and significant statistical effect on academic writing skills (B = 6.413; β = 0.334; p < 0.001). Generative artificial intelligence utilization also had a positive and significant effect and provided a stronger relative contribution (B = 9.097; β = 0.494; p < 0.001). Simultaneously, both predictors produced F(2,97) = 42.013; p < 0.001 and explained 46.4% of the variance. These findings indicated that vocational students’ academic writing development required the integration of digital literacy and critical, ethical, and responsible artificial intelligence practices in writing instruction and institutional policy.