Differential patterns of digital literacy among Indonesian students: a Rasch-based DIF analysis

Purpose This study aims to investigate patterns of digital literacy differences among Indonesian students based on education level and demographic groups. Design/methodology/approach Data were collected from 534 Indonesian students using Rasch measurement and differential item functioning (DIF) analysis to detect item bias and measurement inequity. Findings University students demonstrated higher digital literacy levels than senior high school students. DIF analysis further revealed that several digital literacy items functioned differently across educational and demographic groups. These findings indicate that observed differences in digital literacy may reflect not only variations in competence but also differences in how specific groups respond to particular assessment items. The results highlight the importance of considering measurement fairness in comparing digital literacy skills across diverse populations. Research limitations/implications These findings may have limited generalisability beyond the specific context and sample used due to self-reported sampling and convenience sampling. However, Rasch DIF provides methodological implications for fair digital literacy assessment. Practical implications The findings highlight the need for targeted interventions in both secondary and higher education systems. Educational institutions can utilise DIF results to refine digital literacy assessments and design instructional resources tailored to students’ varying socio-demographic conditions. Social implications These findings can support evidence-based policies to improve digital literacy and prepare students for effective participation in academic and social digital environments. Originality/value This study extends digital literacy research by applying Rasch measurement and DIF analysis to examine measurement fairness and item bias in an emerging higher education context. It contributes novel empirical evidence regarding item bias, measurement equity and demographic influences on digital literacy development.