Gender Differences in ICT Self-Efficacy and Computer Literacy Across ICILS 2018 and 2023

Aim. This study examines the predictive relationships between students’ general ICT self-efficacy (S_GENEFF), specialised ICT self-efficacy (S_SPECEFF), and computer and information literacy (CIL) scores within the framework of ICILS 2018 and 2023. It also examines gender-based differences in ICT self-efficacy perceptions across two independent ICILS assessment cycles. Methods. The research employs a secondary data analysis approach using ICILS datasets from 13 participating countries. Both descriptive and inferential statistical analyses were conducted to explore gender differences in general and specialised ICT self-efficacy. Regression analyses were then applied to determine the extent to which these variables predict students’ CIL scores across the two assessment years. Results. The findings reveal a persistent gender gap favouring boys in specialised ICT self-efficacy (S_SPECEFF), though the effect sizes declined in 2023. General ICT self-efficacy (S_GENEFF) was found to be a positive predictor of CIL scores for both genders, whereas specialised ICT self-efficacy emerged as a negative predictor, an effect that was stronger in 2023. These results may suggest a discrepancy between students’ perceived competence in specialised ICT tasks and their demonstrated CIL performance, rather than providing direct evidence of overconfidence. Conclusions. The study suggests that while access to technology and gender equity in digital participation have improved, disparities in confidence and competence remain. Educational policies should aim to align students’ perceived and actual ICT competencies, particularly in advanced technological tasks, while fostering gender-balanced digital learning environments.