The gender divide in digital competence: a cross-sectional study on university students in southwestern Bangladesh

Abstract

Introduction: A persistent gender divide in digital competence is visible empirically in both developed and developing countries. But there is not a single study in the context of Bangladesh, as per the author’s best knowledge. This study, therefore, was designed to find out the gender divide in the digital competence of university students with reference to socioeconomic background. Methods: This cross-sectional study was carried out in a public university of Bangladesh, where data were collected from 1,059 students using a semi-structured interview schedule, where digital competence was measured by computer application usage (CAU) and computer self-efficacy (CSe), with overall reliability of 0.840 and 0.960, respectively. Data were analyzed using IBM SPSS Statistic v25, and one-way analysis of variance (ANOVA) and t-test were used to determine the differences between students regarding digital competence. Results: Findings from ANOVA suggested that older students, in terms of age (p < 0.001 for CAU and p < 0.001 for CSe) and levels of education (p < 0.001 for CAU and p < 0.001 for CSe), were more digitally competent. Likewise, students of Management and Business school (p < 0.001 for CAU and p < 0.001 for CSe) and from higher SES (p < 0.001 for CAU and p < 0.001 for CSe) were better off in digital competence. Regarding the gender divide, it is apparent that male students, irrespective of age (p < 0.001 for CAU and p < 0.001 for CSe), levels of education (p < 0.001 for CAU and p < 0.001 for CSe), school (p < 0.001 for CAU and p < 0.001 for CSe), and SES (p < 0.001 for CAU and p < 0.001 for CSe), were more digitally competent than their female counterparts. Conclusion: It is, therefore, strongly recommended to educators and policymakers to reduce long-established gender stereotypes by implementing gender-specific training and educational guidelines to create a generation of knowledgeable and skillful workforce.