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Information Technology for Development

Author ORCID Identifier

Samad Rasoulzadeh Aghdam: https://orcid.org/0000-0002-2096-6676

Glenn Muschert: https://orcid.org/0000-0003-3748-4961

Behnam Ghasemzadeh: https://orcid.org/0000-0002-0689-1401

Kris Hartley: https://orcid.org/0000-0001-5349-0427

Abstract

Technology influences development in numerous ways, including through education and training. It is both a didactic tool and a defining feature of students’ personal growth and social experiences. The ability of students to develop personal digital caTechnology influences development in numerous ways, including through education and training. It is both a didactic tool and a defining feature of students’ personal growth and social experiences. The ability of students to develop personal digital capital (an extension of Bourdieu’s multidimensional concept of capital) is a major determinant of their educational and career success and, by extension, national economic development. This study examines the influence of sociodemographic factors – age, gender, degree type, income, and parental education – on the personal development of digital capital among university students. Applying a structural equation model with data from an Iran-based survey (n = 421), the study finds that disparities in digital capital are explained by gender, income, and other sociodemographic factors. The finding that digital access supersedes digital competence in explaining inequalities in digital capital highlights pathways for targeted policy intervention.pital (an extension of Bourdieu’s multi-dimensional concept of capital) is a major determinant of their educational and career success and, by extension, national economic development. This study examines the influence of socio-demographic factors – age, gender, degree type, income, and parental education – on the personal development of digital capital among university students. Applying a structural equation model with data from an Iran-based survey (n = 421), the study finds that disparities in digital capital are explained by gender, income, and other socio-demographic factors. The finding that digital access supersedes digital competence in explaining inequalities in digital capital highlights pathways for targeted policy intervention.

DOI

10.17705/1ITD.032205

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