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Advanced digital literacy: Analysis of student readiness in facing generative AI

Author

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  • Indrawati Syamsuddin

    (Universitas Halu Oleo)

  • Verawati Verawati

    (Institut Teknologi dan Bisnis Bina Adinata)

  • Ilhamurrahman M Hubaib

    (Universitas Halu Oleo)

Abstract

The development of artificial intelligence technology, particularly generative artificial intelligence (generative AI), has brought about significant changes, especially in higher education. This condition requires students not only to understand the use of basic digital tools but also to master advanced digital literacy, which includes evaluative, strategic, and adaptive abilities in response to technological automation. This study aims to explore students’ readiness to master advanced digital literacy and identify the factors influencing it. This study employed a qualitative approach, with data collected through in-depth interviews, observations, and document analysis involving students in the Civic Education Study Program at Halu Oleo University. The findings show that students demonstrate high readiness to utilize AI for academic needs and technological adaptation. However, this readiness is not balanced with adequate information validation abilities, understanding AI mechanisms, and awareness of digital ethics. These findings align with advanced digital literacy theories that emphasize the evaluative, ethical, and critical aspects of modern technology use. The tables included in this study reinforce the pattern that students’ readiness tends to be stronger in operational aspects but weaker in reflective and evaluative ones. This study contributes to the development of a more adaptive advanced digital literacy learning model in higher education for the generative AI ecosystem.

Suggested Citation

  • Indrawati Syamsuddin & Verawati Verawati & Ilhamurrahman M Hubaib, 2026. "Advanced digital literacy: Analysis of student readiness in facing generative AI," Priviet Social Sciences Journal, Privietlab Research Center, vol. 6(1), pages 312-320, January.
  • Handle: RePEc:prv:pssjpv:1223
    DOI: 10.55942/pssj.v6i1.1223
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