Measuring the Digital Divide among students caused by Artificial Intelligence

The integration of artificial intelligence (AI) in higher education requires to equip students with the skills to engage with AI technologies. Drawing from the digital divide concept—which encompasses disparities in access, skills, and outcomes—this study investigates potential inequalities among students in higher education contexts in conjunction with AI. Furthermore, this study introduces the Digital Divide–Artificial Intelligence (DD-AI) survey instrument, developed through a two-phase approach. Initially, a systematic literature review adhering to a seven-stage process was con-ducted, identifying 481 articles, with 15 undergoing in-depth analysis. Findings from this literature review informed the construction of the DD-AI. Subsequently, a theo-retical model comprising eight hypotheses was established to assess AI-related digital divides. The instrument's development followed an established scale development process, including a comprehensive pre-test involving the think-aloud method with three students and a survey of n=106 students. Preliminary results indicate that the DD-AI possesses high reliability and validity, offering a robust tool for examining AI-induced digital inequalities in higher education.