THE DIGITAL DIVIDE 2.0: ASSESSING EQUITY GAPS IN AI-ENHANCED PERSONALIZED LEARNING ENVIRONMENTS

Abstract

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The increasing application of Artificial Intelligence (AI) in education, i.e. AI-based personalized learning environment, has the potential to change the learning process of learners. However, the innovation is disruptive with regards to equity particularly the digital divide that may further widen the existing educational inequality. The author of the present paper will discuss the disparities of AI-based educational resources with equity considerations and their consequences on the performance of learners belonging to different socio-economic groups. The paper is based on a mixed-method design and examines the use of AI technologies in personalized learning environments and assesses their accessibility to the underrepresented student groups. It was a qualitative interview with a quantitative analysis of the educational outcomes of datasets obtained in other school districts. The broad implications of the findings are that despite the huge advantages of AI-based learning experiences, it also discriminates underprivileged students, since only those who are better off and live in larger cities are advantaged. The paper ends with an explanation of the implications of the differences and recommendations on how the AI based personalized learning could be made more accessible, equitable, and effective in a range of educational environments.