Adoption and Perceived Effectiveness of AI in Education: Personalization, Outcomes, and Equity

Abstract

This study examines the adoption and perceived effectiveness of Artificial Intelligence (AI) in education, with particular attention to its perceived role in supporting personalization, student engagement, and learning outcomes. Using a quantitative survey of educators and students across diverse institutions, the research assessed the frequency of AI tool usage, user familiarity, perceived benefits, and barriers to implementation. Findings indicate that while respondents report digital learning platforms are widely integrated into teaching and learning practices, the use of AI-powered adaptive systems remains comparatively limited. Respondents generally perceive AI as effective in improving learner motivation, content relevance, and real-time feedback, though its perceived contribution to academic performance is rated as moderate. Importantly, most participants reported few personal difficulties with AI tools, such as technical issues or usability concerns. However, they acknowledged broader systemic challenges, including inequitable access to technology, high implementation costs, algorithmic bias, and data-privacy concerns. The results suggest that AI appears most promising as a supplementary and collaborative tool rather than a replacement for traditional pedagogy, especially when aligned with ethical safeguards, inclusivity, and sound pedagogical design. The study concludes that while AI holds considerable potential to transform learning through adaptive and personalized experiences, its success depends on policies and practices that prioritize equity, teacher support, and responsible innovation.