Key Barriers to Personalized Learning in Times of Artificial Intelligence: A Literature Review - Gina Paola Barrera Castro; Andrés Chiappe; María Soledad Ramírez-Montoya; Carolina Alcántar Nieblas (Applied Sciences)
Personalized learning (PL) has emerged as a promising approach to address diverse educational needs, with artificial intelligence (AI) playing an increasingly pivotal role in its implementation. This systematic literature review examines the landscape of PL across various educational contexts, focusing on the use of AI and associated challenges. Using the PRISMA guidelines, 68 empirical studies published between 2018 and 2024 were analyzed, revealing correlations between academic levels, learning modalities, technologies, and implementation barriers. Key findings include (a) predominant use of AI in higher education PL implementations, (b) preference for blended learning in secondary and elementary education, (c) shift from technological to pedagogical barriers across educational levels, and (d) persistent psychological barriers across all contexts. This review provides valuable insights for educators, policymakers, and researchers, offering a comprehensive understanding of the current state and future directions of AI-driven personalized learning.