Integrating Large Language Models into Accessible and Inclusive Education: Access Democratization and Individualized Learning Enhancement Supported by Generative Artificial Intelligence - Inigo Lopez-Gazpio (Information, 2025)
This study explores the integration of large language models (LLMs) into educational environments, emphasizing enhanced accessibility, inclusivity, and individualized learning experiences. The study evaluates trends in the transformative potential of artificial intelligence (AI) technologies in their capacity to significantly mitigate traditional barriers related to language diversity, learning disabilities, cultural differences, and socioeconomic inequalities. The result of the analysis highlights how LLMs personalize instructional content and dynamically respond to each learner’s educational and emotional needs. The work also advocates for an instructor-guided deployment of LLMs as pedagogical catalysts rather than replacements, emphasizing educators’ role in ethical oversight, cultural sensitivity, and emotional support within AI-enhanced classrooms. Finally, while recognizing concerns regarding data privacy, potential biases, and ethical implications, the study argues that the proactive and responsible integration of LLMs by educators is necessary for democratizing access to education and to foster inclusive learning practices, thereby advancing the effectiveness and equity of contemporary educational frameworks.