Generative AI in Inclusive Classrooms: Enhancing Social Interactions, Personalised Learning, and Metacognitive Skills

In this study, the researcher conducted a systematic literature review to investigate the pioneering potential of generative artificial intelligence (GAI) tools and technologies to cater to diverse learning needs in inclusive classrooms. The research was based on social constructivist, human–machine learning collaborative learning, and metacognitive theories and was designed to address three major concerns: the social hindrances faced by students with diverse learning needs during collaborative tasks in inclusive classrooms, the inability of students with learning difficulties’ to participate equally when using GAI tools, and the potential implications of GAI tools for students struggling with metacognitive skill development. The investigation was based on a thematic analysis of 20 scholarly research articles drawn from Scopus, Web of Science, and Google Scholar following PRISMA. Commonalities in the data were identified using colour coding techniques. The results revealed that GAI tools improve communication skills by breaking down cultural and linguistic barriers, which gives neurodivergent learners equitable opportunities to participate in peer interactions. GAI tools can increase reflective thinking, encourage creative problem-solving, and aid in developing structured and planned groups within a stipulated time. GAI tools effectively reduce cognitive load, improve focus, facilitate goal-driven learning, and provide personalised assistance through adaptive scaffolding that addresses learners’ multimodal needs. These tools help in deskilling by providing scaffolding and fostering gradually increasing independence. Further research can be conducted to explore the long-term impact of GAI on students and open up new possibilities for addressing the limitations of current GAI technology in inclusive pedagogy.