Authors: Sureshkumar M and Mahabub Basha S
Abstract: Artificial intelligence (AI) is now a key factor in the conception, delivery, and assessment of education. Many AI applications, such as intelligent tutoring systems, adaptive learning systems, and predictive analytics, support creating highly personalized, efficient, and empowering learning settings. However, the social and cognitive implications of AI on learning processes and learning outcomes are not sufficiently addressed, especially for the general public. Through an ensemble analysis of literature from education, psychology, sociology, and computer science, this paper provides novel perspectives on the intersection of human-AI interactions in educational settings. A mixed-methods research method was used to obtain quantitative data on AI-based learning platforms and qualitative data collected through structured interviews and classroom observations. The findings demonstrate two main effects: on the one hand, AI can significantly improve academic performance, learner engagement, and individualized instruction; while on the other hand, AI may be able to undermine interpersonal communication, and social skills development and require excessive reliance on automated decision making (critical thinking and independent problem solving). The findings draw attention to the urgent need for human-centered AI design for helping to foster academic excellence but also building collaboration, ethical reasoning, and reflective thinking; the findings also have the potential to inform policymakers, educators, and artificial intelligence developers pursuing strategies to adopt AI solutions in line with the holistic educational values and long-term developmental needs of students.
Keywords: Artificial Intelligence (AI), Social Behavior, Cognitive Development, Education