AI for human learning and behavior change: A comprehensive analysis

Timbadiya, Ajay (2025) AI for human learning and behavior change: A comprehensive analysis. World Journal of Advanced Research and Reviews, 25 (2). pp. 1119-1123. ISSN 2581-9615

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Abstract

People now study Artificial Intelligence's partnership with human learning because it reveals new ways to transform behavior. This article studies how AI helps people learn but also explains how it changes their actions. Technological advances including machine learning make it possible for us to tailor learning processes and extend human brain power while helping people change their behaviors. The research studies how using AI technologies to teach people poses ethical problems plus risks personal data security and calls for multiple professional viewpoints. The journal uses case examples to reveal how AI technology supports habit changes when put into practice across different fields such as education, healthcare, addiction treatment, and mental health specialist care. Digital tools currently change our behavior by providing bespoke learning tools online and through AI healthcare solutions as digital therapeutics. According to the research AI systems require teamwork from different fields and need to stay updated as AI models develop to stay relevant to their intended purposes. The final part demonstrates how combining AI systems and human-focused design will help us use technology to better teach and change behavior at scale across all groups of people

Item Type: Article
Official URL: https://doi.org/10.30574/wjarr.2025.25.2.0306
Uncontrolled Keywords: AI-powered; Behavior change; Cognitive-behavioral therapy (CBT); Data privacy; Digital therapeutics; Education; Ethical considerations; Healthcare; Learning personalization; Machine learning; Mental health; Natural language processing (NLP); Personalized feedback; Recovery; Scalability; Smart systems; Social well-being; Teacher support; Technology integration
Depositing User: Editor WJARR
Date Deposited: 15 Jul 2025 15:19
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/737