Current limitation of ai in education
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Authors
Neo, Kazuki
Issue Date
2025-03
Type
Electronic thesis
Thesis
Thesis
Language
en_US
Keywords
Information technology
Alternative Title
Abstract
This study examines the effectiveness and limitations of artificial intelligence (AI) in education, focusing on the subjects where AI can enhance student learning and the barriers to its widespread adoption. Using a semantic review methodology, the research synthesizes existing literature to assess AI's impact across different academic domains. Findings indicate that AI shows promise in subjects that benefit from personalized learning and data-driven insights, such as mathematics and language learning. However, significant challenges remain, including ethical concerns, data privacy risks, and the potential to exacerbate educational inequalities. These findings underscore the need for a balanced approach to AI integration, ensuring that technological advancements align with principles of equity and ethics. Further research, incorporating empirical methods, is recommended to deepen understanding and address these challenges.
Description
March2025
Information Technology and Web Science Program
Information Technology and Web Science Program
Full Citation
Publisher
Rensselaer Polytechnic Institute, Troy, NY