THE «DIGITAL CRUTCH» WHY ARE STUDENTS BECOMING DEPENDENT ON AI?
Keywords:
Artificial Intelligence (AI), AI Dependency, Higher Education, Academic Stress, Illusion of Competence, AI Literacy.Abstract
The use of Artificial Intelligence in universities is changing how students do their school work. Artificial Intelligence tools make things easier and more accessible for students. However people are getting worried that students are becoming too dependent on Artificial Intelligence.This study looks at how dependent students are on Artificial Intelligence. It checks the cognitive effects of using Artificial Intelligence too much. The study also looks at how stress and the pressure to perform make students rely too heavily on Artificial Intelligence systems. For example students might think they understand something just because Artificial Intelligence makes it sound clear. Artificial Intelligence can also hurt creativity. Make students less honest about their work. It can even stop students from talking to each other. This study does not say that Artificial Intelligence should be banned from schools. Instead it says that students should learn how to use Artificial Intelligence in a way. We need to make sure that Artificial Intelligence helps students learn without doing all the thinking for them. The future of universities depends on finding a balance between using Artificial Intelligence and still thinking for ourselves. Artificial Intelligence should be a tool that helps students, not a replacement, for their thoughts. We need to teach students how to use Artificial Intelligence without relying on it much. This way Artificial Intelligence can make learning without hurting the students.
References
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4. White House Office of Science and Technology Policy (2022). Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People. Available at: https://www.whitehouse.gov/ostp/ai-bill-of-rights/
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[1] U.S. Department of Education, Office of Educational Technology (2023).Cardona, M. A., Rodríguez, R. J., & Ishmael, K. Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations.
[2] Zhang, S., Zhao, X., Zhou, T., & Kim, J. H. (2024).Do you have AI dependency? The roles of academic self-efficacy, academic stress, and performance expectations on problematic AI usage behavior. International Journal of Educational Technology in Higher Education, 21(1), 1–22.
[3] Zhai, X., He, P., & Krajcik, J. (2022). Applying machine learning to automatically assess scientific models. Journal of Research in Science Teaching, 59(7), 1190–1216.
[4] Zacamy, J., & Roschelle, J. (2022). Navigating the tensions: How could equity-relevant research also be agile, open, and scalable? Digital Promise.
[5] White House Office of Science and Technology Policy (2022). Blueprint for an AI Bill of Rights: Making Automated Systems Work for the American People.
[6] . Winne, P. H. (2021). Open learner models working in symbiosis with self-regulating learners: A research agenda. International Journal of Artificial Intelligence in Education, 31(3), 446–459.
[7] Zacamy, J., & Roschelle, J. (2022). Navigating the tensions: How could equity-relevant research also be agile, open, and scalable? Digital Promise.
[8] Zhang, S., Zhao, X., Zhou, T., & Kim, J. H. (2024).Do you have AI dependency? The roles of academic self-efficacy, academic stress, and performance expectations on problematic AI usage behavior. International Journal of Educational Technology in Higher Education, 21(1), 1–22
