Student Perspectives on the Benefits and Risks of AI in Education
Not on the map. Why?
Abstract (arXiv)
The use of chatbots equipped with artificial intelligence (AI) in educational settings has increased in recent years, showing potential to support teaching and learning. However, the adoption of these technologies has raised concerns about their impact on academic integrity, students' ability to problem-solve independently, and potential underlying biases. To better understand students' perspectives and experiences with these tools, a survey was conducted at a large public university in the United States. Through thematic analysis, 262 undergraduate students' responses regarding their perceived benefits and risks of AI chatbots in education were identified and categorized into themes. The results discuss several benefits identified by the students, with feedback and study support, instruction capabilities, and access to information being the most cited. Their primary concerns included risks to academic integrity, accuracy of information, loss of critical thinking skills, the potential development of overreliance, and ethical considerations such as data privacy, system bias, environmental impact, and preservation of human elements in education. While student perceptions align with previously discussed benefits and risks of AI in education, they show heightened concerns about distinguishing between human and AI generated work - particularly in cases where authentic work is flagged as AI-generated. To address students' concerns, institutions can establish clear policies regarding AI use and develop curriculum around AI literacy. With these in place, practitioners can effectively develop and implement educational systems that leverage AI's potential in areas such as immediate feedback and personalized learning support. This approach can enhance the quality of students' educational experiences while preserving the integrity of the learning process with AI.
Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 4 of its 35 references that are in the map. First posted on arXiv 4 May 2025.
Builds on
4 of 35 references.
References · 4
- 2022Programming Is Hard -- Or at Least It Used to Be: Educational Opportunities And Challenges of AI Code Generationcited by 99
- 2023Unveiling Security, Privacy, and Ethical Concerns of ChatGPTcited by 53
- 2023Towards Applying Powerful Large AI Models in Classroom Teaching: Opportunities, Challenges and Prospectscited by 6
- 2021Artificial Intelligence Technologies in Education: Benefits, Challenges and Strategies of Implementationcited by 3
Built on by
Citing papers per year: 2025: 3; 2026: 3.
6 papers.
- 2025Students' Reliance on AI in Higher Education: Identifying Contributing Factorscited by 5
- 2025Understanding Human-AI Trust in Educationcited by 4
- 2026Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderatorscited by 3
- 2026What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AIcited by 2
- 2026Retrieval-Augmented Tutoring for Algorithm Tracing and Problem-Solving in AI Educationcited by 2
- 2025Designing and Evaluating Chain-of-Hints for Scientific Question Answeringcited by 0
- 2026Retrieval-Augmented Tutoring for Algorithm Tracing and Problem-Solving in AI Education13 May 2026
- 2026Trust and Reliance on AI in Education: AI Literacy and Need for Cognition as Moderators1 Apr 2026
- 2026What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI24 Feb 2026
- 2025Designing and Evaluating Chain-of-Hints for Scientific Question Answering24 Oct 2025
- 2025Students' Reliance on AI in Higher Education: Identifying Contributing Factors16 Jun 2025
- 2025Understanding Human-AI Trust in Education10 Jun 2025