Student Perspectives on the Benefits and Risks of AI in Education
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ID: 282489
2025
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Abstract
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.
| Reference Key |
motamedi2025student
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|---|---|
| Authors | Griffin Pitts; Viktoria Marcus; Sanaz Motamedi |
| Journal | arXiv |
| Year | 2025 |
| DOI |
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