A Discussion about the Impact of ChatGPT in Education: Benefits and Concerns
Open accessAbstract
The advent of advanced machine learning models such as ChatGPT has led to significant advancements in various fields, including education. The purpose of this article is to explore the impact of ChatGPT in higher education, covering both positive and negative nuances. A critical literature review analysis was conducted, which included references from reliable sources. The methodology used in this article was based on a critical literature review method. The results of the analysis indicate that ChatGPT might have several benefits in education, including improved student engagement, personalized learning experiences, and enhanced teaching practices. However, there are also some negative implications, such as concerns over privacy, academic integrity, and the potential for bias. The article concludes by highlighting the need for further research in this area and providing recommendations for educators and policymakers.
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ChatGPT has been highlighted for fostering students' performance, engagement, and motivation and enhancing teaching practices.
“foster students’ performance, engagement and motivation [14, 44, 58], and enhance teaching practices [17, 18, 64, 74].”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [18]
Concerns have been raised that ChatGPT may disseminate false information and references, reinforce bias, compromise academic integrity, and cause potential decline in students' skills.
“These include the dissemination of false information and references [12, 23, 61, 85], biased reinforcement [47, 50], compromised academic integrity [18, 40, 66, 74], and the potential decline in students' skills [43, 61, 64, 74].”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [18]
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Understanding the role of digital technologies in education: A review
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What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00237-x · Cited by 2,003 · see citing works
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Evaluating GPT-3.5 and GPT-4 Models on Brazilian University Admission ExamsPreprint
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- Mollick, E. (2022). ChatGPT Is a Tipping Point for AI. Harvard Business Review.
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AI literacy and its implications for prompt engineering strategies
Knoth, N., Tolzin, A., Janson, A., & Leimeister, J. M. (2024) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2024.100225 · Cited by 368 · see citing works
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A systematic literature review of empirical research on ChatGPT in education
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ChatGPT in Teaching and Learning: A Systematic Review
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AI chatbots: A disguised enemy for academic integrity?
Niloy, A. C., Hafiz, R., Hossain, B. M., Gulmeher, F., Sultana, N., Islam, K. F., Bushra, F., Islam, S., Hoque, S. I., Rahman, M., et al. (2024) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2024.100396 · Cited by 26 · see citing works
- Authors
- Alves de Castro, C.
- Venue
- Journal of Business Theory and Practice
- Publisher
- Scholink Co, Ltd.
- Published
- 2023-05-07
- Volume
- 11
- Issue
- 2
- Pages
- p28
- ISSN
- 2329-2644 (ISSN-L)
- 2372-9759
- OpenAlex
- W4372311190
- Cited by
- 35
- References
- 6
- Citations by year
- 2026: 3 · 2025: 11 · 2024: 18 · 2023: 3
- FWCI
- 8.21
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- Journal of Business Theory and Practice (publishedVersion, cc-by)
- Figshare (submittedVersion, cc-by)
- Figshare (cc-by)
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- ChatGPT, large language models, higher education, student engagement, personalized learning, teaching practice, privacy concerns, academic integrity, algorithmic bias, educational technology
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