The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Unlocking the Power of ChatGPT: A Framework for Applying Generative AI in Education
Open accessAbstract
Purpose: Artificial intelligence (AI) chatbots, such as ChatGPT and GPT-4, developed by OpenAI, have the potential to revolutionize education. This study explores the potential benefits and challenges of using ChatGPT in education (or “educative AI”). Design/Approach/Methods: This paper proposes a theoretical framework called “IDEE” for educative AI such as using ChatGPT and other generative AI in education, which includes identifying the desired outcomes, determining the appropriate level of automation, ensuring ethical considerations, and evaluating effectiveness. Findings: The benefits of using ChatGPT in education or more generally, educative AI, include a more personalized and efficient learning experience for students as well as easier and faster feedback for teachers. However, challenges such as the untested effectiveness of the technology, limitations in the quality of data, and ethical and safety concerns must also be considered. Originality/Value: This study explored the opportunities and challenges of using ChatGPT in education within the proposed theoretical framework.
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In the citing paper
“Generative AI tools may also benefit instructors by automating monotonous administrative tasks, which leaves more time for instructors to engage with students (Su & Yang, 2023, p. 365).”
From Effects of Generative AI on Engagement and Performance Within Asynchronous Online Courses (2026) · cites this paper as Su & Yang, 2023, p. 365
In the citing paper
“These tools can be trained to be virtual tutors that can assess the learner’s level of comprehension of a topic, and then adapt the learning content to fit the needs of the learner (Su & Yang, 2023).”
From Effects of Generative AI on Engagement and Performance Within Asynchronous Online Courses (2026) · cites this paper as Su & Yang, 2023
In the citing paper
“Generative AI tools may also benefit instructors by automating monotonous administrative tasks, which leaves more time for instructors to engage with students”
From Effects of Generative AI on Engagement and Performance Within Asynchronous Online Courses (2026) · cites this paper as Su & Yang, 2023, p. 365
In the citing paper
“Prior work suggested that AI-driven systems can support parenting education [61] and provide evidence-based advice through applications and chatbots, delivering micro-interventions such as teaching parents how to praise their children effectively [11, 17] or offering strategies to teach complex concepts [55, 69].”
From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [69]
In the citing paper
“GAI offers promising support for parents by enhancing their ability to educate and engage with their children.”
From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [69]
In the citing paper
“Prior work highlighted the limitations of GAI, such as its limited effectiveness in more complex learning tasks,the limited quality of the training data, and its inability to offer comprehensive educational support [69].”
From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [69]
In the citing paper
“It can help create personalized learning experiences by providing timely feedback and tailoring content [28, 55, 69], enhancing positive learning experiences [39].”
From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [69]
In the citing paper
“There is also a significant risk of GAI producing inaccurate or biased information, discouraging independent thought among children, and threatening user privacy [27, 28, 69].”
From SET-PAiREd: Designing for Parental Involvement in Learning with an AI-Assisted Educational Robot (2025) · cites this paper as [69]
In the citing paper
“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 [74]
In the citing paper
“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 [74]
Citations
Cites
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., et al. (2021) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2019.08.002 · Cited by 4,611 · cited 1×
“The use of arti fi cial intelligence (AI) in education has gained signi fi cant attention in recent years, with a growing number of educational institutions and organizations exploring the potential bene fi ts of AI-driven technologies (Dwivedi et al., 2021; Su & Yang, 2022).”
BackgroundBAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 3,939
Baidoo-Anu, D., & Owusu Ansah, L. (2023) · doi:10.2139/ssrn.4337484 · Cited by 3,004 · cited 1×
“ChatGPT has recently been used in a variety of fi elds, including library services (Lund & Wang, 2023), healthcare (Ayd ı n & Karaarslan, 2022), and education (Baidoo-Anu & Owusu Ansah, 2023; Rudolph et al., 2023).”
MethodConceptualizing AI literacy: An exploratory review
Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2021.100041 · Cited by 2,205
ChatGPT is fun, but not an author
Thorp, H. H. (2023) · Science · doi:10.1126/science.adg7879 · Cited by 1,437 · cited 2×
“ChatGPT is a type of large language model (Thorp, 2023).”
BackgroundChatting about ChatGPT: how may AI and GPT impact academia and libraries?
Lund, B. D., & Wang, T. (2023) · Library Hi Tech News · doi:10.1108/lhtn-01-2023-0009 · Cited by 1,355
Chatting about ChatGPT: How May AI and GPT Impact Academia and Libraries?Preprint
Lund, B. D., & Ting, W. (2023) · Social Science Research Network · doi:10.2139/ssrn.4333415 · Cited by 1,089 · cited 2×
“ChatGPT has recently been used in a variety of fi elds, including library services (Lund & Wang, 2023), healthcare (Ayd ı n & Karaarslan, 2022), and education (Baidoo-Anu & Owusu Ansah, 2023; Rudolph et al., 2023).”
MethodChatGPT and other large language models are double-edged swords
Shen, Y., Heacock, L., Elias, J., Hentel, K. D., Reig, B., Shih, G., & Moy, L. (2023) · Radiology · doi:10.1148/radiol.230163 · Cited by 1,008 · cited 1×
“AI literacy also involves understanding the ethical, legal, and social implications of AI, and the ability to communicate effectively about AI issues and ideas (Su et al., 2023).”
BackgroundYang, W. (2022) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2022.100061 · Cited by 606 · cited 2×
“It encompasses a range of skills and knowledge, including the ability to comprehend AI concepts, techniques, and algorithms as well as the ability to analyze and evaluate AI systems and their applications (Su & Zhong, 2022; Yang, 2022).”
BackgroundSelf-citationArtificial Intelligence (AI) Literacy in Early Childhood Education: The Challenges and Opportunities
Su, J., Ng, D. T. K., & Chu, S. K. W. (2023) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2023.100124 · Cited by 489 · cited 1×
“AI literacy also involves understanding the ethical, legal, and social implications of AI, and the ability to communicate effectively about AI issues and ideas (Su et al., 2023).”
BackgroundSelf-citation
Flagged first, then by citations
Research works printed but not linked: 2
- Liebrenz M., 2023, The Lancet Digital Health, 1
- Rudolph J., 2023, Journal of Applied Learning and Teaching, 6, 1
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Imanuel, S. (2026) · Edutik Jurnal Pendidikan Teknologi Informasi dan Komunikasi · doi:10.67142/edutik.v6i3.417
Ali, I. M., & Arpacı, İ. (2026) · Education and Information Technologies · doi:10.1007/s10639-026-14087-w
“In education, AI has been associated with more personalized learning support for students and greater pedagogical flexibility for instructors (Chan & Hu, 2023; Su et al., 2023; Su & Yang, 2023).”
Generative AI Agents in Personalized Learning and Assessment: A Systematic Bibliometric Review
Zrigui, F., Cheniti‐Belcadhi, L., Guyeux, C., & Laiymani, D. (2026) · IEEE International Conference on Smart Sustainable Systems for Computer and Engineering Applications (3SCEA) · doi:10.1109/3scea68071.2026.11603193 · Cited by 1
“First, a strong emphasis on pedagogical frameworks and student adoption is evident in highly cited works by [15] (Rank 1) and [16] (Rank 2).”
Ng, K., Ng, R. Y.-K., Hon, D., Cheung, S. K. S., Chui, K. T., Wells, R. N., & Chan, S. C. (2026) · Lecture notes in computer science · doi:10.1007/978-981-92-3761-6_20
Giray, L., Nemeño, J., Jadulos, M. X., Abosejo, M. M., & Fabros, B. G. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-33997-3_11
Zhang, H., Tang, Q., Wang, J., Yang, L., & Deng, W. (2026) · SAGE Open · doi:10.1177/21582440261462203
Khan, A., Hussain, S., & Khan, F. N. (2026) · Quality & Quantity · doi:10.1007/s11135-026-03030-3
Sun, J. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7210620
Assessing Graduate Students’ Perceptions in Exploring Generative AI for Scientific Writing
Polastri, P. C. P., Linhalis, F., & dos Reis, J. C. (2026) · Anais do Workshop sobre as Implicações da Computação na Sociedade (WICS) · doi:10.5753/wics.2026.23311
Teacher Mediation and the Contingent Promise of Generative AI in Mathematics Education
Canonigo, A. M. (2026) · Journal of Computer Assisted Learning · doi:10.1002/jcal.70307
Designing and Developing Rights-Based Architectures for GenAI in Special and Inclusive Classrooms
Alam, A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-9169-4.ch004
Li, W., Zhang, W., Li, M., & Zhang, Y. (2026) · Journal of Intelligence · doi:10.3390/jintelligence14080185
Geinitz, S., Rajan, R., Peprah, K., Schmidt, K. C. S., Singh, S., & Jay, S. M. (2026) · Lecture notes in networks and systems · doi:10.1007/978-3-032-25387-3_1
Laviola, F., Palese, B., Kim, S. T., & Cucari, N. (2026) · European Research on Management and Business Economics · doi:10.1016/j.iedeen.2026.100327
Acosta, R. R., Almanzor, L. A., Cierto, I., Toledo, A. M., & Cajurao, E. C. (2026) · Journal of Learning Theory and Methodology · doi:10.17309/jltm.2026.7.2.07
Tseng, S.-S., Yeh, H., & Chiang, K. M. (2026) · European Journal of Teacher Education · doi:10.1080/02619768.2026.2720628
Maxim, B. R., Ghammam, A., Roy, M., Gandi, S., & Gujarathi, A. (2026) · ASEE Annual Conference & Exposition · doi:10.18260/1-2--60806
Metadata
- Authors
- Su (苏嘉红), J., & Yang (杨伟鹏), W.
- Affiliations
- The University of Hong Kong
- The Education University of Hong Kong
- Venue
- ECNU Review of Education
- Publisher
- SAGE Publications
- Published
- 2023-04-19
- Volume
- 6
- Issue
- 3
- Pages
- 355-366
- ISSN
- 2096-5311 (ISSN-L)
- 2632-1742
- OpenAlex
- W4366489368
- Cited by
- 625
- References
- 12
- Citations by year
- 2026: 135 · 2025: 234 · 2024: 204 · 2023: 52
- FWCI
- 146.68
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- ECNU Review of Education (publishedVersion, cc-by-nc)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Education › 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, generative AI in education, AI chatbots, personalized learning, teacher feedback, AI ethics, AI safety, educational technology effectiveness, educational automation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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