Cited by 1,080Artificial Intelligence in EducationTeaching and Learning ProgrammingArtificial Intelligence in Healthcare and Education

The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index; none of the 9 sources its claims cite is checked for support yet.

ChatGPT for Education and Research: Opportunities, Threats, and Strategies

Open access

Rahman, Md. Mostafizer, Watanobe, Yutaka·2023·Applied Sciences

DOI 10.3390/app13095783

Published version of a preprint

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Abstract

In recent years, the rise of advanced artificial intelligence technologies has had a profound impact on many fields, including education and research. One such technology is ChatGPT, a powerful large language model developed by OpenAI. This technology offers exciting opportunities for students and educators, including personalized feedback, increased accessibility, interactive conversations, lesson preparation, evaluation, and new ways to teach complex concepts. However, ChatGPT poses different threats to the traditional education and research system, including the possibility of cheating on online exams, human-like text generation, diminished critical thinking skills, and difficulties in evaluating information generated by ChatGPT. This study explores the potential opportunities and threats that ChatGPT poses to overall education from the perspective of students and educators. Furthermore, for programming learning, we explore how ChatGPT helps students improve their programming skills. To demonstrate this, we conducted different coding-related experiments with ChatGPT, including code generation from problem descriptions, pseudocode generation of algorithms from texts, and code correction. The generated codes are validated with an online judge system to evaluate their accuracy. In addition, we conducted several surveys with students and teachers to find out how ChatGPT supports programming learning and teaching. Finally, we present the survey results and analysis.

AI snapshot

Written from the paper’s full text.

TL;DR

This paper examines ChatGPT’s opportunities and threats for education and research, with a focus on programming learning and teaching. It combines coding experiments on an online judge system with surveys of students and teachers, finding generally useful support but also accuracy, integrity, and over-reliance concerns.

Key findings

In code-generation experiments, ChatGPT’s generated code was correct about 95.83% of the time on a basic compiler and about 75% on the Aizu Online Judge (AOJ), with an average accuracy of 85.42%.
Among surveyed students, 78.8% had used ChatGPT for programming problems, 86.7% said its suggestions helped solve programming problems, and 92.9% found it useful for learning programming; most student satisfaction ratings were 4/5 (36.6%) or 5/5 (20%).
About 60% of surveyed teachers had used ChatGPT for teaching programming, but about 50% rated satisfaction as 3/5, suggesting limited trust; one teacher said ChatGPT “is still not perfect to answer some exams of my Java class.”
The paper identifies threats including cheating on online exams and assignments, diminished critical thinking, difficulty evaluating AI-generated text/code, ethical implications and bias, and blind reliance on generative AI; proposed strategies include clear assignment instructions, plagiarism detection, proctoring, comparing responses, and follow-up questions.

Methods

The authors conducted coding-related experiments with ChatGPT: code generation from problem descriptions, pseudocode generation, code correction/debugging, and code optimization.
For code generation, they used eight random “Algorithms and Data Structures” problems from AOJ, generated code three times per problem, and validated results on both a basic compiler and the AOJ platform.
They also conducted surveys with undergraduate, Master’s, and doctoral students and with teachers about ChatGPT’s support for programming learning and teaching; the paper reports percentages but not the total number of respondents.

Limitations

The paper states that experiments were conducted on ChatGPT during active development, so results may vary with new ChatGPT versions, different questions, different problem descriptions, and different solution codes for optimization.
The paper notes that although ChatGPT generated about 85.42% correct code on average, adjustments may still be necessary for error-free compilation and acceptance, and it failed an elementary counting task involving the digit “8.”
Evident from the text: the survey sample size is not reported, and the coding experiments are limited to eight AOJ problems with three generations each, which restricts generalizability.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.3390/app13095783

Cites

71 of 71 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 9 cited sources checked · 0 supported · 0 flagged

Show all 33 claims

It may state two separate claims as one. 18
Probably not a substantial claim. 31

A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The suggestions proved to be interesting to the programmers and helpful in resolving the code errors.”
§ ChatGPT for Education and Research: Opportunities, Threats, and Strategies > 4.3. Error Checking and Debugging in Code
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
It may state two separate claims as one.
- Rests on an assumption: The authors' assessment that ChatGPT's debugging suggestions were helpful reflects actual programmer benefit.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“it can be difficult to hold anyone accountable for the responses generated”
§ ChatGPT for Education and Research: Opportunities, Threats, and Strategies > Ethical implications and potential biases:
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
- Rests on an assumption: ChatGPT generates responses without human intervention.
In the paper
“Cotton et al. [57] presented several strategies for recognizing texts from LLMs such as ChatGPT, including language inconsistencies, a lack of proper citations, factual errors, ambiguity, and poor context awareness.”
§ ChatGPT for Education and Research: Opportunities, Threats, and Strategies > -Sam Altman, CEO of OpenAI
What the sources say
- Not checked yetcites [57] Cotton, D.R., Cotton, P.A., and Shipway, J.R. (2023). Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT. Innov. Educ. Teach. Int., 1–12. source
Strength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passes
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“The answers and texts generated by ChatGPT are becoming indistinguishable from human-generated answers and texts.”
§ ChatGPT for Education and Research: Opportunities, Threats, and Strategies > -Sam Altman, CEO of OpenAI
What the sources say
- Not checked yetcites [57] Cotton, D.R., Cotton, P.A., and Shipway, J.R. (2023). Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT. Innov. Educ. Teach. Int., 1–12. source
- Not checked yetcites [60] Elkins, 2020, Can GPT-3 pass a Writer’s turing test?, J. Cult. Anal.
- Not checked yetcites [61] Gao, C.A., Howard, F.M., Markov, N.S., Dyer, E.C., Ramesh, S., Luo, Y., and Pearson, A.T. (2022). Comparing scientific abstracts generated by ChatGPT to original abstracts using an artificial intelligence output detector, plagiarism detector, and blinded human reviewers. bioRxiv. source
Load-bearingStrength:plain· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In short, ChatGPT threatens the fairness and validity of online exams and assignments.”
§ ChatGPT for Education and Research: Opportunities, Threats, and Strategies > 6. Threats and Strategies
Load-bearingStrength:plain· not yet calibratedCausal:direct· not yet calibrated
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
Probably not a substantial claim.
- Rests on an assumption: ChatGPT can generate human-like text for academic topics.

40 of 40

The paper relies on this without support.
The eight randomly selected AOJ problems and three code generations per problem are representative of ChatGPT's general code-generation performance for programming learning.
“We leveraged the problem descriptions of eight random problems and generated codes three times for each problem on the basis of the same description.”
The paper relies on this without support.
The survey respondents are representative of students and teachers who use ChatGPT for programming learning and teaching.
“We conducted a comprehensive survey on how ChatGPT supports programming learning and teaching among undergraduate, Master's, and doctoral students and teachers.”
The paper relies on this without support.
Students' self-reported helpfulness of ChatGPT suggestions reflects actual improvement in solving programming problems.
“By asking the question “Do ChatGPT's suggestions help you in solving programming problems?”,we tried to assess how ChatGPT suggestions help students.We found that about 86.7% of the students answered “Yes”.”
The paper relies on this without support.
The authors' judgment that ChatGPT-generated explanations and pseudocode are easy to understand and useful reflects learners' actual understanding.
“The results demonstrate that ChatGPT can generate easy-to-understand explanations and pseudocode that are useful for learners to understand algorithmic concepts.”
The paper relies on this without support.
The authors' assessment that ChatGPT's debugging suggestions were helpful reflects actual programmer benefit.
“The suggestions proved to be interesting to the programmers and helpful in resolving the code errors.”
The paper relies on this without support.
ChatGPT can generate human-like text for academic topics.
“As ChatGPT can generate human-like text for academic topics”
The paper relies on this without support.
LLMs rely heavily on training data, and when the data contain biases or anomalies, it could lead to unfair results.
“Typically, LLMs rely heavily on training data, and when the data contain biases or anomalies, it could lead to unfair results.”
The paper relies on this without support.
The internal mechanisms and processes of ChatGPT are not sufficiently open and transparent to users about how they work.
“Furthermore, the internal mechanisms and processes are not sufficiently open and transparent to users about how they work.”
The paper relies on this without support.
ChatGPT generates responses without human intervention.
“Because ChatGPT generates responses without human intervention”

9 of 9

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Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

Table 1 names a different lead author for reference 25
Minor
Table 1 attributes reference 25 to Simon et al., while the reference list identifies Frieder as its lead author.

1 of 1

1 retracted

Retracted: Chat With ChatGPT on Intelligent Vehicles: An IEEE TIV Perspective
Du, H., Teng, S., Chen, H., Ma, J., Wang, X., Gou, C., Li, B., Ma, S., Miao, Q., Na, X., et al. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3253281 · Cited by 164 · cited 1×
“Moreover, ChatGPT has recently been applied to tasks in different domains such as software engineering [36], medical education [37], data augmentation [38], ﬁfth industrial revolution [39], code generation [40], intelligent vehicles [41], and solving AI tasks [42].”
Method
Retracted
Attention Is All You Need
Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017) · arXiv · doi:10.48550/arxiv.1706.03762 · Cited by 120,404 · cited 1×
“Therefore, the Transformer architecture was introduced [4] to alleviate this problem.”
Method
Language Models are Few-Shot Learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372 · cited 1×
“Generative pretrained transformer (GPT)-3 is a large language model (LLM) based on the Transformer architecture [5,6] that has achieved signiﬁcant success in NLP tasks.”
Background
ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 3×
“Furthermore, several studies [9–12 Frieder et al. [25] tested the mathematical capabilities of ChatGPT on GHOSTS and handcrafted datasets.”
BackgroundMethod
Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C. L., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al. (2022) · arXiv · doi:10.48550/arxiv.2203.02155 · Cited by 4,208 · cited 2×
“Finally, the resulting model is called InstructGPT [8].”
BackgroundMethod
Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models
Kung, T. H., Cheatham, M., ChatGPT, Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., et al. (2022) · doi:10.1101/2022.12.19.22283643 · Cited by 4,115
Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115 · cited 1×
“Kung et al. [26] evaluated the performance of ChatGPT on the US Medical Licensing Exam, which includes three exams: Step 1, Step 2CK, and Step 3.”
Background
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087 · cited 3×
“Students can be given clear instructions on assignments and online exams on how to structure their assignments and answer their questions online [57].”
Background
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079

Flagged first, then by citations

Show all 58 references

Research works printed but not linked: 3

Rahman, M.M. (2022). Data Analysis and Code Assessment Using Machine Learning Techniques for Programming Activities. [Ph.D. Thesis, The University of Aizu].
Avila-Chauvet, L., Mejía, D., and Acosta Quiroz, C.O. (2023). Chatgpt as a Support Tool for Online Behavioral Task Programming. SSRN, Available online: https://ssrn.com/abstract=4329020.
Jiao, W., Wang, W., Huang, J.t., Wang, X., and Tu, Z. (2023). Is ChatGPT a good translator? A preliminary study. arXiv.

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Judging the institution: Simulated jurisprudence and the governance of professional futures
Hibbert, K. (2025) · Policy Futures in Education · doi:10.1177/14782103251386648 · Cited by 3
“It is informed by emerging research on AI-enabled methods (Ahmed and Mahmood, 2024; Fan et al., 2024; Gao et al., 2024; Rahman and Watanobe, 2023; Stokel-Walker, 2023).”
Echoes of Automation: The Increasing Use of LLMs in Newsmaking
Ansari, A., Zhang, D. C., Tripto, N. I., & Lee, D. (2025) · Lecture notes in computer science · doi:10.1007/978-3-032-07715-8_1 · Cited by 6
Measuring student receptivity to ChatGPT in higher education: A case study from Peru
Chura‐Quispe, G., Estrada-Araoz, E. G., Ayay-Arista, G., Quiac, S. C., García, P. P. A., & Cruz-Laricano, E. O. (2025) · Online Journal of Communication and Media Technologies · doi:10.30935/ojcmt/17380 · Cited by 5
ChatGPT in the academia: exploring teachers' and students' practices and perspectives in higher education
Begum, M., Butt, M. N., & Ullah, S. (2025) · Asian Education and Development Studies · doi:10.1108/aeds-06-2025-0257 · Cited by 2
Programming Challenges and Perceptions: A Study of Separate Groups before and after the Release of ChatGPT
Ada, M. B. (2025) · ACM Transactions on Computing Education · doi:10.1145/3777904 · Cited by 3
Reimagining instructional design: ChatGPT, Bloom's taxonomy, and the role of teacher expertise
Eideh, B. A. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.102325 · Cited by 6
ChatGPT’s benefits, acceptance, and ethical challenges for teaching and learning in key African countries: a systematic review of literature from 2022 to 2024
Dake, D. K., & Gbagbo, F. Y. (2025) · Discover Education · doi:10.1007/s44217-025-01074-5 · Cited by 3
“The challenges discovered by Bettayeb et al. [34], Memarian and Doleck [36], and Elbanna and Armstrong [37], Rahman and Watanobe [38], all align with the findings of our study that mentioned transparency, plagiarism, biases, ethical concerns, privacy, laziness, lack of higher-order skills,…”
The Effect of Artificial Intelligence-Supported Activities on Academic Achievement, Critical Thinking and Innovation Skills in Social Studies Classes
ARIKAN, A. (2025) · Anadolu Kültürel Araştırmalar Dergisi · doi:10.63556/ankad.v9i4.269 · Cited by 4
“Thus, there is a certain need for empirical research on this topic (Aşkun, 2023; Guo & Wang, 2023; İşler & Kılıç, 2021; Jeon & Lee, 2023; Labadze et al., 2023; Oksanen et al., 2020; Rahman & Watanobe, 2023; Williamson, 2020).”
Unlocking the Future: A Comprehensive Review of ChatGPT in Education
Kim, D., Wang, C. K., Borowiec, K., Rein, N., Cho, J.-H. A., & Liu, J. J. (2025) · Technology Knowledge and Learning · doi:10.1007/s10758-025-09923-w · Cited by 2
Statistical and qualitative analysis of ChatGPT and human raters in preservice teachers’ writing assessment
GÜLDEN, B., Bilge, H., & Uysal, P. K. (2026) · International Journal of Assessment Tools in Education · doi:10.21449/ijate.1678002 · Cited by 4
“Although positive and negative reactions to AI have divided the educational community (Rahman & Watanobe, 2023), expectations for AI in education are high (Altundal, 2024).”
A new frontier in biostatistics: evaluating the accuracy of ChatGPT-4 vs. R in analysing liver resection data
Jobeir, B. A., Alahdal, A., Saner, F., Staubli, S. M., Broering, D. C., & Raptis, D. A. (2024) · Journal of Global Health Economics and Policy · doi:10.7189/001c.123577 · Cited by 2
ADAPTIVE LEARNING PLATFORMS FOR PERFORMING ARTS
Shinde, J. M., Chaudhary, S., Bhilare, A., Jarad, R., Anitha, K., & Satav, M. S. S. (2026) · ShodhKosh Journal of Visual and Performing Arts · doi:10.29121/shodhkosh.v7.i1s.2026.7081 · Cited by 2
Use of ChatGPT as a supplemental learning tool in mathematics
Sosas, M. R. D., Fat, A. F. G., Dangculos, J. M. M., Anoba, H. R. P., Remiscal, C. G., & Aleguen, J. M. (2026) · Contemporary Mathematics and Science Education · doi:10.30935/conmaths/17989 · Cited by 6
“These contributions provide a foundation for future studies to critically explore AI adoption in mathematics education and inform teacher preparation programs on how to guide ethical, effective, and pedagogically sound use of emerging AI tools.”
Influential
Is ChatGPT a Rational Assistant for University Students During Mathematical Reasoning?
Urhan, S., Gençaslan, O., & Dost, Ş. (2026) · Science & Education · doi:10.1007/s11191-026-00725-9 · Cited by 2
Something Old, Something New: WebQuests and GenAI in Teacher Education
Tiernan, P., Donlon, E., Hamash, M., & Lovatt, J. (2026) · AI in Education · doi:10.3390/aieduc2010007 · Cited by 3
“Teachers should also consider how GenAI aligns with curricular, pedagogical, and student needs (Rahman & Watanobe, 2023).”
Exploring AI integration in United Arab Emirates’ teacher education programmes: the voice of educators leading the change
Massouti, A., Baroudi, S., & Shaya, N. (2026) · Cambridge Journal of Education · doi:10.1080/0305764x.2026.2651759 · Cited by 3
“Various learning platforms have increasingly adopted AI tools, from personalising the learning experience to leading a transformation in teaching and learning practices for all (Akavova et al., 2023; Farrokhnia et al., 2023; Rahman & Watanobe, 2023; Salas-Pilco et al., 2022).”
Teaching Ethical AI Use in Graduate Nursing Programs: A Scaffolded Model for Professional Identity Formation
Zakhari, R. (2026) · Journal of Nursing Education · doi:10.3928/01484834-20260504-01 · Cited by 2
Artificial intelligence-enhanced inquiry-based learning and higher-order thinking skills: a meta-analysis
Yulanda, N. I. P., Gestiardi, R., Subanji, S., Nusantara, T., & Setyosarı, P. (2026) · Learning Research and Practice · doi:10.1080/23735082.2026.2672411 · Cited by 3
Pre-service mathematics teachers' use of artificial intelligence: an extended technology acceptance model with self-efficacy (the case of ChatGPT)
Demir, B. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1826980 · Cited by 2
“Furthermore, it is noted that systems based on large language models can be used as digital assistants in teachers’ teaching processes and can contribute to teachers planning their teaching activities more eﬃciently (Rudolph et al., 2023; Rahman and Watanobe, 2023; Aydin and Karaarslan, 2023).”
Influential
The role of ChatGPT in higher education: a systematic literature review of applications, perceptions and ethical implications
Abdelrahman, M., Hu, S., Al-Shamaileh, O., Hammady, R., & Nizamuddin, N. (2026) · Journal of Information Communication and Ethics in Society · doi:10.1108/jices-09-2025-0261 · Cited by 3
Structured AI-Supported Assessment (SAISA): A Novel Design Integrating ChatGPT to Support Clinical Reasoning and Reflective Engagement in Veterinary Students
Sousa, S. A., Bukhari, S. S. U. H., Tang, M., Man, Y. K., Hobi, S., & Steagall, P. V. M. (2026) · Journal of Veterinary Medical Education · doi:10.3138/jvme-2025-0198 · Cited by 2
From AI dependence to reflective collaboration: psychological ownership, competency anxiety, and perceived support in AI-assisted learning
Li, X., Xian, X., & Du, P. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1903784 · Cited by 3
“This pattern is particularly important in writing, coding, literature review, and conceptual analysis, where generative systems are increasingly used for educational and research-related tasks (Kasneci et al., 2023; Lee et al., 2024; Rahman and Watanobe, 2023; Yan et al., 2024).”
Artificial intelligence in academic writing: A decade of trends and influences
Ghosh, P. L., Barua, S., & Golder, U. (2026) · Sustainable Futures · doi:10.1016/j.sftr.2026.102034 · Cited by 3
مراجعة منهجية لاستخدامات وتحديات ChatGPT في التعليم
المقرن., ن. أ. ع. ا. (2024) · التربية (الأزهر) مجلة علمية محکمة للبحوث التربوية والنفسية والاجتماعية) · doi:10.21608/jsrep.2024.344161 · Cited by 3
Innovación, inteligencia artificial y su utilidad para la mejora del aprendizaje basado en evidencia
Jara, M. P. (2024) · Cuidado de Enfermería y Educación en Salud · doi:10.15443/ceyes.v8i1.2105 · Cited by 2
Can the Potential Contributions of ChatGPT in Tourism Education Be Realized?
Yaşar, E. (2024) · Advances in higher education and professional development book series · doi:10.4018/979-8-3693-1666-5.ch009 · Cited by 2
The Performance of ChatGPT on Short-answer Questions in a Psychiatry Examination: A Pilot Study
Lin, C.-C., Plooy, K. D., Gray, A. R., Brown, D. A., Hobbs, L., Patterson, T., Tan, V., Fridberg, D., & Hsu, C.-W. (2024) · Taiwanese Journal of Psychiatry · doi:10.4103/tpsy.tpsy_19_24 · Cited by 2
The Use and Effects of ChatGPT in Tourism Education
Yaşar, E., Öztürk, İ., Yayla, E., & TÜR, E. (2024) · Advances in systems analysis, software engineering, and high performance computing book series · doi:10.4018/979-8-3693-3033-3.ch007 · Cited by 2
THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: UNIVERSITY SOCIAL RESPONSIBILITY AND STAKEHOLDERS’ PERCEPTIONS
Ņikadimovs, O., & Vēvere, V. (2024) · Environment Technology Resources Proceedings of the International Scientific and Practical Conference · doi:10.17770/etr2024vol2.8015 · Cited by 5
“Lesson preparation, personalized learning support, responding to learners' questions, fast assessment and evaluation, and many more opportunities for educators thus saving a substantial amount of time [21].”
Background
PHƯƠNG PHÁP XÂY DỰNG ỨNG DỤNG HỖ TRỢ HỌC TẬP DỰA TRÊN CHATGPT API
Long, H. N. L. H. N., Thịnh, N. Đ. T. N. Đ., Thưởng, L. D. T. L. D., Đăng, V. H. Đ. V. H., & Việt, T. H. V. T. H. (2024) · TẠP CHÍ KHOA HỌC TRƯỜNG ĐẠI HỌC QUỐC TẾ HỒNG BÀNG · doi:10.59294/hiujs.khqg.2024.003 · Cited by 2
“- Tạo thói quen lười biếng và ỷ lại, trong trường hợp tệ hơn, sinh viên có thể dùng ChatGPT để gian lận trong thi cử hoặc để tự động viết báo cáo, luận văn [2].”
Exploring the Impacts of Implementing Block Mode of Teaching in Higher Education
Trinh, N. T. T., Ghapanchi, A. H., & Purarjomandlangrudi, A. (2024) · International Journal of Emerging Technologies in Learning (iJET) · doi:10.3991/ijet.v19i06.49229 · Cited by 2
Reshaping and Transforming of English Teaching in Higher Education in the ChatGPT Era: An Empirical Study Based on Big Data
Liu, Y. (2024) · IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C) · doi:10.1109/qrs-c63300.2024.00169 · Cited by 4
“This technology offers exciting opportunities for students and educators, including personalized feedback, increased accessibility, interactive conversations, lesson preparation, evaluation, and new ways to teach complex concepts [3].”
Background
Introducción de inteligencia artificial en la evaluación de asignaturas de teoría e historia
Nadal, M. F., & Mora, E. S. (2024) · Jornadas sobre Innovación Docente en Arquitectura (JIDA) · doi:10.5821/jida.2024.13259 · Cited by 3
GPT AI in Computer Science Education: A Systematic Mapping Study
Strik, B., Menolli, A., & Brancher, J. D. (2024) · Anais do ... Simpósio Brasileiro de Informática na Educação/Anais do Simpósio Brasileiro de Informática na Educação · doi:10.5753/sbie.2024.242103 · Cited by 2
O Uso e o Potencial de Inteligências Artificiais no Aprendizado de Algoritmos e Programação de Computadores
de Carvalho, S. M. F. T., & de Oliveira, I. C. A. (2024) · Anais do ... Simpósio Brasileiro de Informática na Educação/Anais do Simpósio Brasileiro de Informática na Educação · doi:10.5753/sbie.2024.244954 · Cited by 2
CHATGPT AS AI ASSISTANT IN THE PRE-SERVICE TEACHERS TRAINING AND THEIR FUTURE ROLE IN SECONDARY SCHOOLS: RESEARCH IN PROGRESS
Pesce, M., & Blanco, D. F. (2024) · European Journal of Education Studies · doi:10.46827/ejes.v11i12.5687 · Cited by 4
“Additionally, the development of new technologies, such as AI-based plagiarism detectors, is essential to uphold the integrity of education and research (Rahman & Watanobe, 2023).”
ChatGPT: The Future Research Assistant or an Academic Fraud? [A Case Study on a State University Located in Jakarta, Indonesia]
Rahardyan, T. M., Susilo, C. H., Iswara, A., & Hartono, M. L. (2024) · Asia Pacific Fraud Journal · doi:10.21532/apfjournal.v9i2.347 · Cited by 5
“Once a manuscript is completed, ChatGPT can automatically detect grammatical errors (Rahman & Watanobe, 2023).”
Behavioral Intention and Use of ChatGPT Among Accounting and Finance Students: A Two-Year Comparative Study
Ziemba, E. W., Grabara, D., Renik, K., & Maruszewska, E. W. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-78465-1_6 · Cited by 2
Innovative Approach to Agile Education: Generative AI-Supported Planning Poker Simulation
Nafil, K., & Lefdaoui, Y. (2024) · International Conference on Information Technology Based Higher Education and Training (ITHET) · doi:10.1109/ithet61869.2024.10837671 · Cited by 5
Early Coding Education and its Multidimensional Impact on Preschool Development: An Analysis of ChatGPT’s Insights
Başaran, M., Vural, Ö. F., Metin, Ş., & Tamur, S. (2025) · International Journal of Early Childhood · doi:10.1007/s13158-024-00411-3 · Cited by 2
“This technology offers exciting opportunities for students and educators, including personalized feedback, increased accessibility, interactive conversations, lesson preparation, assessment, and new ways to teach complex concepts (Rahman & Watanobe, 2023).”
Introducing ChatGPT to Education in Science Museums: A Conceptual Framework
Fareed, M. W. (2025) · Journal of Museum Education · doi:10.1080/10598650.2024.2440287 · Cited by 2
Leveraging ChatGPT-4 for Enhanced Education: Personalized Problem-Solving and Consistent Learning
Khan, I. M., Chohan, M. I., & Malik, S. I. (2024) · International Conference on Computing and Data Analytics (ICCDA) · doi:10.1109/iccda64887.2024.10867340 · Cited by 2
ChatGPT in Academia and Research: A Comprehensive Review of Integrating AI in Higher Education
Thakkar, A., Asmelash, A., & Hirpo, H. D. (2025) · Springer eBooks · doi:10.1007/978-981-96-2355-6_10 · Cited by 2
Acceptance of ChatGPT in social work students
Meinhardt‐Injac, B., Späte, J., Siemer, L., & Witter, S. (2025) · Forum for education studies. · doi:10.59400/fes1812 · Cited by 3
“ChatGPT may also enhance teaching practices by providing access to a wide range of learning resources, aiding in lesson planning, and automating student assessment and feedback [3,6,7].”
Influential
The Impact of AIGC on Modern Education: Transforming Learning and Teaching Methods
Cheng, Y., & Wang, T. (2024) · International Conference on Intelligent Education and Intelligent Research (IEIR) · doi:10.1109/ieir62538.2024.10959761 · Cited by 2
“Additionally, there are instances demonstrating that the use of AIGC can enhance student engagement in specific courses [33], improve deep learning ability [34], increase overall learning efficiency [35], and support programming teaching [36].”
ChatGPT's application in management education: In-depth critical analysis of opportunities, threats, and strategies
Hasan, M. T., Jin, H. H., Mahmood, M., Hasan, M. T., Sarkar, J. B., Salleh, N. M., & Chowdhury, A. Y. (2025) · Multidisciplinary Reviews · doi:10.31893/multirev.2025338 · Cited by 3
The role of ChatGPT in junior high school physics education: Insights from teachers and students and guidelines for optimal use
Bessas, N., Tzanaki, E., Vavougios, D., & Plagianakos, V. (2025) · Social Sciences & Humanities Open · doi:10.1016/j.ssaho.2025.101610 · Cited by 7
Occupational Therapy Students’ Perceptions of Using ChatGPT for an Academic Course Assignment
Tom, D., Wu, R., & Shea, C. (2025) · The Open Journal of Occupational Therapy · doi:10.15453/2168-6408.2376 · Cited by 3
Learning in the Age of LLMs: Boosting not Bypassing the Learning Process
Blake, J. (2025) · Educational communications and technology yearbook · doi:10.1007/978-981-96-2921-3_9 · Cited by 3
AI-Driven Conservation of the Endangered Twisted Yew (Taxus contorta Griff.) in the Western Himalaya
Din, S., Ali, H., Panagopoulos, Τ., Alam, J., Malik, S., & Sher, H. (2025) · Sustainability · doi:10.3390/su17198541 · Cited by 2
“AI models can also forecast future habitat risks due to land use changes, climate effects, and human pressures [30].”
Manfaat chatGPT dalam hubungan manusia dengan alam: menggunakan chatGPT di bidang pertanian
Basuki, R. S., Martin, L., & Mulyani, N. (2023) · Jurnal Riset Multidisiplin dan Inovasi Teknologi · doi:10.59653/jimat.v1i01.161 · Cited by 2
À conversa com o coautor, que o não quis ser, ChatGPT
Moreira, C. A. A., França, P. F. P., Beites, P. D., & Ersari, E. (2023) · Revista Prática Docente · doi:10.23926/rpd.2023.v8.n2.e23042.id711 · Cited by 2
Would Business Applications Such as the FinTech Benefit by ChatGPT? If So, Where and How?
Gill, M. A., Zhou, X., Nabi, F., Genrich, R., & Gururajan, R. (2023) · IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · doi:10.1109/wi-iat59888.2023.00090 · Cited by 2
“…the dialogue, providing more personalized and natural interactions (Qureshi, B., 2023). c) Task Flexibility: ChatGPT can perform various tasks, including answering questions, providing explanations, generating creative content, and assisting with problem-solving (Rahman and Watanobe, 2023).”
Background
A State-of-the-Art Review on the Implications of ChatGPT in Educational Practices and Research
Linda, S. (2024) · Advances in business information systems and analytics book series · doi:10.4018/979-8-3693-2314-4.ch001 · Cited by 2
The use of ChatGPT in the study of economics: a SWOT analysis
Pittner, D., Romih, D., & Polančič, G. (2023) · International Scientific Conference on Economics, Management and Information Technologies (ICEMIT) · doi:10.46793/icemit23.157p · Cited by 3
Mapping Challenges, Opportunities, Strategies, and Policies on the Use of ChatPGT in Indonesians Theological Higher Education
Marbun, T. O. (2024) · Journal of Religious & Theological Information · doi:10.1080/10477845.2024.2302680 · Cited by 2
Analysis of the Programming Languages Preferred by Novice Programmers for Solving Programming Problem
Amin, M. F. I., Rahman, M. M., Shirafuji, A., & Watanobe, Y. (2023) · Asia Service Sciences and Software Engineering Conference (ASSE) · doi:10.1145/3634814.3634818 · Cited by 2
“Furthermore, several studies have introduced machine learning-based models to reinforce programming education [9, 12–14].”
BackgroundSelf-citation
The Use of Persona in Foreign Language Learning Facilitated by ChatbotsPreprint
Klímová, B., Pikhart, M., & Al-Obaydi, L. H. (2023) · Research Square · doi:10.21203/rs.3.rs-3129096/v1 · Cited by 2
Responsible AI
Kumar, K., & Poonam (2025) · Wiley eBooks · doi:10.1002/9781394287499.ch17 · Cited by 2

Authors: Rahman, M. M., & Watanobe, Y.
Affiliations: University of Aizu (JP)
Corresponding author: Rahman, Md. Mostafizer
ORCID: Rahman, Md. Mostafizer
Watanobe, Yutaka
Venue: Applied Sciences
Publisher: MDPI AG
Published: 2023-05-08
Volume: 13
Issue: 9
Pages: 5783
ISSN: 2076-3417 (ISSN-L)
DOI: 10.3390/app13095783
OpenAlex: W4381982883
Semantic Scholar: 3b69ec0fc17c5134c9b002bebe283e0189bfdae5
Cited by: 1,080
References: 58
Citations by year: 2026: 193 · 2025: 338 · 2024: 425 · 2023: 124
FWCI: 253.56
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Applied Sciences (publishedVersion, cc-by)
Preprints.org (acceptedVersion, cc-by)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: Japan Society for the Promotion of Science (JSPS) KAKENHI (23H03508)
Topics: Social Sciences › Education › Artificial Intelligence in Education
Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords: ChatGPT, large language models, artificial intelligence in education, academic dishonesty, critical thinking, programming education, code generation, code correction, student and teacher perceptions

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ChatGPT for Education and Research: Opportunities, Threats, and Strategies

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