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Time to Revisit Existing Student’s Performance Evaluation Approach in Higher Education Sector in a New Era of ChatGPT — A Case Study
Open accessAbstract
response based on provided input-it has become crucial for HEIs to be exposed to the implications of AI-based tools on students' learning outcomes, commonly measured using an assessment-based approach to improve program quality, teaching effectiveness, and other learning support.An empirical study has been conducted to test the ChatGPT capability of solving a variety of assignments (from different level courses of undergraduate degree programs) to compare its performance with the highest scored student(s).Further, the ChatGPT-generated assignments were tested using the best-known tools for plagiarism detection to determine whether they could pass the academic integrity tests, including Turnitin, GPTZero, and Copyleaks.The study reported the limitations of the Bot and highlighted the implications of the newly launched AI-based ChatGPT in academia, which calls for HEIs' managers and regulators to revisit their existing practices used to monitor students' learning progress and improve their educational programs.
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“This has invoked an immediate reaction from the higher education community as the question arose as to how it may affect various forms of student performance evaluation (such as essay and thesis writing) (Chaudhry et al. 2023; Yu, 2023; Farazouli et al. 2024).”
From AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI (2024) · cites this paper as Chaudhry et al. 2023
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Cites
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
Advances in neural information processing systems 7
Cios, K. J., & Shields, M. E. (1997) · Neurocomputing · doi:10.1016/s0925-2312(97)90018-7 · Cited by 22,093
Advances in neural information processing systems 7
(1996) · Computers & Mathematics with Applications · doi:10.1016/s0898-1221(96)90463-0 · Cited by 14,759
I.—COMPUTING MACHINERY AND INTELLIGENCE
TURING, A. M. (1950) · Mind · doi:10.1093/mind/lix.236.433 · Cited by 10,290 · cited 1×
“As Pavlik (2023) reported, ChatGPT arguably has the potential to pass the Turing test (meaning humans through interactive conversations with machines cannot tell if he/she is interacting with a machine or a person, as proposed by Turing (1950).”
BackgroundClassrooms: Goals, structures, and student motivation.
Ames, C. (1992) · Journal of Educational Psychology · doi:10.1037/0022-0663.84.3.261 · Cited by 6,468
Kluger, A. N., & DeNisi, A. (1996) · Psychological Bulletin · doi:10.1037/0033-2909.119.2.254 · Cited by 5,882
Douglas, O. B., & Holland, B. F. (2015) · MacMillan Co eBooks · doi:10.1037/14910-020 · Cited by 2,283
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 · cited 2×
“…consequences of students’ relying too heavily on chatbots for learning purposes so that timely action can be taken by the universities in preparing effective guidelines and policies to facilitate the appropriate and ethical use of this new technology in education sector (Tlili et al., 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
The ABET “Professional Skills” - Can They Be Taught? Can They Be Assessed?
Shuman, L. J., Besterfield‐Sacre, M., & McGourty, J. (2005) · Journal of Engineering Education · doi:10.1002/j.2168-9830.2005.tb00828.x · Cited by 1,167
Pavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972 · cited 1×
“As Pavlik (2023) reported, ChatGPT arguably has the potential to pass the Turing test (meaning humans through interactive conversations with machines cannot tell if he/she is interacting with a machine or a person, as proposed by Turing (1950).”
BackgroundArtificial Intelligence trends in education: a narrative overview
Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.08.233 · Cited by 956
Individual and Contextual Influences on Academic Dishonesty: A Multicampus Investigation
McCabe, D. L., & Trevino, L. K. (1997) · Research in Higher Education · doi:10.1023/a:1024954224675 · Cited by 830
Open AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning
Mhlanga, D. (2023) · doi:10.2139/ssrn.4354422 · Cited by 719 · cited 1×
“They must be trained on how to make ethical use of AI bot for learning purposes and the importance of being original in ideas (Mhlanga, 2023).”
BackgroundOpen AI in Education, the Responsible and Ethical Use of ChatGPT Towards Lifelong Learning
Mhlanga, D. (2023) · Sustainable Development Goals Series · doi:10.1007/978-3-031-37776-1_17 · Cited by 718
Nonis, S., & Swift, C. O. (2001) · Journal of Education for Business · doi:10.1080/08832320109599052 · Cited by 564
Crawford, J., Cowling, M., & Allen, K.-A. (2023) · Journal of University Teaching and Learning Practice · doi:10.53761/1.20.3.02 · Cited by 547 · cited 3×
“ChatGPT has the potential to improve students’ learning outcomes by providing them with an interactive learning experience, where they can ask follow-up questions on a subject and gain in-depth knowledge (Crawford et al., 2023).”
BackgroundAI bot ChatGPT writes smart essays — should professors worry?
Stokel-Walker, C. (2022) · Nature · doi:10.1038/d41586-022-04397-7 · Cited by 543
Use chat gpt to solve programming bugs
Surameery, N. M. S., & Shakor, M. Y. (2023) · International Journal of Information technology and Computer Engineering · doi:10.55529/ijitc.31.17.22 · Cited by 382
Academic integrity: A review of the literature
Macfarlane, B., Zhang, J., & Pun, A. (2014) · Studies in Higher Education · doi:10.1080/03075079.2012.709495 · Cited by 359
García-Peñalvo, F. J. (2023) · Education in the Knowledge Society (EKS) · doi:10.14201/eks.31279 · Cited by 331
Vivar, J. M. F., & García‐Peñalvo, F. J. (2022) · Comunicar · doi:10.3916/c74-2023-03 · Cited by 312
The Relationship Between Homework and Achievement—Still Much of a Mystery
Trautwein, U., & Köller, O. (2003) · Educational Psychology Review · doi:10.1023/a:1023460414243 · Cited by 279
No child, no school, no state left behind: schooling in the age of accountability 1
Hopmann, S. (2008) · Journal of Curriculum Studies · doi:10.1080/00220270801989818 · Cited by 265
Motivation and Self-Regulated Learning
Rheinberg, F., Vollmeyer, R., & Burns, B. D. (2000) · Advances in psychology · doi:10.1016/s0166-4115(00)80007-2 · Cited by 223
Artificial Intelligence as an Effective Classroom Assistant
du Boulay, B. (2016) · IEEE Intelligent Systems · doi:10.1109/mis.2016.93 · Cited by 213 · cited 1×
“The use of artificial intelligence by students to improve their learning and performance is not new to the education sector (Du Boulay, 2016).”
BackgroundCiolacu, M. I., Tehrani, A. F., Binder, L., & Svasta, P. M. (2018) · IEEE International Symposium for Design and Technology in Electronic Packaging (SIITME) · doi:10.1109/siitme.2018.8599203 · Cited by 203
OpenAI ChatGPT-Generated Results: Similarity Index of Artificial Intelligence-Based Contents
Ventayen, R. J. M. (2023) · Advances in intelligent systems and computing · doi:10.1007/978-981-99-3608-3_15 · Cited by 135
OpenAI ChatGPT Generated Results: Similarity Index of Artificial Intelligence-Based Contents
Ventayen, R. J. M. (2023) · doi:10.2139/ssrn.4332664 · Cited by 123 · cited 3×
“…claim of work authorship by the students in the absence of any tool capable of detecting AI-assisted writing or plagiarized work (Ventayen, R., Ventayen, 2023), hence, opening doors to the discussion of the legitimacy of the existing performance evaluation models followed in the higher…”
BackgroundMethodInfluentialOECD (2002) · OECD eBooks · doi:10.1787/9789264174986-en · Cited by 99
Learners for Life: Student Approaches to Learning
OECD (2003) · Programme for international student assessment/Internationale Schulleistungsstudie · doi:10.1787/9789264103917-en · Cited by 81
Learning Outcomes as a Key Concept in Policy Documents throughout Policy Changes
Prøitz, T. S. (2014) · Scandinavian Journal of Educational Research · doi:10.1080/00313831.2014.904418 · Cited by 75
ChatGPT in Surgical Practice—a New Kid on the Block
Bhattacharya, K., Bhattacharya, A. S., Bhattacharya, N., Yagnik, V. D., Garg, P. K., & Kumar, S. (2023) · Indian Journal of Surgery · doi:10.1007/s12262-023-03727-x · Cited by 75
Using Learning Analytics for Preserving Academic Integrity
Amigud, A., Arnedo-Moreno, J., Daradoumis, T., & Guerrero-Roldan, A.-E. (2017) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v18i5.3103 · Cited by 61
The Surprising Return of Honor Codes.
Pavela, G., & McCabe, D. L. (1993) · Planning for higher education · Cited by 31
Evaluating the effectiveness of a first year module designed to improve student engagement
Willmot, P., & Perkin, G. (2011) · Engineering Education · doi:10.11120/ened.2011.06020057 · Cited by 16
Meta-evaluation of school evaluation models
Gallegos, A. M. (1994) · Studies In Educational Evaluation · doi:10.1016/s0191-491x(00)80004-8 · Cited by 9
(2021) · DOAJ (DOAJ: Directory of Open Access Journals)
Research works printed but not linked: 17
- Aasen, P. (2012). Accountability under ambiguity. Dilemmas and contradictions in education. In A.-L. Østern, K. Smith, T. Krüger, M.-B. Postholm, & T. Ryghaug (Eds.), Teacher education research between national identity and global trends (pp. 77–30). Academics.
- Altbach, P. G. (2004). The question of corruption in academe. International Higher Education, 34(March), 8–10.
- 10.2139/ssrn.4337484 · DOI · Paper page
- CAIE-Cambridge Assessment International Education. (2021). Education brief: School evaluation. Retrieved from https://www.cambridgeinternational.org/Images/637044-education-brief-school-evaluation.pdf
- 10.2139/ssrn.4405254 · DOI
- CERI. (2008). Assessment for Learning Formative Assessment. Paper presented in OECD/CERI International Conference titled Learning in the 21st Century: Research, Innovation and Policy. Retrieved from https://www.oecd.org/site/educeri21st/40600533.pdf
- Chen Y. Chen Y. & Heffernan N. (2020). Personalized math tutoring with a conversational agent. arXiv preprint arXiv:2012.12121. · arXiv
- Deepa, S., & Seth, M. (2013). Do soft skills matter? – Implications for educators based on recruiters’ perspectives. IUP Journal of Soft Skills, 7(1), 7–20.
- Gilson, A., Safranek, C., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2022). How well does ChatGPT do when taking the medical licensing exams? The implications of large language models for medical education and knowledge assessment. medRxiv, 9(Feb), e45312.
- Kim, S., Park, J., & Lee, H. (2019). Automated essay scoring using a deep learning model. Journal of Educational Technology Development and Exchange, 2(1), 1–17.
- Ludeman, R. (2005). Student leadership and moral accountability. Journal of College and Character, 2, Retrieved from. http://www.collegevalues.org/ethics.cfmin=460&d=1
- Owings, L. (2002). Cheaters never win but they keep professors on their toes. Silicon Valley/San Jose Business Journal, 8(August), 19.
- 10.1108/S2044-9968 · DOI
- 10.21203/rs.3.rs-2610655/v1 · DOI
- Telecom Review. (2023). UAE: Sheikh Mohammed Requests Study on ChatGPT. 10 February 2023. Retrieved from https://www.telecomreview.com/articles/reports-and-coverage/6773-uae-sheikh-mohammed-requests-study-on-chatgpt
- Van Dis E. Bollen J. Zuidema W. Rooij R. & Bockting C. (2023). ChatGPT: Five priorities for research Nature 3 February 2023. Retrieved from https://www.nature.com/articles/d41586-023-00288-7
- Willmot, P., & Colman, B. (2016). Interpersonal skills in engineering education, AAEE2016 CONFERENCE, Coffs Harbour, Australia.
Cited by
Sorted by citations
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023) · Sustainability · doi:10.3390/su151712983 · Cited by 784
Does ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105224 · Cited by 531
A Scoping Review on How Generative Artificial Intelligence Transforms Assessment in Higher Education
Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00468-z · Cited by 493
Abbas, M., Jam, F. A., & Khan, T. I. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00444-7 · Cited by 531
“However, the extensive use of ChatGPT brings a number of challenges for higher education (Bahroun et al., 2023; Chan, 2023; Chaudhry et al., 2023; Dalalah & Dalalah, 2023).”
BackgroundInfluentialExploring Artificial Intelligence in Academic Essay: Higher Education Student's Perspective
Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., Darwis, A., & Marzuki (2023) · International Journal of Educational Research Open · doi:10.1016/j.ijedro.2023.100296 · Cited by 418
Metadata
- Authors
- Chaudhry, I. S., Sarwary, S. A. M., El Refae, G. A., & Chabchoub, H.
- Affiliations
- Al Ain University (AE)
- Portland State University (US)
- Al Ain University
- Corresponding author
- Chaudhry, Iffat Sabir
- Venue
- Cogent Education
- Publisher
- Informa UK Limited
- Published
- 2023-05-14
- Volume
- 10
- Issue
- 1
- ISSN
- 2331-186X (ISSN-L)
- OpenAlex
- W4376564338
- Cited by
- 262
- References
- 37
- Citations by year
- 2026: 63 · 2025: 85 · 2024: 89 · 2023: 25
- FWCI
- 61.50
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Cogent Education (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- funding
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Social Sciences › Education › Academic integrity and plagiarism
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- ChatGPT, student assessment, higher education, plagiarism detection, academic integrity, Turnitin, GPTZero, undergraduate students, artificial intelligence in academia, learning outcomes
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