The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education
Open accessAbstract
Engineering education is constantly evolving to keep up with the latest technological developments and meet the changing needs of the engineering industry. One promising development in this field is the use of generative artificial intelligence technology, such as the ChatGPT conversational agent. ChatGPT has the potential to offer personalized and effective learning experiences by providing students with customized feedback and explanations, as well as creating realistic virtual simulations for hands-on learning. However, it is important to also consider the limitations of this technology. ChatGPT and other generative AI systems are only as good as their training data and may perpetuate biases or even generate and spread misinformation. Additionally, the use of generative AI in education raises ethical concerns such as the potential for unethical or dishonest use by students and the potential unemployment of humans who are made redundant by technology. While the current state of generative AI technology represented by ChatGPT is impressive but flawed, it is only a preview of what is to come. It is important for engineering educators to understand the implications of this technology and study how to adapt the engineering education ecosystem to ensure that the next generation of engineers can take advantage of the benefits offered by generative AI while minimizing any negative consequences.
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In the citing paper
“CGPA reflects academic performance and self-regulation, as high-performing students tend to engage with AI more responsibly and uphold integrity (Qadir, 2022;Vieriu & Petrea, 2025).”
From Academic Integrity and Students’ Ethical Use of ChatGPT in Higher Education (2026) · cites this paper as Qadir, 2022
In the citing paper
“AI tools and resources, such as virtual tutors, voice assistants [18], text-to-image generation (Stable Diffusion, Dall-e-2, Midjourney), text summarization (summarizer.org),AI video generation platforms (Synthesia or Elai.io),AI-enabled adaptive assessment [48], and smart content, may also supplement traditional learning techniques by providing students with additional material and interactive ex”
From New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023) · cites this paper as [34]
In the citing paper
“Despite the myriad of potential educational benefits, in its current state ChatGPT has been found to have several serious inherent limitations, such as generating wrong answers and making-up articles that do not exist.”
From Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning (2023) · cites this paper as Qadir, 2022
In the citing paper
“For example, an author asked ChatGPT to generate books and articles in a paper he is working on, ChatGPT included a make-up article which does not exist and even provided full bibliographic details of the article with a non-functional URL (Qadir, 2022).”
From Education in the Era of Generative Artificial Intelligence (AI): Understanding the Potential Benefits of ChatGPT in Promoting Teaching and Learning (2023) · cites this paper as Qadir, 2022
In the citing paper
“ChatGPT has exhibited top performance in many application domains, such as coherent content and essay generation, chatbot responses, language translation, question answering, and programming code [9,10].”
From ChatGPT for Education and Research: Opportunities, Threats, and Strategies (2023) · cites this paper as [10]
Citations
Cites
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Ahmad, K., Iqbal, W., Elhassan, A., Qadir, J., Benhaddou, D., Ayyash, M., & Al‐Fuqaha, A. (2023) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2023.3314610 · Cited by 466
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Rothstein, D., & Santana, L. (2011) · Cited by 133
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Litman, D. J. (2016) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v30i1.9879 · Cited by 129
Data-Driven Artificial Intelligence in Education: A Comprehensive ReviewPreprint
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Self-citationA Student Primer on How to Thrive in Engineering Education during and beyond COVID-19
Qadir, J., & Al‐Fuqaha, A. (2020) · Education Sciences · doi:10.3390/educsci10090236 · Cited by 83
Self-citationToward accountable human-centered AI: rationale and promising directions
Qadir, J., Islam, M., & Al-Fuqaha, A. I. (2022) · Journal of Information, Communication and Ethics in Society · doi:10.1108/jices-06-2021-0059 · Cited by 47
Self-citationCaveat Emptor: The Risks of Using Big Data for Human Development
Latif, S., Qayyum, A., Usama, M., Qadir, J., Zwitter, A., & Shahzad, M. (2019) · IEEE Technology and Society Magazine · doi:10.1109/mts.2019.2930273 · Cited by 36
Self-citationWhat Every Student Should Know: Seven Learning Impediments and Their Remedies
Qadir, J. (2015) · IEEE Potentials · doi:10.1109/mpot.2014.2368793 · Cited by 19
Self-citationLearning 101: The Untaught Basics
Qadir, J., & Imran, M. A. (2017) · IEEE Potentials · doi:10.1109/mpot.2017.2749408 · Cited by 17
Self-citationThe Triple Imperatives of Online Teaching: Equity, Inclusion, and EffectivenessPreprint
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Kent, M., & Bennett, R. (2017) · Routledge eBooks · doi:10.4324/9781315594248-1 · Cited by 11
Learning 101: The Untaught BasicsPreprint
Qadir, J., & Imran, M. A. (2017) · SSRN Electronic Journal · doi:10.2139/ssrn.2916505 · Cited by 6
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Sorted by citations
Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., et al. (2023) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2023.102642 · Cited by 4,584
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Metadata
- Authors
- Qadir, J.
- Affiliations
- Qatar University (QA)
- Corresponding author
- Qadir, Junaid
- ORCID
- Qadir, Junaid
- Published
- 2022-12-30
- OpenAlex
- W4313313935
- Cited by
- 264
- References
- 20
- Citations by year
- 2026: 18 · 2025: 24 · 2024: 103 · 2023: 119
- Type
- posted content
- Language
- en
- Open access
- green
- doi.org
- Locations
- Figshare (submittedVersion, cc-by)
- Funders
- Qatar University
- 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 › Artificial Intelligence Applications
- Keywords
- generative AI, ChatGPT, engineering education, artificial intelligence in education, personalized learning, virtual simulation, training data bias, misinformation, academic dishonesty, AI ethics, automation and unemployment
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