The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index; none of the 24 sources its claims cite is checked for support yet.
What ChatGPT means for universities: Perceptions of scholars and students
Open accessAbstract
This study investigates the implications of ChatGPT, an AI-powered language model, for students and universities by examining the perceptions of scholars and students. The responses of seven scholars and 14 PhD students from four countries – Turkey, Sweden, Canada and Australia – are analysed using a thematic content analysis approach. Nine key themes emerge from the findings. According to their frequency of recurrence, these themes are: “Evolution of learning and education systems”, “changing role of educators”, “impact on assessment and evaluation”, “ethical and social considerations”, “future of work and employability”, “personalized learning”, “digital literacy and AI integration”, “AI as an extension of the human brain”, and “importance of human characteristics”. The potential benefits of AI in education as well as the challenges and barriers that may arise from its integration are discussed in the context of existing literature. Based on these findings, suggestions for future research include further exploration of the ethical implications of AI for education, the development of strategies to manage privacy concerns, and the investigation of how educational institutions can best prepare for the integration of AI technologies. The paper concludes by emphasizing the importance of understanding the potential opportunities and challenges associated with AI in higher education and the need for continued research in this area.
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
This study uses thematic content analysis of responses from seven scholars and 14 PhD students to examine perceptions of ChatGPT’s implications for students and universities. Nine themes emerged, with the most frequent being “evolution of learning and education systems,” “changing role of educators,” and “impact on assessment and evaluation.”
Key findings
- Nine key themes emerged from 24 comments by 21 participants: “Evolution of learning and education systems,” “changing role of educators,” “impact on assessment and evaluation,” “ethical and social considerations,” “future of work and employability,” “personalized learning,” “digital literacy and AI integration,” “AI as an extension of the human brain,” and “importance of human characteristics.”
- The most repeated themes were “evolution of learning and education systems” with 16 frequencies, “changing role of educators” with 13 frequencies, and “impact on assessment and evaluation” with 11 frequencies.
- Participants generally agreed that AI will significantly impact traditional learning methods, shift focus toward skills and competencies, and redefine the roles of educational institutions, while also recognizing challenges and expressing optimism for AI in education.
- The findings are discussed as consistent with existing literature on benefits and challenges, including personalized learning, changing educator roles, assessment concerns, digital literacy, ethics, and responsible implementation.
Methods
- Qualitative study using thematic content analysis of responses to an open-ended question about the potential impact of ChatGPT on students and universities.
- Data were collected from seven scholars via ResearchGate and 14 PhD students via Google Form, totaling 21 participants from Turkey, Sweden, Canada, and Australia; all PhD students were from Turkey, and most participants were from education-related fields.
- The resulting data set contained 24 comments from 21 participants; analysis followed a six-step thematic content analysis approach.
Limitations
- The paper states that the research is limited by a sample size of 21 scholars and PhD students and by using a single open-ended question for data collection.
- The paper states that it assumed participants understood the English question correctly because PhD programmes require adequate English, and it calls for including participants from more diverse backgrounds, countries, and academic fields.
- Evident from the text: all PhD students were from Turkey and the majority of participants were from education-related fields, which limits the breadth of perspectives; the paper also notes future research could benefit from additional qualitative and quantitative methods, including longitudinal and experimental designs.
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Claims the paper makes
17 Not checked yet · 8 Own interpretation · 5 Own result · 3 No basis given · 2 Own method
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
“These three themes show that scholars and students think that AI technologies will change our habits regarding the implementation and evaluation of education by looking at the capabilities of ChatGPT, one of the leading AI applications.”
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
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In the paper
“However, integrating AI in education also raises concerns about assessment and evaluation, as traditional methods may become obsolete in the face of AIgenerated answers (Rudolph et al., 2023).”
What the sources say
- Not checked yetcites Rudolph et al., 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“The changing role of educators, as discussed by Fırat (2023), Bozkurt (2023), and Sengupta and Chakraborty (2020), supports the idea that AI tools can increase student engagement and satisfaction by relieving university staff of routine tasks and allowing them to focus on higher-order skills and mentoring.”
What the sources say
- Not checked yetcites Fırat (2023)
- Not checked yetcites Bozkurt (2023)
- Not checked yetcites Sengupta and Chakraborty (2020)
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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- Probably not a substantial claim. 28
- The quote only partly states this claim. 1
- It may state two separate claims as one. 18
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
“As can be seen in Figure 1, the most repeated themes were”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
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
“According to their frequency of recurrence, these themes are:”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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
“Nine key themes emerge from the findings.”
- Also stated in: § Findings · plain
“Nine themes emerged from the analysis of the comments on the question”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The quote only partly states this claim.
- Also stated in: § Findings · plain
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
“Participants also recognize the challenges and potential issues that may arise in the process, but they express optimism for the future of AI in education.”
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
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 comments of scholars and PhD students reflect the diverse opinions and concerns of the participants regarding integrating Chat GPT and AI into education.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“The COPE (Committee on Publication Ethics) guidelines have been followed in this research.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“The study found that students had a positive attitude towards the chatbot and perceived it as a useful tool for language learning.”
What the sources say
- Not checked yetcites Xiong et al. (2021)
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The introduction of AI technologies in education has the potential to revolutionize traditional educational practices, promote personalized learning experiences, and foster the development of soft skills (Fırat, 2023).”
What the sources say
- Not checked yetcites Fırat, 2023
hedgedconditional- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“The study also highlighted that chatbots could reduce the workload of university staff by answering frequently asked questions.”
What the sources say
- Not checked yetcites Sengupta and Chakraborty (2020)
hedgeddirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, as of early April 2023, there is an insufficient number of studies addressing the perspectives of scholars and students on the rapid use of ChatGPT.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Sullivan et al. (2023) found that ChatGPT has raised both academic integrity concerns and the potential for enhanced learning in higher education.”
What the sources say
- Not checked yetcites Sullivan et al. (2023)
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, it is not yet possible to assert a consensus among educators, specifically concerning ChatGPT.”
hedged- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
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
“Using the thematic content analysis method, the study was able to extract valuable insights and opinions from the collected responses, providing a deeper understanding of the potential implications of Chat GPT and AI integration in the context of students and universities.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“Recent advancements in AI, such as GPT-3.5 and GPT-4, have further implications for education as these models become increasingly capable of understanding and generating human-like text (Adiguzel et al., 2023).”
What the sources say
- Not checked yetcites Adiguzel et al., 2023
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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
“For students and universities, this research highlights the transformative potential of AI technologies such as ChatGPT.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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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
“However, this shift brings about challenges in assessment, digital literacy, and ethical considerations.”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The main differences between GPT-3.5 and GPT-4 are the parameter size of the models (GPT-3.5 has 175 billion parameters while GPT-4 has much more context length, the ability to use images as input in addition to text, and the use of Rule-Based Reward Models in its training (Koubaa, 2023;OpenAI, 2023).”
What the sources say
- Not checked yetcites Koubaa, 2023
- Not checked yetcites OpenAI, 2023
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“GPT-3, an auto-regressive language model, was found to perform strongly on many NLP datasets, such as answering questions and completing missing words in the training process (Brown et al. 2020).”
What the sources say
- Not checked yetcites Brown et al. 2020
boosted- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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
“This development supports the theme of”
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
In the paper
“They found that the advantages of ChatGPT include personalized learning, the encouragement of interactive learning, and the potential for formative assessment that supports teaching and learning and provides continuous feedback.”
What the sources say
- Not checked yetcites Baidoo-Anu and Owusu Ansah, (2023)
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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
“Overall, the consensus is that AI will significantly impact traditional learning methods, shifting the focus on skills and competencies and redefining the roles of educational institutions.”
plaindirect- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“Their content analysis of 100 news articles revealed mixed responses, with an emphasis on academic integrity and innovative assessment design.”
What the sources say
- Not checked yetcites Sullivan et al. (2023)
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
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
“The findings from the thematic content analysis are consistent with the existing literature, highlighting the potential benefits and challenges of integrating AI, such as ChatGPT, into education.”
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The themes related to digital literacy, ethical and social considerations, and the importance of human-specific features are also evident and strongly emphasized in the related literature.”
What the sources say
- Not checked yetcites Willems (2023)
- Not checked yetcites Halaweh (2023)
- Not checked yetcites Crawford et al. (2023)
boosted- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
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 conclusion, integrating AI in education offers numerous opportunities to enhance learning experiences, personalize instruction, and transform the role of educators.”
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
In the paper
“However, the study also noted that the potential benefits for disadvantaged students and students' perspectives remain underrepresented in media discussions.”
What the sources say
- Not checked yetcites Sullivan et al. (2023)
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“In a similar vein, Alotaibi et al. (2020) found that chatbots can improve student performance and knowledge retention, which supports the theme of personalized learning found in the analysis of this study.”
What the sources say
- Not checked yetcites Alotaibi et al. (2020)
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Research has demonstrated that chatbot technologies can enhance student interaction and learning processes (D'Mello et al., 2014), enrich learning experiences by impacting student success in higher education (Winkler & Söllner, 2018), and potentially improve student motivation, engagement, and learning outcomes (Deng & Yu, 2023).”
What the sources say
- Not checked yetcites D'Mello et al., 2014
- Not checked yetcites Winkler & Söllner, 2018
- Not checked yetcites Deng & Yu, 2023
boostedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“However, the integration of AI in education also raises critical questions about the potential challenges and obstacles that may emerge as a result of this technological shift.”
hedgedconditional- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“However, ChatGPT has been found to have issues of misinformation generation, bias in data training and privacy issues.”
What the sources say
- Not checked yetcites Baidoo-Anu and Owusu Ansah, (2023)
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“GPT-4 is more reliable, more creative, and can handle much more nuanced instructions than GPT-3.5 (OpenAI, 2023).”
What the sources say
- Not checked yetcites OpenAI, 2023
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“This research is limited with a sample size of 21 scholars and PhD students and an open-ended question for data collection.”
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
The authors state this as an assumption.
PhD students and scholars understood the question asked in English correctly.
“Since PhD programmes require an adequate level of English, it was assumed that students and scholars understood the question asked in English correctly.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Applying AI technologies can facilitate analyzing students' learning procedures, performance, and needs, providing instructors with timely feedback, and assisting them in delivering adaptive instruction.”
From A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment (2025) · cites this paper as Firat, 2023
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Ethical concerns in instruction include incorrect or fabricated information, accessibility, and algorithm biases (Firat, 2023).”
From A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment (2025) · cites this paper as Firat, 2023
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Firat (2023) also mentioned overreliance on AI, data privacy, and unequal access to AI tools as challenges.”
From A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment (2025) · cites this paper as Firat (2023)
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Firat (2023) indicated that implementing AI may require educators to change their role from being instructors to guides or facilitators.”
From A systematic review of the early impact of artificial intelligence on higher education curriculum, instruction, and assessment (2025) · cites this paper as Firat (2023)
In the citing paper
“ChatGPT has the potential to offer personalized learning experiences and support an effective learning process by providing students with customized feedback and explanations tailored to their needs and abilities”
From A systematic literature review of empirical research on ChatGPT in education (2024) · cites this paper as [27]
In the citing paper
“Previous studies indicate that students are optimistic about the potential of ChatGPT to be used in universities [22,23].”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [22]
In the citing paper
“They believe that ChatGPT can be used to help them with their studies, such as providing personalized feedback and answering questions.”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [22]
In the citing paper
“Students are concerned about the potential for ChatGPT to be used for academic dishonesty and they are aware of the limitations of ChatGPT and the need for careful consideration before it is widely adopted.”
From ChatGPT for Academic Purposes: Survey Among Undergraduate Healthcare Students in Malaysia (2024) · cites this paper as [22]
Self-check
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.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Literature review
“Okuyama and Suzuki (2023) proposed a new training methodology for GPT-4 that leverages large-scale semantic discrimination tasks to improve the model's ability to understand the meaning of a text.”
§ References
“18. Okuyama, K., & Suzuki, K. (2023). Correlators of double scaled SYK at one-loop. arXiv preprint. arXiv:2303.07552.”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Introduction
“(Haque et al., 2023;Sardana et al., 2023)”
§ References
“12. Haque, M. U., Dharmadasa, I., Sworna, Z. T., Rajapakse, R. N., & Ahmad, H. (2022).”
Citations
Cites
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×
“GPT-3, an auto-regressive language model, was found to perform strongly on many NLP datasets, such as answering questions and completing missing words in the training process (Brown et al. 2020).”
BackgroundChatGPT 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 1×
“For example, Kasneci et al. (2023) examined the potential benefits and risks of ChatGPT for education, while Willems (2023) discussed the wider ethical implications of using such models in universities.”
BackgroundBAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 3,939
Sallam, M. (2023) · Healthcare · doi:10.3390/healthcare11060887 · Cited by 3,126 · cited 2×
“While some consider that this AI’s pioneering application will create a paradigm shift in various fields, including education (Bozkurt, 2023; Sallam, 2023), others emphasize the possible ethical challenges of ChatGPT and consider it a disruptive technology (Haque et al., 2023; Sardana et al., 2023).”
BackgroundBaidoo-Anu, D., & Owusu Ansah, L. (2023) · doi:10.2139/ssrn.4337484 · Cited by 3,004
ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.9 · Cited by 1,806 · cited 2×
“Prior to the advent of ChatGPT, a study by Sengupta and Chakraborty (2020) investigated the use of chatbots in higher education and found that they can be an effective tool for improving student engagement and satisfaction.”
BackgroundMethodChatGPT is fun, but not an author
Thorp, H. H. (2023) · Science · doi:10.1126/science.adg7879 · Cited by 1,437 · cited 4×
“In a study that criticizes the use of ChatGPT in education, Thorp (2023) emphasized that this application may be fun but has serious consequences in the world of science and academia.”
BackgroundInfluentialRevolutionizing education with AI: Exploring the transformative potential of ChatGPT
Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023) · Contemporary Educational Technology · doi:10.30935/cedtech/13152 · Cited by 975 · cited 1×
“5 and GPT-4, have further implications for education as these models become increasingly capable of understanding and generating human-like text (Adiguzel et al., 2023).”
BackgroundChatGPT in higher education: considerations for academic integrity and student learning
(2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.1.17 · Cited by 853 · cited 2×
“Willems (2023) discussed the ethical implications of using large language models like ChatGPT in universities, while Halaweh (2023) and Crawford et al.”
Background
Research works printed but not linked: 3
- Biswas, S. (2023, February). Role of ChatGPT in education. https://ssrn.com/abstract=4369981
- Smith, K., Jones, L., & Davis, B. (2023). GPT-4 and beyond: Exploring the limits of language AI. Frontiers in Artificial Intelligence, 6, 12345. https://doi.org/10.3389/ frai.2023.12345 · DOI
- Mehmet Firat. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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Items 101–200 of 430
ChatGPT Goes to College: Exploring Student Perspectives on Artificial Intelligence in the Classroom
Cavazos, J. T., Hauck, K. A., Baskin, H. M., & Bain, C. M. (2024) · Teaching of Psychology · doi:10.1177/00986283241268829 · Cited by 42
“Firat (2023) explored the initial perspectives of both students and scholars on ChatGPT and found a general consensus that its mere presence is impactful enough to restructure traditional roles in educational systems.”
Systematic analysis of generative AI tools integration in academic research and peer review
Salman, H., Ahmad, M. A., Ibrahim, R. B., & Mahmood, J. (2025) · Online Journal of Communication and Media Technologies · doi:10.30935/ojcmt/15832 · Cited by 39
Shahzad, M. F., Xu, S., An, X., & Asif, M. (2025) · SAGE Open · doi:10.1177/21582440251368594 · Cited by 45
Emerging Dynamics of ChatGPT in Academia: A Scoping Review
Mahrishi, M., Abbas, A., Radovanović, D., & Hosseini, S. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/b182ws13 · Cited by 28
“Firat (2023) studied the influence of ChatGPT on students and universities from Turkey, Sweden, Canada, and Australia, revealing nine key themes, including learning system evolution, educator roles, assessment (Ratten & Jones, 2023), ethical considerations, personalised learning, digital literacy…”
BackgroundChang, Y., Silalahi, A. D. K., & Lee, K.-Y. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2381930 · Cited by 24
“The integration of AI-powered ChatGPT has the potential to transform educational practices (Firat, 2023).”
Guo, X. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2024.2445177 · Cited by 23
“…reactions among GFL learners in response to ChatGPT-provided WCF. Initially, students exhibited positive feelings such as curiosity and engagement, aligning with the findings of (Tlili et al., 2023) and (Firat, 2023), who noted initial enthusiasm for technological tools in educational contexts.”
Muringa, T. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1628019 · Cited by 24
What if GPT4 Became Autonomous: The Auto-GPT Project and Use Cases
Fırat, M., & Kuleli, S. (2023) · Journal of Emerging Computer Technologies · doi:10.57020/ject.1297961 · Cited by 29
Self-citationUniversity Teachers’ Perceptions of Using ChatGPT in Language Teaching and Assessment
Nguyễn, T. C. (2024) · Proceedings of the AsiaCALL International Conference · doi:10.54855/paic.2349 · Cited by 40
Prospects for ChatGPT Application in Higher Education: A Scoping Review of International Research
Raitskaya, L., & Lambovska, M. (2024) · Integration of Education · doi:10.15507/1991-9468.114.028.202401.010-021 · Cited by 34
Ouaazki, A., Bergram, K., Farah, J. C., Gillet, D., & Holzer, A. (2024) · International Conference on Conversational User Interfaces · doi:10.1145/3640794.3665542 · Cited by 28
Kangwa, D., Msafiri, M. M., & Fute, A. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70109 · Cited by 22
ChatGPT between opportunities and challenges: an empirical study in Italy
Pasca, M. G., & Arcese, G. (2024) · The TQM Journal · doi:10.1108/tqm-08-2023-0268 · Cited by 25
Alghazo, R., Fatima, G., Malik, M., Abdelhamid, S. E., Jahanzaib, M., Nayab, D. E., & Raza, A. (2025) · Education Sciences · doi:10.3390/educsci15020158 · Cited by 22
Critical minds: enhancing education with ChatGPT
Costa, A. R., Lima, N., Viegas, C., & Caldeira, A. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2415286 · Cited by 28
Koroleva, D. O., & Jogezai, N. A. (2024) · Information and Learning Sciences · doi:10.1108/ils-10-2023-0137 · Cited by 27
Research agenda: Synergizing in-class and out-of-class language learning with technology
Lai, C., & Sundqvist, P. (2025) · Language Teaching · doi:10.1017/s026144482500014x · Cited by 21
“…are multifaceted, including offering tailored and interactive support, providing immediate feedback and guidance, proffering learning materials, helping students locate and utilize open educational materials, and supporting monitoring and reflection on individual learning progress (Firat, 2023).”
Marengo, A., Pagano, A., Lund, B. D., & Santamato, V. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2025.1587040 · Cited by 32
A Testing Framework for AI Linguistic Systems (testFAILS)
Kumar, Y., Morreale, P. A., Sorial, P., Delgado, J., Li, J. J., & Martins, P. (2023) · Electronics · doi:10.3390/electronics12143095 · Cited by 19
Isiaku, L., Kwala, A. F., Sambo, K. U., & Isiaku, H. H. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/7egat807 · Cited by 21
“A growing body of research has examined the perception of university and on the use of ChatGPT in academia (Firat, 2023; Singh et al., 2023).”
BackgroundPrivacy fatigue and its effects on ChatGPT acceptance among undergraduate students: is privacy dead?
Chung, J., & Kwon, H.-Y. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13198-6 · Cited by 23
“…(Balu & Sriram, 2023), there has been a continuous stream of research on user technology acceptance and perceptions of ChatGPT (Choudhury & Shamszare, 2023; Duong et al., 2024; Firat, 2023; Foroughi et al., 2023; Menon & Shilpa, 2023; Sallam et al., 2023; Strzelecki, 2023; Tiwari et al., 2024).”
ChatGPT in Brazilian K-12 science education
Monteiro, F. F., Souza, P. V. S., da Silva, M. C., Maia, J. R., da Silva, W. F., & Girardi, D. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1321547 · Cited by 31
Effectiveness of ChatGPT in Essay Autograding
Altamimi, A. B. (2023) · International Conference on Computing, Electronics & Communications Engineering (iCCECE) · doi:10.1109/iccece59400.2023.10238541 · Cited by 23
“Assignments and exams autograding is one of the features that can benefit from ChatGPT as reported in [19],[20].”
BackgroundA Glimpse of chatGPT: An Introduction of Features, Challenges, and Threads in Higher Education
Arista, A., Shuib, L. M., & Ismail, M. A. (2023) · International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS) · doi:10.1109/icimcis60089.2023.10349057 · Cited by 20
“Nonetheless, the incorporation of artificial intelligence (AI) in education also prompts important inquiries regarding the possible difficulties and roadblocks that could arise from this technological revolution [27].”
BackgroundChatikobo, M. V., & Pasipamire, N. (2024) · Cogent Education · doi:10.1080/2331186x.2024.2425209 · Cited by 30
“Examples of AI solutions enhancing LMSs like Canvas and Moodle include Smart Sparrow and Learnosity (Firat, 2023).”
ChatGPT as a Digital Tool in the Transformation of Digital Teaching Competence: A Systematic Review
Cerero, J. F., Rueda, M. M., Graván, P. R., & Fernández‐Batanero, J. M. (2025) · Technologies · doi:10.3390/technologies13050205 · Cited by 25
“Integration must be balanced with direct instruction to ensure that critical skills such as analytical thinking and problem solving are maintained and reinforced [41].”
InfluentialSuchánek, P., & Kŕaĺová, M. (2025) · Journal of Innovation & Knowledge · doi:10.1016/j.jik.2025.100781 · Cited by 23
Naher, J., Maruf, M. H., Bakht, S. T., & Sadaf, S. S. (2023) · Technium Romanian Journal of Applied Sciences and Technology · doi:10.47577/technium.v15i.9660 · Cited by 24
“Furthermore, Firat [6] conducted a thematic analysis based on the comments of 14 scholars, focusing on their perceptions of ChatGPT's usage in universities.”
BackgroundMethodChatGPT: Where Is a Silver Lining? Exploring the realm of GPT and large language models
Тихонова, Е. В., & Raitskaya, L. (2023) · Journal of language and Education · doi:10.17323/jle.2023.18119 · Cited by 22
“ChatGPT reached one million users only within five days as compared with 300 days for Facebook, 75 days for Instagram to reach the same audi - ence (Firat, 2023, p. 58).”
BackgroundMethodInfluentialAwal, M. R., & Asaduzzaman (2024) · Higher Education Skills and Work-based Learning · doi:10.1108/heswbl-09-2023-0249 · Cited by 19
Threading the GenAI needle: Unpacking the ups and downs of GenAI for higher education stakeholders
Neupane, A., Shahi, T. B., Cowling, M., & Tanna, D. (2024) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2024.7.2.4 · Cited by 17
Xiao, Q.-M. (2024) · ICIEI · doi:10.1145/3664934.3664946 · Cited by 22
“ChatGPT relies on extensive language models to produce text that closely resembles human language [7].”
Kangwa, D., Msafiri, M. M., & Fute, A. (2025) · AI and Ethics · doi:10.1007/s43681-025-00689-6 · Cited by 17
“Educators should use GenAI tools to underscore the importance of personalised learning and perceived fairness in enhancing ethical awareness, leading to a high intention to use these tools [24, 40].”
The changing nature of teaching future IS professionals in the era of generative AI
Kajtazi, M., Holmberg, N., & Sarker, S. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2267330 · Cited by 17
ChatGPT Evaluation: Can It Replace Grammarly and Quillbot Tools?
A. younis, H., Mohammed, O., Muthmainnah, Sahib, T. M., Akhtom, D., Hayder, I. M., Salisu, S., & Shahid, M. (2023) · British Journal of Applied Linguistics · doi:10.32996/bjal.2023.3.2.4 · Cited by 17
A Systematic Rapid Review of Empirical Research on Students’ Use of ChatGPT in Higher Education
Dikilitaş, K., Klippen, M. I. F., & Keleş, S. (2024) · Nordic Journal of Systematic Reviews in Education · doi:10.23865/njsre.v2.6227 · Cited by 25
“In line with the findings reported above, Firat (2023) highlights the role of digital literacy in “learning how to interact effectively and critically evaluate AI-generated content,” adding that “AI will significantly impact traditional learning methods, shifting the focus on skills and…”
BackgroundMethodResultInfluentialEduVQA: A multimodal Visual Question Answering framework for smart education
Xiao, J., & Zhang, Z. (2025) · Alexandria Engineering Journal · doi:10.1016/j.aej.2025.03.005 · Cited by 18
Exploring the AI–Human Interface for Personalized Learning in a Chemical Context
Clark, T. M., & Tafini, N. (2024) · Journal of Chemical Education · doi:10.1021/acs.jchemed.4c00967 · Cited by 16
Liu, Q., Hu, A., Gladman, T., & Gallagher, S. (2025) · Innovative Higher Education · doi:10.1007/s10755-025-09790-4 · Cited by 26
“Studies reported that both students and staff agreed that ChatGPT and other generative AI would have an influence on the future of work, and university teaching, learning and assessment (Firat, 2023).”
InfluentialAssessing ChatGPT adoption in Jordanian medical education: a UTAUT model approach
Alqaisi, N., Alshwayyat, S., Aburumman, S., Qassim, N., Almasri, N., Algroosh, F., Alkhatib, M., Hanifa, H., & AlRyalat, S. A. (2025) · BMC Medical Education · doi:10.1186/s12909-025-07336-y · Cited by 18
Assessing the Transformative Influence of ChatGPT on Research Practices among Scholars in Pakistan
Ullah, A., Baber, M. U., & Arshad, N. (2024) · Mesopotamian Journal of Big Data · doi:10.58496/mjbd/2024/001 · Cited by 18
Loos, E. F., & Radicke, J. (2024) · AI and Ethics · doi:10.1007/s43681-024-00470-1 · Cited by 18
“It is worth noting that the above studies by [11, 12, 26] and [5] on the public perception of ChatGPT’s role as a writing assistant in education clearly show that risks are mentioned, but that they are not framed as moral hazards.”
Unveiling the Impact of Large Language Models on Student Learning: A Comprehensive Case Study
Zdravkova, K., Dalipi, F., Ahlgren, F., Ilijoski, B., & Olsson, T. (2024) · IEEE Global Engineering Education Conference (EDUCON) · doi:10.1109/educon60312.2024.10578855 · Cited by 16
“They were enthusiastically accepted not only by students, but also by their professors, stressing that they will cause significant changes in education [5, 6].”
BackgroundVietnamese University Students’ Perceptions of ChatGPT for Homework Assistance
Le, M. T. T., & Tran, K. V. (2024) · International Journal of Interactive Mobile Technologies (iJIM) · doi:10.3991/ijim.v18i15.48819 · Cited by 18
Anik, M. H., Raaz, S. N. C., & Khan, N. (2024) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-024-00438-6 · Cited by 27
Arum, R., Leon, M. D. C., Li, X., & Lopes, J. (2025) · AERA Open · doi:10.1177/23328584251331956 · Cited by 24
Divekar, R. R., Gonzalez, L., Guerra, S., Boos, N., & Divekar, R. (2025) · TechTrends · doi:10.1007/s11528-025-01095-9 · Cited by 22
“In Ngo (2023)’s study, students were aware of this issue; however, we show a possible deviation from the finding, implying that awareness of such issues might not be widespread.”
Riding the Generative AI Tsunami: Addressing the Teaching and Learning Crisis in Higher Education
Tan, S., Rudolph, J., & Tan, S. (2024) · Springer eBooks · doi:10.1007/978-3-031-54509-2_8 · Cited by 20
Exploring the potentials of ChatGPT for instructional assessment: Lecturers' attitude and perception
Opesemowo, O. A. G., Abanikannda, M. O., & Iwintolu, R. O. (2024) · Interdisciplinary Journal of Education Research · doi:10.38140/ijer-2024.vol6.21 · Cited by 14
“The increasing prevalence of AI tools, such as ChatGPT, has triggered the need to reconsider traditional assessment methodologies, as these tools may render traditional examinations and assignments obsolete, owing to their capacity to readily generate AI-generated answers (Firat, 2023).”
BackgroundOnunka, T., Raji, A., Obiki-Osafiele, A. N., Daraojimba, C., Egbokhaebho, B. A., & Okoye, C. C. (2023) · Economic Growth and Environment Sustainability · doi:10.26480/egnes.02.2023.66.78 · Cited by 18
ChatGPT and computational-based research: benefits, drawbacks, and machine learning applications
Atkinson, C. F. (2023) · Discover Artificial Intelligence · doi:10.1007/s44163-023-00091-3 · Cited by 18
“Following release in November 2022, it reached one million followers in five days, illustrating the application potential of GenAIs [32].”
BackgroundAssessing law students in a GenAI world to create knowledgeable future lawyers
Head, A., & Willis, S. (2024) · International Journal of the Legal Profession · doi:10.1080/09695958.2024.2379785 · Cited by 24
“Student views on using GenAI in higher education have received some attention (Chan 2023; Chan and Hu 2023; Farhi et al. 2023; Firat 2023; Huallpa et al. 2023; Shoufan 2023; Smolansky et al. 2023).”
Hussein, R., Zhang, Z., Amarante, P., Hancock, N., Orduña, P., & Rodríguez-Gil, L. (2024) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10892918 · Cited by 13
“Research indicates that such tools can enhance the coding experience by assisting users in debugging and auto-completing code segments without compromising their ability to code independently [16], [17].”
Zhang, X., Hu, J., & Zhou, Y. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13535-3 · Cited by 16
“In academia, decisions about adopting new technologies are not made in isolation; they are often influenced by peers, colleagues, and the broader academic community (Firat, 2023).”
AI-assisted academic cheating: a conceptual model based on postgraduate student voices
Hanh, N. V., & Duyen, N. T. (2025) · Frontiers in Computer Science · doi:10.3389/fcomp.2025.1682190 · Cited by 12
ChatGPT in Higher Education: Design Teaching Model Involving ChatGPT
An, Y., Ouyang, W., & Fu, Z. (2023) · Lecture Notes in Education Psychology and Public Media · doi:10.54254/2753-7048/24/20230560 · Cited by 12
Assessing the Impact of ChatGPT in a PHP Programming Course
Hajj, J. A., & Şah, M. (2023) · International Symposium on Innovative Approaches in Smart Technologies (ISAS) · doi:10.1109/isas60782.2023.10391549 · Cited by 16
“The study of Firat(2023)[23] examined the effects of ChatGPT on learners as well as institutions by surveying researchers and learners.”
BackgroundChatGPT in public policy teaching and assessment: An examination of opportunities and challenges
Casey, D. (2024) · Australian Journal of Public Administration · doi:10.1111/1467-8500.12647 · Cited by 12
MARKETING STUDENTS’ PERCEPTIONS TOWARDS ChatGPT: AN AI-ASSISTED THEMATIC ANALYSIS
Hazari, S. (2025) · Marketing Education Review · doi:10.1080/10528008.2025.2470198 · Cited by 17
“ChatGPT can significantly enhance the learning experience by providing instant access to information and clarification on complex topics (Baidoo-Anu & Ansah, 2023; Firat, 2023).”
Misra, V. P., Mishra, P. K., & Sharma, A. (2023) · IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE) · doi:10.1109/csde59766.2023.10487664 · Cited by 11
“As per the trend topics, 2022-23 has been an interesting year where on the one hand, there is excitement about ChatGPT [26][27] and generative artificial intelligence [28][29], but there is also concern about ethics [30][31].”
The potential of ChatGPT technology in education: advantages, obstacles and future growth
Al-Ghonmein, A. M., & Al-Moghrabi, K. G. (2024) · IAES International Journal of Artificial Intelligence · doi:10.11591/ijai.v13.i2.pp1206-1213 · Cited by 11
“[23] Higher education 10 Investigates the impacts of ChatGPT for educational institutions and students by analysing the perspectives of scholars and students.”
BackgroundMandai, K., Tan, M. J. H., Padhi, S., & Pang, K. T. (2024) · Education Sciences · doi:10.3390/educsci14060614 · Cited by 11
“5 (where the former having 175 billion and the latter having 6.7 billion parameters) [2].”
BackgroundInfluentialSingh, R. G., & Ngai, C. S. B. (2024) · Discover Education · doi:10.1007/s44217-024-00211-w · Cited by 11
“…resonate with discussions in prior studies [5, 10], previous studies on ChatGPT followed opinion-based discussions, involved a qualitative study or conducted a literature review e.g. [4, 22, 23] without offering a rigorous research design to identify the key themes embedded in ChatGPT discourse.”
Hussain, F., & Anwar, M. A. (2024) · Journal of Asian Public Policy · doi:10.1080/17516234.2024.2422917 · Cited by 12
Karafil, B., & Uyar, A. (2025) · Education and Information Technologies · doi:10.1007/s10639-024-13291-w · Cited by 14
“Consequently, students’ learning outcomes may suffer if they rely solely on ChatGPT for their written work and neglect reflection and critical thinking (Fırat, 2023).”
Abdelnabi, A. A. B., Soykan, B., Bhatti, D., & Rabadi, G. (2025) · ACM Transactions on Computing for Healthcare · doi:10.1145/3712298 · Cited by 12
“Through an examination of academics’ and students’ perspectives, Firat [1] explored the consequences of ChatGPT for students and institutions.”
Andersen-Kiel, N., & Linos, P. K. (2024) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie61694.2024.10892934 · Cited by 12
Apriani, E., Daulay, S. H., Aprilia, F., Marzuki, A. G., Warsah, I., Supardan, D., & Muthmainnah, M. (2025) · Journal of language and Education · doi:10.17323/jle.2025.17913 · Cited by 41
“These capabilities hold the promise of revolutionizing traditional pedagogical approaches and enriching personalized learning journeys (Firat, 2023).”
Rudolph, J., Tan, S., & Aspland, T. (2023) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2023.6.2.1 · Cited by 13
Syahrin, S., & Akmal, N. (2024) · Arab World English Journal · doi:10.24093/awej/chatgpt.4 · Cited by 10
“The models were no longer passive content generators but could interact, engage, and persuade, bridging the gap between static content and interactive media (Firat, 2023).”
BackgroundCutillas, A. L. (2025) · Environment and Social Psychology · doi:10.59429/esp.v10i4.3185 · Cited by 12
Al-Kamzari, F., & Alias, N. (2025) · Interactive Learning Environments · doi:10.1080/10494820.2025.2508323 · Cited by 14
“This surge in user adoption has had a profound impact on personalized learning and student engagement (Firat, 2023).”
InfluentialMadsen, D. Ø., & Toston, D. M. (2025) · Digital · doi:10.3390/digital5030024 · Cited by 16
“Uni-versities are grappling with course redesigns and integrity policies [53–57].”
Digital Learning Management using OpenAI ChatGPT: A Systematic Literature Review
Faruq, M. S. S. A., Sunoko, A., Ibda, H., & Wahyudi, K. (2023) · International Journal of Learning Teaching and Educational Research · doi:10.26803/ijlter.22.12.2 · Cited by 16
Torres-Gómez, A. (2024) · Investigación Bibliotecológica Archivonomía Bibliotecología e Información · doi:10.22201/iibi.24488321xe.2024.98.58852 · Cited by 21
Benefits, Challenges, and Attitudes Toward ChatGPT in English Writing Courses at Saudi Universities
Alqahtani, N. S. (2024) · International Journal of Language and Literary Studies · doi:10.36892/ijlls.v6i2.1739 · Cited by 18
“This finding of neutrality and slight positivity towards the tool is not in line with previous research like Firat (2023), which reported that students and teachers expressed positive attitudes towards ChatGPT implementation.”
BackgroundResultOhm, M., Bungartz, C., Boes, F., & Meier, M. (2024) · International Conference on Availability, Reliability and Security (ARES) · doi:10.1145/3664476.3670446 · Cited by 9
“According to a survey conducted by Firat [5], PhD students and scholars have concerns about the ethics and privacy of ChatGPT.”
The Benefits and Weaknesses of ChatGPT on Students’ Learning Writing
Su, A. A. T., & Nguyen, T. T. H. (2024) · International journal of AI in language education. · doi:10.54855/ijaile.24112 · Cited by 14
Unlocking the potential of ChatGPT in academic libraries
Hussain, A. (2024) · IP Indian Journal of Library Science and Information Technology · doi:10.18231/j.ijlsit.2024.015 · Cited by 15
The use of large language models as scaffolds for proleptic reasoning
Kudina, O., Ballsun-Stanton, B., & Alfano, M. (2025) · Asian Journal of Philosophy · doi:10.1007/s44204-025-00247-1 · Cited by 13
Exploring University Staff’s Perceptions of Using Generative Artificial Intelligence at University
Whitbread, M., Hayes, C., Prabhakar, S., & Upsher, R. J. (2025) · Education Sciences · doi:10.3390/educsci15030367 · Cited by 9
Obura, E. A., & Emoit, P. I. (2024) · Africa Education Review · doi:10.1080/18146627.2024.2440351 · Cited by 16
Nowacki, L., & Wrochna, A. E. (2025) · E-Learning and Digital Media · doi:10.1177/20427530251331083 · Cited by 11
Student perspectives on the use of AI-based language tools in academic writing
Boillos, M. M., & Mondragón, N. I. (2025) · Journal of Writing Research · doi:10.17239/jowr-2025.17.01.06 · Cited by 22
“As Firat (2023) noted, the rapid evolution of AILTs and their transformative impact on academia underscore the necessity to comprehend the entire ecosystem—this study represents a novel contribution to this research area.”
Nudging Motivation to Learn English Through a ChatGPT Smartphone-Based Hybrid Model
Muthmainnah, M., Apriani, E., Seraj, P. M. I., Obaid, A. J., & Yakin, A. M. A. (2023) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3693-0502-7.ch002 · Cited by 9
Using ChatGPT to Teach English for Academic Purposes
Glahn, K. (2024) · Journal of Education, Innovation, and Communication. · doi:10.34097/jeicom-5-2-december-23-5 · Cited by 9
Korkmaz, H., & Akbıyık, M. (2024) · Participatory Educational Research · doi:10.17275/per.24.76.11.6 · Cited by 10
A method for generating personalized learning content based on AIGC
Hu, Z. (2025) · Sustainable Futures · doi:10.1016/j.sftr.2025.101331 · Cited by 8
Towards Responsible Use: Student Perspectives on ChatGPT in Higher Education
Yang, H. (2024) · European Conference on e-Learning · doi:10.34190/ecel.23.1.2790 · Cited by 7
“Firat (2023) investigates the perceptions of students and scholars towards ChatGPT in universities.”
BackgroundInfluentialSui, X., Lin, Q., Wang, Q., & Wan, H. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13590-w · Cited by 9
“In this transformative educational landscape, undergraduates, recognized as the most dynamic and innovative demographic, are pivotal users and beneficiaries of AIGC technology (Firat, 2023).”
Characterizing Relationships with Companion and Assistant Large Language Models
Manoli, A., Pauketat, J. V. T., & Anthis, J. R. (2025) · ACM Conference on Computer Supported Cooperative Work (CSCW) · doi:10.1145/3715070.3749245 · Cited by 13
Haderlie, T. C., Sewak, S., Agarwal, S., & Lee, J. (2025) · Marketing Education Review · doi:10.1080/10528008.2025.2576159 · Cited by 8
Educators’ Acceptance and Use of AI Software: UTAUT2 Model
AÇIKGÜL, K., & Şad, S. N. (2026) · SAGE Open · doi:10.1177/21582440251413449 · Cited by 10
Sain, Z. H., & Kurniati, V. S. D. (2023) · TAMANSISWA INTERNATIONAL JOURNAL IN EDUCATION AND SCIENCE · doi:10.30738/tijes.v5i1.16274 · Cited by 11
VanderLinde, G., & Cury, T. M. (2024) · Cuaderno de Pedagogía Universitaria · doi:10.29197/cpu.v21i41.564 · Cited by 16
“…inteligencia artificial tienen el potencial de aumentar el compromiso y la retención de conocimientos entre los estudiantes, también existen problemas con su evaluación y valoración (Firat, 2023)), así como dudas sobre la autenticación, el plagio y la integridad académica (Crawford et al., 2023).”
BackgroundEducational Potential of ChatGPT: Teaching Tool for Students’ Competencies Development
Shabunina, V., Sarancha, V., Maslak, V., Shevchenko, O., & Tur, O. (2023) · 2023 IEEE 5th International Conference on Modern Electrical and Energy System (MEES) · doi:10.1109/mees61502.2023.10402380 · Cited by 7
“…of ChatGPT [8]; M. Firat investigated the implications of ChatGPT for students and universities by examining perceptions of scholars and students [9]; M. Javaid et al. described the opportunities towards ameliorating the education system through ChatGPT tool [10]; F. Fauzi et al. analysed the…”
BackgroundAlario-Hoyos, C., Kemcha, R., Kloos, C. D., Callejo, P., Estévez-Ayres, I., Santín-Cristóbal, D., Cruz-Argudo, F., & López-Sánchez, J. L. (2024) · 2024 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE) · doi:10.1109/tale62452.2024.10834365 · Cited by 8
“The widespread availability of chatbots, many offering free access, has led a growing number of students to integrate these tools into their daily academic routines, using them for tasks such as completing assignments and resolving subject-related questions [15], [16].”
Testa, M., Volpe, M. D., D’Amato, A., & Apuzzo, A. (2024) · Transforming Government People Process and Policy · doi:10.1108/tg-02-2024-0031 · Cited by 7
“Instagram, Facebook, Twitter and Net fl ix took 75, 300, 720 and 1,200days, respectively, to reach this number of users (Firat, 2023).”
Development of Linguistic Competence in English for Specific Purposes Through ChatGPT: A Case Study
Enamorado, M. Á. J. (2025) · Journal of language and Education · doi:10.17323/jle.2025.23745 · Cited by 17
Is Gen AI a professor in creativity? A case study in postgraduate students
Zhang, H., & Ge, S. (2025) · Education and Information Technologies · doi:10.1007/s10639-025-13644-z · Cited by 6
“Mehmet (2023) suggests that Gen AI plays a role in assisting humans with sorting and organizing ideas from stored data.”
Metadata
- Authors
- Fırat, M.
- Affiliations
- Anadolu University (TR)
- Corresponding author
- Mehmet Fırat
- ORCID
- Mehmet Fırat
- Venue
- Journal of Applied Learning & Teaching
- Publisher
- Open Access Publishing Association
- Published
- 2023-04-19
- Volume
- 6
- Issue
- 1
- ISSN
- 2591-801X (ISSN-L)
- OpenAlex
- W4366422585
- Semantic Scholar
- 6f9f5e84221b991756500676031e0ebb4dc00b0d
- Cited by
- 431
- References
- 27
- Citations by year
- 2026: 55 · 2025: 131 · 2024: 185 · 2023: 60
- FWCI
- 100.90
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- cc-by
- Locations
- Journal of Applied Learning & Teaching (publishedVersion, cc-by)
- 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 › Ethics and Social Impacts of AI
- Keywords
- ChatGPT, large language models, artificial intelligence in education, higher education, student perceptions, doctoral students, role of educators, assessment and evaluation, AI ethics, digital literacy, personalized learning, employability, future of work, privacy concerns, AI integration in universities
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.
A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
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