Embracing AI in academia: A mixed methods study of nursing students’ and educators’ perspectives on using ChatGPT

Ebtsam Aly Abou Hashish; Sharifah Abdulmuttalib Alsayed; Noura Mohamed Fadl Abdel Razek

doi:10.1371/journal.pone.0327981

Peer Review History

Original SubmissionDecember 30, 2024
Decision Letter - Lucija Gosak, Editor PONE-D-24-60162Embracing AI in Academia: A mixed methods study of nursing students' and educators' perspectives on using ChatGPTPLOS ONE Dear Dr. Abou Hashish, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by May 02 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: Yes Reviewer #2: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes Reviewer #2: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This study provides valuable insights into the role of AI in nursing education. Addressing the concerns outlined below more explicitly will enhance the study’s overall impact. Thematic Analysis Rigor 1.The qualitative analysis mentions Braun and Clarke’s framework but does not specify how intercoder reliability was ensured. Were multiple researchers involved in coding? If so, how were disagreements resolved? Providing more details would enhance the trustworthiness of the findings. Limitations 2.While the study acknowledges certain limitations, it should discuss how these might impact the findings and interpretations. For instance, the sample includes students and educators from a single institution. How might this affect the generalizability of the results? Consider discussing whether similar findings could be expected in other cultural or educational settings. Detailed Discussion on Ethical Concerns 3.The ethical concerns regarding ChatGPT’s use (plagiarism, over-reliance, and privacy issues) are well-identified. However, the study would benefit from a deeper discussion on potential solutions. Could existing ethical frameworks in nursing education provide guidance? Reviewer #2: Review Report The study aimed to explore nursing students' and educators' perspectives on using ChatGPT in academia through a mixed-methods approach. However, several concerns raise doubts about the study's rigor and contribution to the existing literature: • The introduction discusses AI/ChatGPT adoption, but no adoption theory has been utilized to assess attitudes toward ChatGPT. The absence of a theoretical framework weakens the study's foundation. • The research gap is not clearly established, making it unclear why this study was conducted. Without a well-defined gap, the study’s objectives seem questionable. • Numerous studies already exist on the adoption of ChatGPT, particularly regarding knowledge and attitudes. The authors have not adequately demonstrated how this study differs from previous research. Specifically, it is unclear whether findings from nursing students would differ significantly from those of students in other domains. • Although the study focuses on nursing students, no domain-specific questions were included. This omission limits the study's relevance to nursing education. • The sample size raises concerns. The manuscript first states that 240 students participated but then mentions that the minimum recommended sample size was 169. If the entire population was invited to participate, why was a sample-based inference needed? Additionally, increasing the sample size solely to enhance statistical significance without considering response rates and data collection timelines is problematic. • The analysis appears overly simplistic, relying on basic statistical techniques such as ANOVA and elementary graphs. A more robust analytical approach would have strengthened the findings. Given these concerns, I do not recommend the manuscript for publication in a quality journal. Recommended Readings: • Ahmed, F. R., Rushdan, E. E., Al-Yateem, N., Almaazmi, A. N., Subu, M. A., Hijazi, H., ... & Aburuz, M. E. (2024). AI in higher education: unveiling nursing students' perspectives on ChatGPT's challenges and opportunities. Teaching and Learning in Nursing. • Arjanto, P., & Aditama, M. H. R. (2025). AI in nursing education: From ethical challenges to institutional strategies for effective adoption. Teaching and Learning in Nursing. • Wang, X., Fei, F., Wei, J., Huang, M., Xiang, F., Tu, J., ... & Gan, J. (2024). Knowledge and attitudes toward artificial intelligence in nursing among various categories of professionals in China: a cross-sectional study. Frontiers in Public Health, 12, 1433252. • Sallam, M., Salim, N. A., Barakat, M., Al-Mahzoum, K., Ala'a, B., Malaeb, D., ... & Hallit, S. (2023). Assessing health students' attitudes and usage of ChatGPT in Jordan: validation study. JMIR Medical Education, 9(1), e48254. • Almogren, A. S., Al-Rahmi, W. M., & Dahri, N. A. (2024). Exploring factors influencing the acceptance of ChatGPT in higher education: A smart education perspective. Heliyon, 10(11). • Sahari, Y., Al-Kadi, A. M. T., & Ali, J. K. M. (2023). A cross sectional study of ChatGPT in translation: Magnitude of use, attitudes, and uncertainties. Journal of Psycholinguistic Research, 52(6), 2937-2954. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy . Reviewer #1: Yes: Moustaq Karim Khan Rony Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. 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Revision 1
26 Mar 2025 Author Response Dear respected Reviewers We sincerely appreciate your time and effort in reviewing our manuscript. We are grateful for your insightful comments and constructive feedback, which have significantly improved the clarity, rigor, and impact of our study. We have considered each point raised and have made the necessary revisions accordingly. Below, we provide detailed responses to each comment, indicating how the manuscript has been revised to address the concerns. All modifications done are colored blue. We believe the revisions have significantly improved the clarity, rigor, and contribution of our work. We respectfully request reconsideration of our manuscript for publication and remain open to any further revisions that may be required. Thank you again for your guidance and the opportunity to revise and improve our manuscript. Reviewer #1 Comments 1. The qualitative analysis mentions Braun and Clarke’s framework but does not specify how intercoder reliability was ensured. Were multiple researchers involved in coding? If so, how were disagreements resolved? Providing more details would enhance the trustworthiness of the findings. Authors’ Response: Thank you for this suggestion. We have now provided a more detailed explanation of our approach to intercoder reliability in the Methods section. Specifically, two independent researchers manually coded the data. They initially worked separately to identify themes, then compared their findings and discussed discrepancies until reaching consensus. This process ensured consistency and minimized bias, thereby enhancing the trustworthiness of our qualitative analysis. 2. While the study acknowledges certain limitations, it should discuss how these might impact the findings and interpretations. For instance, the sample includes students and educators from a single institution. How might this affect the generalizability of the results? Consider discussing whether similar findings could be expected in other cultural or educational settings. Authors’ Response: We appreciate this recommendation. We have expanded the Limitations section to discuss how the single-institution sample may impact generalizability. While the findings provide valuable insights, they may not be fully generalizable to other nursing programs with different curricula, institutional cultures, or technological infrastructures. Future research involving diverse educational settings and international comparisons is recommended to validate and extend our findings. 3. The ethical concerns regarding ChatGPT’s use (plagiarism, over-reliance, and privacy issues) are well-identified. However, the study would benefit from a deeper discussion on potential solutions. Could existing ethical frameworks in nursing education provide guidance? Authors’ Response: Thank you for highlighting this point. We have expanded our discussion to incorporate ethical frameworks from nursing education, such as the American Nurses Association (ANA) Code of Ethics and the International Council of Nurses (ICN) Code of Ethics. These frameworks emphasize responsible AI use, professional accountability, and ethical decision-making. Additionally, we have suggested institutional policies, academic integrity guidelines, and structured AI literacy training programs to mitigate ethical risks and ensure responsible ChatGPT use in nursing education. Reviewer #2 Comments 1. The introduction discusses AI/ChatGPT adoption, but no adoption theory has been utilized to assess attitudes toward ChatGPT. The absence of a theoretical framework weakens the study's foundation. Authors’ Response: We appreciate this important observation. In response, we have now explicitly incorporated the Technology Acceptance Model (TAM) as the theoretical framework guiding our study. TAM provides a structured approach to understanding users’ perceptions, attitudes, and adoption of ChatGPT in academic settings. We have revised the Introduction section to reflect this addition. 2. The research gap is not clearly established, making it unclear why this study was conducted. Without a well-defined gap, the study’s objectives seem questionable. Authors’ Response: Thank you for this valuable feedback. We have revised the Introduction section to clearly articulate the research gap. Our study uniquely addresses this gap by exploring ChatGPT’s role within the discipline-specific context of nursing education with both students and educators ample and mixed-methods approach to complement and integrate findings. 3. Numerous studies already exist on the adoption of ChatGPT, particularly regarding knowledge and attitudes. The authors have not adequately demonstrated how this study differs from previous research. Specifically, it is unclear whether findings from nursing students would differ significantly from those of students in other domains. Authors’ Response: We appreciate this concern. We have now included a comparative discussion in the Introduction and Discussion sections, highlighting how our study differs from prior research. While general AI adoption studies exist, our research focuses on nursing education, a field with unique ethical, practical, and critical thinking demands. The findings provide domain-specific insights that distinguish nursing students' perspectives from those in other academic disciplines. 4. Although the study focuses on nursing students, no domain-specific questions were included. This omission limits the study's relevance to nursing education. Authors’ Response: Thank you for this observation. All participants were nursing students and educators, ensuring that responses were inherently discipline-specific. We explicitly use the word "nursing" in our qualitative questions. We have clarified this in the Methods section. 5. The sample size raises concerns. The manuscript first states that 240 students participated but then mentions that the minimum recommended sample size was 169. If the entire population was invited to participate, why was a sample-based inference needed? Authors’ Response: We appreciate the reviewer’s observation regarding sample size clarification. While the minimum recommended sample size was calculated to be 169 based on power analysis, we invited the entire student population (N = 300) to participate in order to enhance representativeness and reduce selection bias. A total of 240 students responded, exceeding the minimum requirement and thereby strengthening the reliability and generalizability of the findings. Sample-based inference was still appropriate because not all members of the population responded. Thus, statistical inference was necessary to estimate the characteristics of the broader student population and examine associations among variables. This approach aligns with best practices in survey-based educational research. 6. The analysis appears overly simplistic, relying on basic statistical techniques such as ANOVA and elementary graphs. A more robust analytical approach would have strengthened the findings. Authors’ Response: Thank you for this valuable feedback. In response, we have expanded the statistical analysis to include Pearson correlation and multiple regression analyses in addition to the originally reported ANOVA. These advanced methods allow us to explore predictive relationships and associations between variables more robustly. We have also added five quantitative tables, four figures, and one qualitative table with a graphical summary to enhance data visualization and interpretation. These enhancements provide a deeper and more rigorous analysis of ChatGPT adoption in nursing education and strengthen the overall credibility and impact of our findings. Authors’ Response to Reviewer 2’s Final Comment: We appreciate the reviewer’s critical feedback and acknowledge the concerns raised. We have taken substantial steps to improve the manuscript by addressing all comments. While we recognize that the reviewer initially did not recommend the manuscript for publication, we genuinely value constructive criticism, as it allows us to refine and enhance our work. The revisions we have made—including strengthening the statistical analyses, incorporating a theoretical framework, clarifying the research gap, and refining discussions on ethical considerations—aim to elevate the study’s rigor and relevance. Beside the nature of mixed-methods study and its value. We sincerely hope that these improvements align with the journal's quality expectations. We kindly request reconsideration of our revised manuscript and welcome any further suggestions to enhance its contribution to the field. We hope that our revisions have sufficiently addressed all concerns. Thank you again for your constructive feedback and guidance. We look forward to your further evaluation. Sincerely, Corresponding Author: Prof. Ebtsam Attachments Attachment Submitted filename: Authors response to reviewer comments.pdf https://doi.org/10.1371/journal.pone.0327981.r002
Decision Letter - Mary Mathew, Editor Embracing AI in academia: a mixed methods study of nursing students' and educators' perspectives on using chatgpt PONE-D-24-60162R1 Dear Dr. Ebstam Aly Abou Hashish We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Mary Mathew, MD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #2: Yes ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #2: Yes ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #2: Yes ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #2: Yes ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #2: I am pleased with the author’s responses to our queries and the revisions made. The manuscript employs a rigorous methodology and represents a high-quality contribution; accordingly, I recommend its acceptance in its current form. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy . Reviewer #2: Yes: Dr. Puneet Kumar Gupta ******** https://doi.org/10.1371/journal.pone.0327981.r003
Formally Accepted
Acceptance Letter - Mary Mathew, Editor PONE-D-24-60162R1 PLOS ONE Dear Dr. Abou Hashish, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Mary Mathew Academic Editor PLOS ONE Attachments Attachment Submitted filename: Response_Letter_to_Reviewer_Comments.docx https://doi.org/10.1371/journal.pone.0327981.r004

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