HomePsychology and Education: A Multidisciplinary Journalvol. 35 no. 3 (2025)

Perceptions, Benefits, and Challenges of Students in SMU Senior High School on the Integration of Generative AI

Keira Danielle Pablo | Kale Gezler Cadorna | Roman Cabanag | Aaron Lucky Berganio | Reine Patrize Roberto | Jhoanna Mj Guieb | Eloisa  Barbieto | Kristel Joy Dapiawen | Lady Valen Charon Dela Peña

Discipline: others in psychology

 

Abstract:

As we stand at the cusp of a revolution in classrooms, the utilization of Generative Artificial Intelligence (GenAI) in education has catapulted scholarly discourses into the spotlight. However, few research studies have delved into the potential benefits and challenges of GenAI in education. This study sought to determine the perceptions, benefits, and challenges of students in Saint Mary's University Senior High School (SMUSHS) regarding the use of generative AI. The study employed a descriptive-comparative research design, using both quantitative and qualitative methods. A Likert scale was used in the quantitative section, while an open-ended question was used for the qualitative part. With the use of purposive sampling, 274 students were selected as the respondents of the study. After data analysis, findings revealed that senior high school students positively perceive generative AI in education as a tool that enhances learning outcomes. Additionally, students tend to focus more on potential drawbacks than benefits when it comes to GenAI, as evidenced by the significantly higher average level of perceived challenges than benefits students experience in their education. It was also found that the frequency of usage of GenAI has a significant difference in students' perceptions of the use of GenAI in education and on the perceived benefits of GenAI in education. Furthermore, academic standing also played a major role in shaping the students' perceived challenges. For the potential integration of GenAI in education, the majority of the respondents suggest that restrictions and limitations be implemented as well as strengthening AI policies to ensure that students are not relying solely on AI for their academic work. This study could serve as a basis for formulating policies and guidelines on the use of GenAI in education and conducting seminars for students and teachers to address misconceptions and increase awareness of the benefits of using generative AI in educational settings.



References:

  1. Abdelwahab, H. R., Rauf, A., & Chen, D. (2022). Business students’ perceptions of Dutch higher education institutions in preparing them for artificial intelligence work environments. Industry and Higher Education, 37(1), 22–34. https://doi.org/10.1177/09504222221087614
  2. Alammar, A., & Amin, E. A. (2023). EFL students’ perception of using AI paraphrasing tools in English language research projects. Arab World English Journal, 14(3), 166–181. https://doi.org/10.24093/awej/vol14no3.11
  3. Al‐Badi, A. H., Khan, A. I., & Eid-Alotaibi. (2022). Perceptions of learners and instructors towards artificial intelligence in personalized learning. Procedia Computer Science, 201,445–451.
  4. https://doi.org/10.1016/j.procs.2022.03.058
  5. Ajlouni, A. O., Almahaireh, A. S., & Whaba, F. A. (2023). Students’ perception of using CHATGPT in Counseling and Mental Health education: the benefits and challenges. International Journal of Emerging Technologies in Learning (iJET), 18(20), 199–218. https://doi.org/10.3991/ijet.v18i20.42075
  6. Alzahrani, L. (2023). Analyzing students’ attitudes and behavior toward artificial intelligence technologies in higher education. International Journal of Recent Technology and Engineering (IJRTE), 11(6), 65–73. https://doi.org/10.35940/ijrte.f7475.0311623
  7. Amyatun, R. L., & Kholis, A. (2023). Can artificial intelligence (AI) like QuillBot AI assist students’ writing skills? Assisting learning to write texts using AI. English Language Education Reviews, 3(2), 135–154. https://doi.org/10.22515/elereviews.v3i2.7533
  8. Atlas, Stephen (2023). "ChatGPT for higher education and professional development: A guide to conversational AI." (2023). https://digitalcommons.uri.edu/cba_facpubs/548
  9. Baek, C., Tate, T. P., & Uci, M. W. (2023, December 12). “ChatGPT seems too good to be true”: College students’ use and perceptions of generative AI. https://doi.org/10.31219/osf.io/6tjpk
  10. Baidoo-Anu, D., Asamoah, D., Amoako, I., & Mahama, I. (2024). Exploring student perspectives on generative artificial intelligence in higher education learning. Discover Education, 3(1). https://doi.org/10.1007/s44217-024-00173-z
  11. Baidoo-Anu, D., & Leticia, O. A. (2023). Education in the era of generative artificial intelligence (AI): Understanding the potential benefits of ChatGPT in promoting teaching and learning. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4337484
  12. Barrett, A., & Pack, A. (2023). Not quite eye to A.I.: Student and teacher perspectives on the use of generative artificial intelligence in the writing process. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00427-0
  13. Barrot, J. S. (2023). Using ChatGPT for second language writing: Pitfalls and potentials. Assessing Writing, 57, 100745. https://doi.org/10.1016/j.asw.2023.100745
  14. Berg, C. (2023). The case for generative AI in scholarly practice. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4407587
  15. Bisdas, S., Topriceanu, C.-C., Zakrzewska, Z., Irimia, A.-V., Shakallis, L., Subhash, J., Casapu, M.-M., Leon-Rojas, J., Pinto dos Santos, D., Andrews, D. M., Zeicu, C., Bouhuwaish, A. M., Lestari, A. N., Abu-Ismail, L., Sadiq, A. S., Khamees, A., Mohammed, K. M. G., Williams, E., Omran, A. I., … Ebrahim, E. H. (2021). Artificial intelligence in medicine: A multinational multi-center survey on the medical and dental students’ perception. Frontiers in Public Health, 9, 795284. https://doi.org/10.3389/fpubh.2021.795284
  16. Bhandari, A., Purchuri, S. N., Sharma, C., Ibrahim, M., & Prior, M. (2021). Knowledge and attitudes towards artificial intelligence in imaging: a look at the quantitative survey literature. Clinical Imaging, 80, 413–419. https://doi.org/10.1016/j.clinimag.2021.08.004
  17. Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., & Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12405-0
  18. Chan, C.K.Y. (2023). Is AI changing the rules of academic misconduct? An in-depth look at students’ perceptions of ‘AI-giarism’. https://arxiv.org/abs/2306.03358
  19. Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8
  20. Chan, C. K. Y., & Lee, K. K. W. (2023). The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers? https://arxiv.org/abs/2305.02878
  21. Chan, C. K. Y., & Tsi, L. H. Y. (2023). The AI revolution in Education: Will AI replace or assist teachers in higher education? arXiv (Cornell University). https://doi.org/10.48550/arxiv.2305.01185
  22. Chan, C. K. Y., & Zhou, W. (2023). Deconstructing student perceptions of Generative AI (GenAI) through an Expectancy Value Theory (EVT)-based Instrument [Preprint]. arXiv. https://arxiv.org/abs/2305.01186
  23. Christensen, C. M., & Eyring, H. J. (n.d.). The Innovative University: Changing the DNA of higher education from the inside out. https://eric.ed.gov/?id=ED532274
  24. Collins, C., Dennehy, D., Conboy, K., & Mikalef, P. (2021). Artificial intelligence in information systems research: A systematic literature review and research agenda. International Journal of Information Management, 60, 102383.  https://doi.org/10.1016/j.ijinfomgt.2021.102383
  25. Dai, Y. (2024). Why students use or not use generative AI: Student conceptions, concerns, and implications for engineering education. Digital Engineering., 100019. https://doi.org/10.1016/j.dte.2024.100019
  26. Daher, W., & Hussein, A. (2024). Higher education students’ perceptions of GenAI tools for learning. Information, 15(7), 416. https://doi.org/10.3390/info15070416
  27. Dehouche, N., & Dehouche, K. (2023). What’s in a text-to-image prompt: The potential of Stable Difusion in visual arts education. https://doi.org/10.48550/arXiv.2301.01902
  28. Ding, L., Li, T., Jiang, S., & Gapud, A. (2023). Students’ perceptions of using ChatGPT in a physics class as a virtual tutor. International Journal of Educational Technology in Higher Education, 20(1).
  29. https://doi.org/10.1186/s41239-023-00434-1
  30. Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
  31. Duong, C. D., Vu, T. N., & Ngo, T. V. N. (2023). Applying a modified technology acceptance model to explain higher education students’ usage of ChatGPT: A serial multiple mediation model with knowledge sharing as a moderator. The International Journal of Management Education, 21(3), 100883. https://doi.org/10.1016/j.ijme.2023.100883
  32. Eden, C. A., Chisom, O. N., & Adeniyi, I. S. (2024). Integrating AI in education: Opportunities, challenges, and ethical considerations. Magna Scientia Advanced Research and Reviews, 10(2), 006-013. https://doi.org/10.30574/msarr.2024.10.2.0039
  33. Eken, S. (2023). Ethic wars: Student and educator attitudes in the context of ChatGPT. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4365433
  34. Elshaer, I. A., Hasanein, A. M., & Sobaih, A. E. E. (2024). The moderating effects of gender and study discipline in the relationship between university students’ acceptance and use of ChatGPT. European Journal of Investigation in Health Psychology and Education, 14(7), 1981–1995. https://doi.org/10.3390/ejihpe14070132
  35. Farhi, F., Jeljeli, R., Aburezeq, I., Dweikat, F. F., Al-Shami, S. A., & Slamene, R. (2023). Analyzing the students’ views, concerns, and perceived ethics about chat GPT usage. Computers and Education Artificial Intelligence, 5, 100180. https://doi.org/10.1016/j.caeai.2023.100180
  36. Feuerriegel, S., Hartmann, J., Janiesch, C., & Zschech, P. (2023). Generative AI. Business & Information Systems Engineering, 66(1), 111–126. https://doi.org/10.1007/s12599-023-00834-7
  37. Gesser-Edelsburg, A., Hijazi, R., Eliyahu, E., & Tal, A. (2024). Bridging the Divide: An empirical investigation of artificial intelligence and generative artificial intelligence integration across genders, disciplines and academic roles. European Journal of Open Distance and E-Learning, 26(s1), 51–69. https://doi.org/10.2478/eurodl-2024-0008
  38. Ghotbi, N., Ho, M. T., & Mantello, P. (2021). Attitude of college students towards ethical issues of artificial intelligence in an international university in Japan. AI & Society, 37(1), 283–290. https://doi.org/10.1007/s00146-021-01168-2
  39. Gocen, A., & Aydemir, F. (2020). Artificial intelligence in education and schools. Research on Education and Media, 12(1), 13–21. https://doi.org/10.2478/rem-2020-0003
  40. Gökçearslan, Ş., Tosun, C., & Erdemir, Z. G. (2024). Benefits, challenges, and methods of artificial intelligence (AI) chatbots in education: A systematic literature review. International Journal of Technology in Education, 7(1), 19–39. https://doi.org/10.46328/ijte.600
  41. Gong, B., Nugent, J. P., Guest, W., Parker, W., Chang, P. J., Khosa, F., & Nicolaou, S. (2019). Influence of artificial intelligence on Canadian medical students’ preference for radiology specialty: A national survey study. Academic Radiology, 26(4), 566–577. https://doi.org/10.1016/j.acra.2018.10.007
  42. Haleem, A., Javaid, M., Qadri, M. A., & Suman, R. (2022). Understanding the role of digital technologies in education: A review. Sustainable Operations and Computers, 3, 275–285. https://doi.org/10.1016/j.susoc.2022.05.004
  43. Harrer, S. (2023). Attention is not all you need: The complicated case of ethically using large language models in healthcare and medicine. EBioMedicine, 90, 104512. https://doi.org/10.1016/j.ebiom.2023.104512
  44. Heeg, D. M., & Avraamidou, L. (2023). The use of artificial intelligence in school science: a systematic literature review. Educational Media International, 60(2), 125–150. https://doi.org/10.1080/09523987.2023.2264990
  45. Hsu, A.J.C., Chen, M.YC. & Shin, NF. From academic achievement to career development: Does self-regulated learning matter?. Int J Educ Vocat Guidance 22, 285–305 (2022). https://doi.org/10.1007/s10775-021-09486-z
  46. Hu, K. (2023, February 2). ChatGPT sets record for fastest-growing user base—analyst note. Reuters. Retrieved from https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/
  47. Hutson, James, "Integrating art and AI: Evaluating the educational impact of AI tools in digital art history learning" (2024). Faculty Scholarship. 578.https://digitalcommons.lindenwood.edu/faculty-research-papers/578
  48. Jangjarat, K., Kraiwanit, T., Limna, P., & Sonsuphap, R. (2023). Public perceptions towards ChatGPT​ a​s the​ Robo​-Assistant. Online Journal of Communication and Media Technologies, 13(3), e202338. https://doi.org/10.30935/ojcmt/13366
  49. Kee, T., Kuys, B., & King, R. (2024). Generative artificial intelligence to enhance architecture education to develop digital literacy and holistic competency. Journal of Artificial Intelligence in Architecture, 3(1), 24–41. https://doi.org/10.24002/jarina.v3i1.8347
  50. Keleş, P. U., & Aydın, S. (2021). University students’ perceptions about artificial intelligence. Shanlax International Journal of Education, 9(S1-May), 212–220. https://doi.org/10.34293/education.v9is1-may.4014
  51. Kelly, A., Sullivan, M., & Strampel, K. (n.d.). Generative artificial intelligence: University student awareness, experience, and confidence in use across disciplines. Research Online. https://ro.uow.edu.au/jutlp/vol20/iss6/12/
  52. Kim, J., & Cho, Y. H. (2023). My teammate is AI: Understanding students’ perceptions of student-AI collaboration in drawing tasks. Asia Pacific Journal of Education, 1–15. https://doi.org/10.1080/02188791.2023.2286206
  53. Kim, T., & Cho, W. (2023). Employee voice opportunities enhance organizational performance when faced with competing demands. Review of Public Personnel Administration, 0(0). https://doi.org/10.1177/0734371X231190327
  54. Kim, J., & Lee, S. (2022). Are two heads better than one?: The effect of student-AI collaboration on students’ learning task performance. TechTrends, 67(2), 365–375. https://doi.org/10.1007/s11528-022-00788-9
  55. Kim, J., Yu, S., Detrick, R. et al. Exploring students’ perspectives on Generative AI-assisted academic writing. Educ Inf Technol (2024). https://doi.org/10.1007/s10639-024-12878-7
  56. Kitamura, F. C. (2023). ChatGPT is shaping the future of medical writing but still requires human judgment. Radiology, 307(2), e230171. https://doi.org/10.1148/radiol.230171
  57. Kumar, A. H. S. (2023). Analysis of ChatGPT tool to assess the potential of its utility for academic writing in biomedical domain. BEMS Reports, 9(1), 24–30. https://doi.org/10.5530/bems.9.1.5
  58. Lee, Y.-F., Hwang, G.-J., & Chen, P.-Y. (2022). Impacts of an AI-based chatbot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational Technology Research and Development, 70, 1843–1865. https://doi.org/10.1007/s11423-022-10142-8
  59. Li, Z., Liang, C., Peng, J., & Yin, M. (2024). The value, benefits, and concerns of generative AI-powered Assistance in Writing. The Value, Benefits, and Concerns of Generative AI-Powered Assistance in writing. https://doi.org/10.1145/3613904.3642625
  60. Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2). https://doi.org/10.1016/j.ijme.2023.100790
  61. Liu, Binghan. (2023). Chinese university students’ attitudes and perceptions in learning English using ChatGPT. International Journal of Education and Humanities. 3. 132-140. 10.58557/(ijeh).v3i2.145. https://www.researchgate.net/publication/373693120
  62. Lubowitz, J. H. (2023). ChatGPT, an artificial intelligence chatbot, is impacting medical literature. Arthroscopy, 39(5),1121-1122. https://doi.org/10.1016/j.arthro.2023.01.015
  63. Maerten, A., & Soydaner, D. (2023, February 14). From paintbrush to pixel: A review of deep neural networks in AI-generated art. arXiv.org. https://arxiv.org/abs/2302.10913
  64. McMurtrie, B. (2023) 'How ChatGPT could help or hurt students with disabilities', The chronicle of higher education. Available at: https://www.chronicle.com/article/how-chatgpt-could-help-or-hurt-students-with-disabilities
  65. Miao, F., and W. Holmes. 2023. “Guidance for Generative AI in Education and Research.” https://www.unesco.org/en/articles/guidance-generative-ai-education-and-research.
  66. Mohammed, P. S., & Watson, E. ‘. (2019). Towards inclusive education in the age of artificial intelligence: Perspectives, challenges, and opportunities. In Perspectives on rethinking and reforming education (pp. 17–37). https://doi.org/10.1007/978-981-13-8161-4_2
  67. Moqbel, M. S. S., & Al-Kadi, A. M. T. (2023). Foreign language learning assessment in the age of CHATGPT. Journal of English Studies in Arabia Felix, 2(1), 71–84. https://doi.org/10.56540/jesaf.v2i1.62
  68. Nader, K., Toprac, P., Scott, S., & Baker, S. (2022). Public understanding of artificial intelligence through entertainment media. AI and Society. https://doi.org/10.1007/s00146-022-01427-w
  69. Narayanan, S. (2024). Decoding the digital fine print: Navigating the potholes in terms of service/ use of GenAI tools against the emerging need for transparent and trustworthy tech futures. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2406.11845
  70. Obaid, O. I., Ali, A. H., & Yaseen, M. G. (2023). Impact of ChatGPT on scientific research: Opportunities, risks, limitations, and ethical issues. Iraqi Journal for Computer Science and Mathematics, 13–17. https://doi.org/10.52866/ijcsm.2023.04.04.002
  71. Obenza, B., Salvahan, A., Rios, A. N., Solo, A., Alburo, R. A., & Gabila, R. J. (2024, February 13). University students’ perception and use of ChatGPT: Generative artificial intelligence (AI) in higher education. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4724968
  72. O’Dea, X., Ng, D. T. K., O’Dea, M., & Shkuratskyy, V. (2024). Factors affecting university students’ generative AI literacy: Evidence and evaluation in the UK and Hong Kong contexts. Policy Futures in Education. https://doi.org/10.1177/14782103241287401
  73. Olatunde-Aiyedun, T. G. (2024). Artificial intelligence (AI) in education: Integration of AI into science education curriculum in Nigerian. ResearchGate. https://doi.org/10.13140/RG.2.2.31699.76320
  74. Peres, R., Shreier, M., Schweidel, D., & Sorescu, A. (2023). On ChatGPT and beyond: How generative artifcial intelligence may affect research, teaching, and practice. International Journal of Research in Marketing. https://doi.org/10.1016/j. ijresmar.2023.03.00
  75. Petricini, T., Wu, C., & Zipf, S. T. (2023). Perceptions about Generative AI and ChatGPT use by faculty and college students. https://doi.org/10.35542/osf.io/jyma4
  76. Pu, S., Ahmad, M. N., Khambari, M. N. M., & Yap, N. K., (2021). Identification and analysis of core topics in educational artificial intelligence research: A Bibliometric analysis. Cypriot Journal of Educational Science. 16(3), 995-1009 https://doi.org/10.18844/cjes.v16i3.5782
  77. Robinson, S., Yasar, K., & Lewis, S. (2024, October 18). What is a Generative Adversarial Network (GAN)? Search Enterprise AI. Retrieved November 30, 2024, from https://www.techtarget.com/searchenterpriseai/definition/generative-adversarial-network-GAN
  78. Sallam, M. (2023). ChatGPT utility in healthcare education, research, and practice: Systematic review on the promising perspectives and valid concerns. Healthcare, 11(6), 887. https://doi.org/10.3390/healthcare11060887
  79. Schönberger, D. (2019). Artificial intelligence in healthcare: A critical analysis of the legal and ethical implications. International Journal of Law and Information Technology, 27(2), 171–203. https://doi.org/10.1093/ijlit/eaz004
  80. Sekeroglu, B., Dimililer, K. and Tuncal, K. (2019) Student performance prediction and classification using Machine Learning Algorithms. Proceedings of the 2019 8th International Conference on Educational and Information Technology, New York, 2-4 March 2019, 7-11. https://doi.org/10.1145/3318396.3318419
  81. Siregar, F., Hasmayni, B., & Lubis, A. (2024, February 1). The analysis of ChatGPT usage impact on learning motivation among scout students. ResearchHub. https://www.researchhub.com/paper/4484890/the-analysis-of-chat-gpt-usage-impact-on-learning-motivation-among-scout-students/conversation
  82. Sit, C., Srinivasan, R., Amlani, A., Muthuswamy, K., Azam, A., Monzon, L., & Poon, D. S. (2020). Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: A mutilcentre survey. Insights into Imaging. https://doi.org/10.1186/s13244-019-0830-7
  83. Slimi, Z. (2023b). The impact of artificial intelligence on higher education: An empirical study. European Journal of Educational Sciences, 10(1). https://doi.org/10.19044/ejes.v10no1a17
  84. Stöhr, C., Ou, A. W., & Malmström, H. (2024). Perceptions and usage of AI chatbots among students in higher education across genders, academic levels and fields of study. Computers and Education Artificial Intelligence, 100259. https://doi.org/10.1016/j.caeai.2024.100259
  85. Su, Y., Lin, Y., & Lai, C. (2023). Collaborating with ChatGPT in argumentative writing classrooms. Assessing Writing, 57, 100752. https://doi.org/10.1016/j.asw.2023.100752
  86. Sun, G. H., & Hoelscher, S. H. (2023). The ChatGPT storm and what faculty can do. Nurse Educator, 48(3), 119–124. https://doi.org/10.1097/nne.0000000000001390
  87. Taber, K. S. (2017). The use of cronbach’s alpha when developing and reporting research instruments in science education. Research in Science Education, 48(6), 1273–1296. https://doi.org/10.1007/s11165-016-9602-2
  88. Tala, M. L., Müller, C. B., Nastase, I. A., State, O., & Gheorghe, G. (2024b). Exploring university students’ perceptions of generative artificial intelligence in education. Amfiteatru Economic, 26(65), 71. https://doi.org/10.24818/ea/2024/65/71
  89. Tominc, P., & Rožman, M. (2023, June 16). Perception of artificial intelligence by students. https://encyclopedia.pub/entry/45643
  90. Tseng, W., & Warschauer, M. (2023). AI-writing tools in education: If you can’t beat them, join them. Journal of China Computer-Assisted Language Learning, 3(2), 258–262. https://doi.org/10.1515/jccall-2023-0008
  91. UNESCO (2019). Artificial intelligence in education: Challenges and opportunities for sustainable development. MINISTERIO DE EDUCACIÓN. http://repositorio.minedu.gob.pe/handle/20.500.12799/6533
  92. Van Dis, E. a. M., Bollen, J., Zuidema, W., Van Rooij, R., & Bockting, C. L. (2023). ChatGPT: Five priorities for research. Nature, 614(7947), 224–226. https://doi.org/10.1038/d41586-023-00288-7
  93. Warschauer, M., Tseng, W., Yim, S., Webster, T., Jacob, S., Du, Q, & Tate, T. (2023). The affordances and contradictions of AI-generated text for second language writers. https://doi.org/10.2139/ssrn.440438
  94. Yang, & Xiaochen. (n.d.). Foundations of generative AI. https://link.springer.com/chapter/10.1007/978-3-031-54252-7_1
  95. Yigitcanlar, T., Degirmenci, K., & Inkinen, T. (2022). Drivers behind the public perception of artificial intelligence: Insights from major Australian cities. AI and Society. https://doi.org/10.1007/s00146-022-01566-0
  96. Y Yüzbaşioğlu, E. (2021). Attitudes and perceptions of dental students towards artificial intelligence. Journal of Dental Education, 85(1), 60–68. https://doi.org/10.1002/jdd.12385
  97. Zawacki‐Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1). https://doi.org/10.1186/s41239-019-0171-0
  98. Zhai, X. (2022). ChatGPT user experience: Implications for education. https://doi.org/10.2139/ssrn.4312418
  99. Zhang, K., & Aslan, A. (2021). AI technologies for education: Recent research & future directions. Computers & Education: Artificial Intelligence, 2, 100025. https://doi.org/10.1016/j.caeai.2021.100025
  100. Zhu, C., Sun, M., Luo, J., Li, T., & Wang, M. (2023). How to harness the potential of ChatGPT in education? Knowledge Management & E-Learning, 15(2), 133–152. https://doi.org/10.34105/j.kmel.2023.15.008