AI in enhancing cultural sensitivity

Abstract

This study investigates the role of Artificial Intelligence (AI) in promoting multicultural sensitivity and inclusivity in education. Using the PRISMA framework, 71 primary articles were analyzed from ERIC, ProQuest, Scopus, and Web of Science. Findings indicate that AI-based instructional media outperform conventional methods in improving cultural representation and reducing implicit biases. However, challenges such as algorithmic bias and unequal access persist, underscoring the need for ethical frameworks and culturally responsive pedagogies. This research highlights AI's potential to foster adaptive learning environments, enhance engagement, and address educational inequalities. Recommendations emphasize the importance of ethical AI implementation to support equitable and inclusive practices in multicultural education.
Keywords
  • AI
  • pendidikan multikultural
  • bias algoritmik
  • representasi budaya
  • personalisasi konten
  • keterlibatan siswa
References
  1. Abdaljaleel, M., Barakat, M., Alsanafi, M., Salim, N. A., Abazid, H., Malaeb, D., Mohammed, A. H., Hassan, B. A. R., Wayyes, A. M., Farhan, S. S., Khatib, S. El, Rahal, M., Sahban, A., Abdelaziz, D. H., Mansour, N. O., AlZayer, R., Khalil, R., Fekih-Romdhane, F., Hallit, R., … Sallam, M. (2024). A multinational study on the factors influencing university students’ attitudes and usage of ChatGPT. Scientific Reports, 14(1), 1983. https://doi.org/10.1038/s41598-024-52549-8
  2. Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429. https://doi.org/10.30935/cedtech/13152
  3. Aldoseri, A., Al-Khalifa, K. N., & Hamouda, A. M. (2024). AI-Powered Innovation in Digital Transformation: Key Pillars and Industry Impact. Sustainability, 16(5), 1790. https://doi.org/10.3390/su16051790
  4. Alyahyan, E., & Düştegör, D. (2020). Predicting academic success in higher education: literature review and best practices. International Journal of Educational Technology in Higher Education, 17(1), 3. https://doi.org/10.1186/s41239-020-0177-7
  5. Androutsopoulou, A., Karacapilidis, N., Loukis, E., & Charalabidis, Y. (2019). Transforming the communication between citizens and government through AI-guided chatbots. Government Information Quarterly, 36(2), 358–367. https://doi.org/10.1016/j.giq.2018.10.001
  6. Ansari, A. N., Ahmad, S., & Bhutta, S. M. (2024). Mapping the global evidence around the use of ChatGPT in higher education: A systematic scoping review. Education and Information Technologies, 29(9), 11281–11321. https://doi.org/10.1007/s10639-023-12223-4
  7. Baker, R. S., & Hawn, A. (2022). Algorithmic Bias in Education. International Journal of Artificial Intelligence in Education, 32(4), 1052–1092. https://doi.org/10.1007/s40593-021-00285-9
  8. Bhutoria, A. (2022). Personalized education and Artificial Intelligence in the United States, China, and India: A systematic review using a Human-In-The-Loop model. Computers and Education: Artificial Intelligence, 3, 100068. https://doi.org/10.1016/j.caeai.2022.100068
  9. Bilquise, G., Ibrahim, S., & Salhieh, S. M. (2024). Investigating student acceptance of an academic advising chatbot in higher education institutions. Education and Information Technologies, 29(5), 6357–6382. https://doi.org/10.1007/s10639-023-12076-x
  10. Bodkin‐andrews, G. H., Denson, N., & Bansel, P. (2013). Teacher Racism, Academic Self‐Concept, and Multiculturation: Investigating Adaptive and Maladaptive Relations With Academic Disengagement and Self‐Sabotage for Indigenous and Non‐Indigenous Australian Students. Australian Psychologist, 48(3), 226–237. https://doi.org/10.1111/j.1742-9544.2012.00069.x
  11. Boscardin, C. K., Gin, B., Golde, P. B., & Hauer, K. E. (2024). ChatGPT and Generative Artificial Intelligence for Medical Education: Potential Impact and Opportunity. Academic Medicine, 99(1), 22–27. https://doi.org/10.1097/ACM.0000000000005439
  12. Boubker, O. (2024). From chatting to self-educating: Can AI tools boost student learning outcomes? Expert Systems with Applications, 238, 121820. https://doi.org/10.1016/j.eswa.2023.121820
  13. Burgess, C., Bishop, M., & Lowe, K. (2022). Decolonising Indigenous education: the case for cultural mentoring in supporting Indigenous knowledge reproduction. Discourse: Studies in the Cultural Politics of Education, 43(1), 1–14. https://doi.org/10.1080/01596306.2020.1774513
  14. Burrell, J., & Fourcade, M. (2021). The Society of Algorithms. Annual Review of Sociology, 47(1), 213–237. https://doi.org/10.1146/annurev-soc-090820-020800
  15. Caingcoy, M. (2023). Culturally Responsive Pedagogy. Diversitas Journal, 8(4), 3203–3212. https://doi.org/10.48017/dj.v8i4.2780
  16. Cascella, M., Semeraro, F., Montomoli, J., Bellini, V., Piazza, O., & Bignami, E. (2024). The Breakthrough of Large Language Models Release for Medical Applications: 1-Year Timeline and Perspectives. Journal of Medical Systems, 48(1), 22. https://doi.org/10.1007/s10916-024-02045-3
  17. Celik, I., Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The Promises and Challenges of Artificial Intelligence for Teachers: a Systematic Review of Research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528-022-00715-y
  18. Chan, C. K. Y. (2023). A comprehensive AI policy education framework for university teaching and learning. International Journal of Educational Technology in Higher Education, 20(1), 38. https://doi.org/10.1186/s41239-023-00408-3
  19. Chassignol, M., Khoroshavin, A., Klimova, A., & Bilyatdinova, A. (2018). Artificial Intelligence trends in education: a narrative overview. Procedia Computer Science, 136, 16–24. https://doi.org/10.1016/j.procs.2018.08.233
  20. Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
  21. Chen, X., Xie, H., Zou, D., & Hwang, G.-J. (2020). Application and theory gaps during the rise of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100002. https://doi.org/10.1016/j.caeai.2020.100002
  22. Chiu, T. K. F. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6, 100197. https://doi.org/10.1016/j.caeai.2023.100197
  23. Chiu, T. K. F., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2023). Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interactive Learning Environments. https://doi.org/10.1080/10494820.2023.2172044
  24. Cooper, G. (2023). Examining Science Education in ChatGPT: An Exploratory Study of Generative Artificial Intelligence. Journal of Science Education and Technology, 32(3), 444–452. https://doi.org/10.1007/s10956-023-10039-y
  25. Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International, 61(2), 228–239. https://doi.org/10.1080/14703297.2023.2190148
  26. Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: the state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00392-8
  27. Crompton, H., Jones, M. V., & Burke, D. (2024). Affordances and challenges of artificial intelligence in K-12 education: a systematic review. Journal of Research on Technology in Education, 56(3), 248–268. https://doi.org/10.1080/15391523.2022.2121344
  28. Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
  29. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
  30. Elbanna, S., & Armstrong, L. (2024). Exploring the integration of ChatGPT in education: adapting for the future. Management & Sustainability: An Arab Review, 3(1), 16–29. https://doi.org/10.1108/MSAR-03-2023-0016
  31. Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024). A SWOT analysis of ChatGPT: Implications for educational practice and research. Innovations in Education and Teaching International, 61(3), 460–474. https://doi.org/10.1080/14703297.2023.2195846
  32. Forsyth, C., Irving, M., Short, S., Tennant, M., & Gilroy, J. (2019a). Strengthening Indigenous cultural competence in dentistry and oral health education: Academic perspectives. European Journal of Dental Education, 23(1). https://doi.org/10.1111/eje.12398
  33. Forsyth, C., Irving, M., Short, S., Tennant, M., & Gilroy, J. (2019b). Students Don’t Know What They Don’t Know: Dental and Oral Health Students’ Perspectives on Developing Cultural Competence Regarding Indigenous Peoples. Journal of Dental Education, 83(6), 679–686. https://doi.org/10.21815/JDE.019.078
  34. García Peñalvo, F. J., Llorens-Largo, F., & Vidal, J. (2023). La nueva realidad de la educación ante los avances de la inteligencia artificial generativa. RIED-Revista Iberoamericana de Educación a Distancia, 27(1), 9–39. https://doi.org/10.5944/ried.27.1.37716
  35. Gaur, A. S., Sharan, H. O., & Kumar, R. (2024). AI in education: Ethical challenges and opportunities. In The Ethical Frontier of AI and Data Analysis (pp. 39–54). https://doi.org/10.4018/979-8-3693-2964-1.ch003
  36. Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023). How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? The Implications of Large Language Models for Medical Education and Knowledge Assessment. JMIR Medical Education, 9, e45312. https://doi.org/10.2196/45312
  37. Golafshani, N. (2023). Teaching mathematics to all learners by tapping into indigenous legends: A pathway towards inclusive education. Journal of Global Education and Research, 7(2), 99–115. https://doi.org/10.5038/2577-509X.7.2.1224
  38. Grassini, S. (2023). Shaping the Future of Education: Exploring the Potential and Consequences of AI and ChatGPT in Educational Settings. Education Sciences, 13(7). https://doi.org/10.3390/educsci13070692
  39. Habib, S., Vogel, T., Anli, X., & Thorne, E. (2024). How does generative artificial intelligence impact student creativity? Journal of Creativity, 34(1), 100072. https://doi.org/10.1016/j.yjoc.2023.100072
  40. Hartinah, H., Fauziah Badarab, I., Nur Hasanah, I., & Madjid, I. (2023). Conflict Management Strategies in Multicultural Education Subjects for Class V Students MI Muhammadiyah 02 Mariyai. Journal of Quality Assurance in Islamic Education (JQAIE), 3(2), 69–79. https://doi.org/10.47945/jqaie.v3i2.1194
  41. Hinojo-Lucena, F.-J., Aznar-Díaz, I., Cáceres-Reche, M.-P., & Romero-Rodríguez, J.-M. (2019). Artificial Intelligence in Higher Education: A Bibliometric Study on its Impact in the Scientific Literature. Education Sciences, 9(1), 51. https://doi.org/10.3390/educsci9010051
  42. Hwang, G.-J., Xie, H., Wah, B. W., & Gašević, D. (2020). Vision, challenges, roles and research issues of Artificial Intelligence in Education. Computers and Education: Artificial Intelligence, 1, 100001. https://doi.org/10.1016/j.caeai.2020.100001
  43. Jiang, Y., Li, X., Luo, H., Yin, S., & Kaynak, O. (2022). Quo vadis artificial intelligence? Discover Artificial Intelligence, 2(1), 4. https://doi.org/10.1007/s44163-022-00022-8
  44. Johnston, H., Wells, R. F., Shanks, E. M., Boey, T., & Parsons, B. N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20(1), 2. https://doi.org/10.1007/s40979-024-00149-4
  45. Kapile, C. (2024). Understanding the Effectiveness of Multicultural Education in Enhancing Social Studies Learning Outcomes. West Science Social and Humanities Studies, 2(05), 716–721. https://doi.org/10.58812/wsshs.v2i05.881
  46. Kaur, D., Uslu, S., Rittichier, K. J., & Durresi, A. (2023). Trustworthy Artificial Intelligence: A Review. ACM Computing Surveys, 55(2). https://doi.org/10.1145/3491209
  47. Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y.-S., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2022). Explainable Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 3, 100074. https://doi.org/10.1016/j.caeai.2022.100074
  48. Kim, J.-H., Song, J.-S., Moon, H.-K., & Lee, M.-H. (2013). Effects of Multicultural Society Recognition and Multicultural Education Experience on Cultural Sensitivity of Middle and High School Students in Daejeon: Focusing on the Mediating Role of Multicultural Education Needs Perception. Family and Environment Research, 51(1), 107–118. https://doi.org/10.6115/khea.2013.51.1.107
  49. Kolachalama, V. B., & Garg, P. S. (2018). Machine learning and medical education. Npj Digital Medicine, 1(1), 54. https://doi.org/10.1038/s41746-018-0061-1
  50. Kurdi, G., Leo, J., Parsia, B., Sattler, U., & Al-Emari, S. (2020). A Systematic Review of Automatic Question Generation for Educational Purposes. International Journal of Artificial Intelligence in Education, 30(1), 121–204. https://doi.org/10.1007/s40593-019-00186-y
  51. Li, H., Cui, C., & Jiang, S. (2024). Strategy for improving the football teaching quality by AI and metaverse-empowered in mobile internet environment. Wireless Networks, 30(5), 4343–4352. https://doi.org/10.1007/s11276-022-03000-1
  52. Li, Z., Zhao, T., Chen, F., Hu, Y., Su, C.-Y., & Fukuda, T. (2018). Reinforcement Learning of Manipulation and Grasping Using Dynamical Movement Primitives for a Humanoidlike Mobile Manipulator. IEEE/ASME Transactions on Mechatronics, 23(1), 121–131. https://doi.org/10.1109/TMECH.2017.2717461
  53. Liakos, K., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine Learning in Agriculture: A Review. Sensors, 18(8), 2674. https://doi.org/10.3390/s18082674
  54. Mao, J., Chen, B., & Liu, J. C. (2024). Generative Artificial Intelligence in Education and Its Implications for Assessment. TechTrends, 68(1), 58–66. https://doi.org/10.1007/s11528-023-00911-4
  55. Megahed, F. M., Chen, Y.-J., Ferris, J. A., Knoth, S., & Jones-Farmer, L. A. (2024). How generative AI models such as ChatGPT can be (mis)used in SPC practice, education, and research? An exploratory study. Quality Engineering, 36(2), 287–315. https://doi.org/10.1080/08982112.2023.2206479
  56. Mitchell, M., Wu, S., Zaldivar, A., Barnes, P., Vasserman, L., Hutchinson, B., Spitzer, E., Raji, I. D., & Gebru, T. (2019). Model Cards for Model Reporting. Proceedings of the Conference on Fairness, Accountability, and Transparency, 220–229. https://doi.org/10.1145/3287560.3287596
  57. Molinillo, S., Aguilar-Illescas, R., Anaya-Sánchez, R., & Vallespín-Arán, M. (2018). Exploring the impacts of interactions, social presence and emotional engagement on active collaborative learning in a social web-based environment. Computers & Education, 123, 41–52. https://doi.org/10.1016/j.compedu.2018.04.012
  58. Nguyen, N. H., Subhan, F. B., Williams, K., & Chan, C. B. (2020). Barriers and Mitigating Strategies to Healthcare Access in Indigenous Communities of Canada: A Narrative Review. Healthcare, 8(2), 112. https://doi.org/10.3390/healthcare8020112
  59. Obrenovic, B., Gu, X., Wang, G., Godinic, D., & Jakhongirov, I. (2024). Generative AI and human–robot interaction: implications and future agenda for business, society and ethics. AI & SOCIETY. https://doi.org/10.1007/s00146-024-01889-0
  60. Olanrewaju, G. S., Adebayo, S. B., Omotosho, A. Y., & Olajide, C. F. (2021). Left behind? The effects of digital gaps on e-learning in rural secondary schools and remote communities across Nigeria during the COVID19 pandemic. International Journal of Educational Research Open, 2, 100092. https://doi.org/10.1016/j.ijedro.2021.100092
  61. Ouyang, F., & Jiao, P. (2021). Artificial intelligence in education: The three paradigms. Computers and Education: Artificial Intelligence, 2, 100020. https://doi.org/10.1016/j.caeai.2021.100020
  62. Oyebola Olusola Ayeni, Nancy Mohd Al Hamad, Onyebuchi Nneamaka Chisom, Blessing Osawaru, & Ololade Elizabeth Adewusi. (2024). AI in education: A review of personalized learning and educational technology. GSC Advanced Research and Reviews, 18(2), 261–271. https://doi.org/10.30574/gscarr.2024.18.2.0062
  63. Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S., … Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. International Journal of Surgery, 88, 105906. https://doi.org/10.1016/j.ijsu.2021.105906
  64. Pessach, D., & Shmueli, E. (2023). A Review on Fairness in Machine Learning. ACM Computing Surveys, 55(3), 1–44. https://doi.org/10.1145/3494672
  65. Poria, S., Majumder, N., Mihalcea, R., & Hovy, E. (2019). Emotion Recognition in Conversation: Research Challenges, Datasets, and Recent Advances. IEEE Access, 7, 100943–100953. https://doi.org/10.1109/ACCESS.2019.2929050
  66. Prabhuswamy, M., Tripathi, R., Vijayakumar, M., Thulasimani, T., Sundharesalingam, P., & Sampath, B. (2024). A Study on the Complex Nature of Higher Education Leadership (pp. 202–223). https://doi.org/10.4018/979-8-3693-1371-8.ch013
  67. Rahiman, H. U., & Kodikal, R. (2024). Revolutionizing education: Artificial intelligence empowered learning in higher education. Cogent Education, 11(1). https://doi.org/10.1080/2331186X.2023.2293431
  68. Rahman, M. M., & Watanobe, Y. (2023). ChatGPT for Education and Research: Opportunities, Threats, and Strategies. Applied Sciences, 13(9), 5783. https://doi.org/10.3390/app13095783
  69. Raiaan, M. A. K., Mukta, M. S. H., Fatema, K., Fahad, N. M., Sakib, S., Mim, M. M. J., Ahmad, J., Ali, M. E., & Azam, S. (2024). A Review on Large Language Models: Architectures, Applications, Taxonomies, Open Issues and Challenges. IEEE Access, 12, 26839–26874. https://doi.org/10.1109/ACCESS.2024.3365742
  70. Rawas, S. (2024). ChatGPT: Empowering lifelong learning in the digital age of higher education. Education and Information Technologies, 29(6), 6895–6908. https://doi.org/10.1007/s10639-023-12114-8
  71. Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154. https://doi.org/10.1016/j.iotcps.2023.04.003
  72. Robbyanandri Pratama, Siswo Hadi Sumantri, & Pujo Widodo. (2023). The Role Of Teachers In Implementing Multicultural Education At Taruna Nusantara High School To Enhance Social Resilience. International Journal Of Humanities Education and Social Sciences (IJHESS), 3(1). https://doi.org/10.55227/ijhess.v3i1.580
  73. Sai, S., Gaur, A., Sai, R., Chamola, V., Guizani, M., & Rodrigues, J. J. P. C. (2024). Generative AI for Transformative Healthcare: A Comprehensive Study of Emerging Models, Applications, Case Studies, and Limitations. IEEE Access, 12, 31078–31106. https://doi.org/10.1109/ACCESS.2024.3367715
  74. 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
  75. Shahnazaryan, N. H., & Shahnazaryan, G. H. (2024). Human Capital Management in the Context of Artificial Intelligence. Регион и Мир / Region and the World, 78–86. https://doi.org/10.58587/18292437-2024.1-78
  76. Sharp, M., Ak, R., & Hedberg, T. (2018). A survey of the advancing use and development of machine learning in smart manufacturing. Journal of Manufacturing Systems, 48, 170–179. https://doi.org/10.1016/j.jmsy.2018.02.004
  77. Tashtoush, M. A., Wardat, Y., Ali, R. Al, & Saleh, S. (2024). Artificial Intelligence in Education: Mathematics Teachers’ Perspectives, Practices and Challenges. Iraqi Journal for Computer Science and Mathematics, 5(1). https://doi.org/10.52866/ijcsm.2024.05.01.004
  78. Tiwari, C. K., Bhat, M. A., Khan, S. T., Subramaniam, R., & Khan, M. A. I. (2024). What drives students toward ChatGPT? An investigation of the factors influencing adoption and usage of ChatGPT. Interactive Technology and Smart Education, 21(3), 333–355. https://doi.org/10.1108/ITSE-04-2023-0061
  79. Tran, B., Xue, B., & Zhang, M. (2018). A New Representation in PSO for Discretization-Based Feature Selection. IEEE Transactions on Cybernetics, 48(6), 1733–1746. https://doi.org/10.1109/TCYB.2017.2714145
  80. Walter, Y. (2024). Embracing the future of Artificial Intelligence in the classroom: the relevance of AI literacy, prompt engineering, and critical thinking in modern education. International Journal of Educational Technology in Higher Education, 21(1), 15. https://doi.org/10.1186/s41239-024-00448-3
  81. Wartman, S. A., & Combs, C. D. (2018). Medical Education Must Move From the Information Age to the Age of Artificial Intelligence. Academic Medicine, 93(8), 1107–1109. https://doi.org/10.1097/ACM.0000000000002044
  82. Wu, M., Song, Z., & Moon, Y. B. (2019). Detecting cyber-physical attacks in CyberManufacturing systems with machine learning methods. Journal of Intelligent Manufacturing, 30(3), 1111–1123. https://doi.org/10.1007/s10845-017-1315-5
  83. Xia, Q., Chiu, T. K. F., Lee, M., Sanusi, I. T., Dai, Y., & Chai, C. S. (2022). A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education. Computers and Education, 189. https://doi.org/10.1016/j.compedu.2022.104582
  84. Yang, S. J. H., Ogata, H., Matsui, T., & Chen, N.-S. (2021). Human-centered artificial intelligence in education: Seeing the invisible through the visible. Computers and Education: Artificial Intelligence, 2, 100008. https://doi.org/10.1016/j.caeai.2021.100008
  85. Yusuf, A., Pervin, N., & Román-González, M. (2024). Generative AI and the future of higher education: a threat to academic integrity or reformation? Evidence from multicultural perspectives. International Journal of Educational Technology in Higher Education, 21(1), 21. https://doi.org/10.1186/s41239-024-00453-6
  86. 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), 39. https://doi.org/10.1186/s41239-019-0171-0
  87. Zhai, X., Chu, X., Chai, C. S., Jong, M. S. Y., Istenic, A., Spector, M., Liu, J.-B., Yuan, J., & Li, Y. (2021). A Review of Artificial Intelligence (AI) in Education from 2010 to 2020. Complexity, 2021(1). https://doi.org/10.1155/2021/8812542
  88. Zhang, P., & Tur, G. (2024). A systematic review of ChatGPT use in K‐12 education. European Journal of Education, 59(2). https://doi.org/10.1111/ejed.12599