الزامات اخلاقی به‌کارگیری هوش مصنوعی در آموزش (یک مطالعه فراترکیب)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار دانشگاه تهران، تهران

2 دانشجوی دکتری د انشگاه تهران

چکیده

مقدمه و هدف: کاربرد گسترده هوش مصنوعی در آموزش، چالش‌های اخلاقی فراوانی به دنبال داشته است. شناسایی الزامات اخلاقی به‌کارگیری هوش مصنوعی در آموزش برای مقابله با چنین چالش‌هایی اهمیت چشمگیری دارد.
روش‌شناسی پژوهش: این مطالعه با رویکرد کیفی و روش فراترکیب انجام شده است. بدین منظور از روش هفت مرحله‌ای سندولوسکی و باروسو (2007) استفاده گردید. میدان پژوهش شامل 351 سند علمی بود که پس از واکاوی و بررسی چکیده، محتوا و کیفیت یافته‌ها با کمک ابزار پریزما، 21 مقاله بر اساس ملاک‌های تعیین‌شده، جهت فراترکیب گزینش شدند. به منظور تحلیل داده‌ها از روش تحلیل مضمون براون و کلارک (2006) استفاده شده است. روایی توصیفی و تفسیری نیز مورد تایید قرار گرفتند.
یافته‌ها: یافته‌ها نشان داد که الزامات اخلاقی به‌کارگیری هوش مصنوعی در آموزش شامل الزامات اخلاقی نهادی و الزامات اخلاقی توسعه‌ای است. الزامات اخلاقی نهادی شامل اخلاق فناورانه و اخلاق سیاستگذاری و نظارت (سازمانی) است. الزامات اخلاقی توسعه‌ای نیز شامل اخلاق آموزش و یادگیری (پداگوژیک) و اخلاق انسانی (بشر) است.
بحث و نتیجه‌گیری: براساس یافته­های بدست آمده می­توان نتیجه گرفت که برای استقرار هوش مصنوعی در آموزش، ملحوظ کردن ملاحظات مختلف منجمله ملاحظات اخلاقی از اهمیت زیادی برخوردار است ولذا نتایج این مطالعه که ملاحظات اخلاقی را مورد مداقّه قرار داده است می‌تواند مورد توجه سیاست‌گذاران، مدیران آموزشی و معلمان جهت استقرار اخلاقی هوش مصنوعی در آموزش قرار گیرد تا با چالش‌های اخلاقی کاربست این فناوری مقابله شود.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Ethical Requirements for Using Artificial Intelligence in Education (A Meta-Synthesis Study)

نویسندگان [English]

  • javad Pourkarimi 1
  • Mahsa Azizi 2
1 Associate Professor of University of Tehran, Iran
2 PhD Student of Uiversity of Tehra
چکیده [English]

Background and Objective: The widespread use of artificial intelligence in education has led to many ethical challenges. Identifying the ethical requirements of using artificial intelligence in education is crucial for addressing such challenges.
Research methodology: This study was conducted with a qualitative approach and meta-synthesis method. For this purpose, the seven-step method of Sandolowski and Barroso (2007) was used. The research field included 351 scientific documents. After analyzing and examining the abstract, content, and quality of the findings using the PRISMA tool, 21 articles were selected for meta-synthesis based on the determined criteria. The content analysis method of Brown and Clark (2006) was used to analyze the data. Descriptive and interpretive validity were also confirmed.
Findings: The findings showed that the ethical requirements of using artificial intelligence in education include institutional ethical requirements and developmental ethical requirements. Institutional ethical requirements include technological ethics, policymaking, and monitoring ethics (organizational). Developmental ethical requirements also include teaching and learning ethics (pedagogical) and human ethics.
Conclusion: The results of this study may interest policymakers, educational administrators, and teachers in ethically establishing artificial intelligence in education to address the ethical challenges of applying this technology.

کلیدواژه‌ها [English]

  • Ethical requirements
  • Artificial intelligence
  • Meta-synthesis
References
Abbas, T. (2023). Ethical implications of AI in modern education: Balancing innovation and responsibility. Social Sciences Spectrum, 2(1), 51–57.
Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligencehttps://doi.org/10.1016/j.caeai.2023.100131
Airaj, M. (2024). Ethical artificial intelligence for teaching-learning in higher education. Educ. Inf. Technol., 29, 17145–17167. https://doi.org/10.1007/s10639-024-12545-x.
Akgun, S., Greenhow, C. (2022). Artificial intelligence in education: Addressing ethical challenges in K-12 settings. AI Ethics, 2, 431–440. https://doi.org/10.1007/s43681-021-00096-7
Al Dhaen, F. S. (2025). The Significance of AI Ethics and Its Implications for Higher Education: Systematic Review. Ethical Standards for Technological and Business Education Sustainability, 67–83. https://doi.org/10.1108/978-1-83608-036-720251005
Al-Omari, O., Alyousef, A., Fati, S., Shannaq, F., & Omari, A. (2025). Governance and Ethical Frameworks for AI Integration in Higher Education: Enhancing Personalized Learning and Legal Compliance. Journal of Ecohumanism4(2), 80 –. https://doi.org/10.62754/joe.v4i2.5781
Aydın, İ. (2024). Ethical Issues in Educational Technology.  Kastamonu Education Journal, 32(1), 138-158. https://doi.org/10.24106/kefdergi.1426735.
Babanoğlu, M. P., Karataş, T. Ö., & Dündar, E. (2025). Ethical considerations of AI through a socio-technical lens: insights from ELT context as a higher education system. Cogent Education12(1). https://doi.org/10.1080/2331186X.2025.2488546
Berson, I. R., & Berson, M. J. (2024). Fragments of the past: The intersection of AI, historical imagery, and early childhood creativity. Future in Educational Research, 2(4), 403–421. https://doi.org/10.1002/fer3.46
Berson, I. R., Berson, M. J., Luo, W., & He, H. (2023). Intelligence augmentation in early childhood education: A multimodal creative inquiry approach. Communications in Computer and Information Science, 1831, 756–763. https://doi.org/10.1007/978-3-031-36336-8_116
Berson, I.R., Berson, M.J., & Luo, W. (2025). Innovating responsibly: ethical considerations for AI in early childhood education. AI Brain Child, 1, 2. https://doi.org/10.1007/s44436-025-00003-5
Biagini, G. (2025). Towards an AI-Literate Future: A Systematic Literature Review Exploring Education, Ethics, and Applications. Int J Artif Intell Educ. https://doi.org/10.1007/s40593-025-00466-w
Borenstein, J., Howard, A. (2021). Emerging challenges in AI and the need for AI ethics education. AI Ethics, 1, 61–65. https://doi.org/10.1007/s43681-020-00002-7
Bouhouita-Guermech, S., Gogognon, P., & Bélisle-Pipon, J. C. (2023). Specific challenges posed by artificial intelligence in research ethics. Frontiers in artificial intelligence6, 1149082. https://doi.org/10.3389/frai.2023.1149082
Brandao, P.R. (2025). The Impact of Artificial Intelligence on Modern Society. AI, 6, 190. https://doi.org/10.3390/ai6080190 
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
Chan, C.K.Y. (2023). A comprehensive AI policy education framework for university teaching and learning. Int J Educ Technol High Educ, 20, 38. https://doi.org/10.1186/s41239-023-00408-3
Chen, Z., Chen, C., Yang, G., He, X., Chi, X., Zeng, Z., & Chen, X. (2024). Research integrity in the era of artificial intelligence: Challenges and responses. Medicine, 103(27), e38811. https://doi.org/10.1097/MD.0000000000038811
Cheong, B. C. (2024). Transparency and accountability in AI systems: Safeguarding wellbeing in the age of algorithmic decision-making. Frontiers in Human Dynamics, 6, 1421273. https://doi.org/10.3389/fhumd.2024.1421273
Corrêa, N. K., Galvão, C., Santos, J. W., Del Pino, C., Pinto, E. P., Barbosa, C., Massmann, D., Mambrini, R., Galvão, L., Terem, E., & De Oliveira, N. (2023). Worldwide AI ethics: A review of 200 guidelines and recommendations for AI governance. Patterns, 4(10), 100857. https://doi.org/10.1016/j.patter.2023.100857
Dabis, A., Csáki, C. (2024). AI and ethics: Investigating the first policy responses of higher education institutions to the challenge of generative AI. Humanit Soc Sci Commun, 11, 1006. https://doi.org/10.1057/s41599-024-03526-z
Du, H., Sun, Y., Jiang, H., Islam, A.Y., & Gu, X. (2024). Exploring the effects of AI literacy in teacher learning: an empirical study. Humanities and Social Sciences Communications, 11, 1–10. https://doi.org/10.1057/s41599-024-03101-6
Farheen, S., Cheema, A. A., Ullah, R. S., & Bandeali, M. M. (2025). Equity and bias in AI Educational Tools: A Critical Examination of algorithmic decision-making in classrooms. The Critical Review of Social Sciences Studies3(3), 67–85. https://doi.org/10.59075/zqmnpa62
Feldman-Maggor, Y., Cukurova, M., Kent, C. et al.  (2025). The Impact of Explainable AI on Teachers’ Trust and Acceptance of AI EdTech Recommendations: The Power of Domain-specific Explanations. Int J Artif Intell Educ. https://doi.org/10.1007/s40593-025-00486-6
Ferhataj, A., Memaj, F., Sahatcija, R., Ora, A., & Koka, E. (2025). Ethical concerns in AI development: analyzing students’ perspectives on robotics and society. Journal of Information, Communication and Ethics in Society23(2), 165-187. https://doi.org/10.1108/JICES-08-2024-0111
Foltynek, T., Bjelobaba, S., Glendinning, I. et al. (2023). ENAI Recommendations on the ethical use of Artificial Intelligence in Education. Int J Educ Integr 19, 12. https://doi.org/10.1007/s40979-023-00133-4
Funa, A. A., & Gabay, R. A. E. (2025). Policy guidelines and recommendations on AI use in teaching and learning: A meta-synthesis study. Social Sciences & Humanities Open, 11, 101221. https://doi.org/10.1016/j.ssaho.2024.101221
Gandhi, S., Ahmed, M. S., Huang, L., Behl, A., & Manrai, A. K. (2025). AI’s Impact on Academic Research Integrity: Guidelines from the Editors of Journal of Global Marketing. Journal of Global Marketing38(3), 189–192. https://doi.org/10.1080/08911762.2025.2488060
Gao, D. K., Haverly, A., Mittal, S., Wu, J., & Chen, J. (2024). AI ethics: a bibliometric analysis, critical issues, and key gaps. International Journal of Business Analytics (IJBAN)11(1), 1–19. https://doi.org/10.4018/IJBAN.338367
Giannakos, M., Horn, M., & Cukurova, M. (2025). Learning, design, and technology in the age of AI. Behaviour & Information Technology44(5), 883–887. https://doi.org/10.1080/0144929X.2025.2469394
Gilbert, C., & Gilbert, M. A. (2024). The convergence of artificial intelligence and privacy: Navigating innovation with ethical considerations. International Journal of Scientific Research and Modern Technology (IJSRMT). 399, 9–17. https://doi.org/10.38124/ijsrmt.v3i9.45
Gilpin, L. H., Bau, D., Yuan, B. Z., Bajwa, A., Specter, M., & Kagal, L. (2018, October). Explaining explanations: An overview of interpretability of machine learning. In 2018, the IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA) (pp. 80–89). IEEE.‏ https://doi.org/10.1109/DSAA.2018.00018
Goktas, P. (2024). Ethics, transparency, and explainability in generative AI decision-making systems: a comprehensive bibliometric study. Journal of Decision Systems, 1–29. https://doi.org/10.1080/12460125.2024.2410042
Gouseti, A., James, F., Fallin, L., & Burden, K. (2024). The ethics of using AI in K-12 education: a systematic literature review. Technology, Pedagogy and Education34(2), 161–182. https://doi.org/10.1080/1475939X.2024.2428601
Güneş, A., & Kaban, A. L. (2025). A Delphi Study on Ethical Challenges and Ensuring Academic Integrity Regarding AI Research in Higher Education. Higher Education Quarterly, 79(4), e70057. https://doi.org/10.1111/hequ.70057
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S., Santos, O., Rodrigo, M., Cukurova, M., Bittencourt, I., & Koedinger, K. (2021). Ethics of AI in Education: Towards a Community-Wide Framework. International Journal of Artificial Intelligence in Education, 32, 504–526. https://doi.org/10.1007/s40593-021-00239-1.
Huang, L. (2023). Ethics of Artificial Intelligence in Education: Student Privacy and Data Protection. Science Insights Education Frontiers16(2), 2577–2587. https://doi.org/10.15354/sief.23.re202
Huo, B., Wang, B., & Li, Z. (2024). How to deal with technological turbulence for improving innovation performance. Technology Analysis & Strategic Management36(3), 549–562. https://doi.org/10.1080/09537325.2022.2042510.
Idowu, J. A. (2024). Debiasing education algorithms. International Journal of Artificial Intelligence in Education34(4), 1510-1540. https://doi.org/10.1007/s40593-023-00389-4
Idowu, J. A., Koshiyama, A. S., & Treleaven, P. (2024). Investigating algorithmic bias in student progress monitoring. Computers and Education: Artificial Intelligence, 7, 100267. https://doi.org/10.1016/j.caeai.2024.100267
Jang, Y., Choi, S., Jung, H., & Kim, H. (2022). Practical early prediction of students’ performance using machine learning and eXplainable AI. Education and Information Technologies, 27(9), 12855–12889. https://doi.org/10.1007/s10639-022-11120-6
Kaddouri, M., Mhamdi, K., Chniete, I., Marhraoui, M., Khaldi, M., & Jmad, S. (2025). Adopting AI in education: Technical challenges and ethical constraints. In Fostering Inclusive Education with AI and Emerging Technologies (pp. 25-72). IGI Global. https://doi.org/10.4018/979-8-3693-7255-5.ch002
Kamińska, D., Zwoliński, G., Laska-Leśniewicz, A., Raposo, R., Vairinhos, M., Pereira, E., Urem, F., Ljubić Hinić, M., Haamer, R. E., & Anbarjafari, G. (2023). Augmented Reality: Current and New Trends in Education. Electronics12(16), 3531. https://doi.org/10.3390/electronics12163531.
Kaminski, M. E. (2018). The right to explanation, explained. Berkeley Technol. Law J. 34. https://doi.org/10.2139/ssrn.3196985
Karpouzis, K. (2024). Artificial intelligence in education: Ethical considerations and insights from Ancient Greek philosophy. In Proceedings of the 13th Hellenic Conference on Artificial Intelligence (pp. 1-7). https://arxiv.org/abs/2409.15296
Khan, S., Mazhar, T., Shahzad, T. et al. Harnessing AI for sustainable higher education: ethical considerations, operational efficiency, and future directions. Discov Sustain, 6, 23 (2025). https://doi.org/10.1007/s43621-025-00809-6
Khanifar, H., Moslemi, N. (2023). Principles and Foundations of Qualitative Research Methods, Tehran: Negah Danesh. (in Persian).
Khosravi, H., Shum, S. B., Chen, G., Conati, C., Tsai, Y., Kay, J., Knight, S., Martinez-Maldonado, R., Sadiq, S., & Gašević, D. (2021). Explainable Artificial Intelligence in education. Computers and Education: Artificial Intelligence, 3, 100074. https://doi.org/10.1016/j.caeai.2022.100074
Kovari, A. (2025). Ethical use of ChatGPT in education—Best practices to combat AI-induced plagiarism. Frontiers in Education, 9, 1465703. https://doi.org/10.3389/feduc.2024.1465703
Lazăr, A. M., Repanovici, A., Popa, D., Ionas, D. G., & Dobrescu, A. I. (2024). Ethical Principles in AI Use for Assessment: Exploring Students’ Perspectives on Ethical Principles in Academic Publishing. Education Sciences14(11), 1239. https://doi.org/10.3390/educsci14111239
Lendvai, G. F., & Gosztonyi, G. (2025). Algorithmic Bias as a Core Legal Dilemma in the Age of Artificial Intelligence: Conceptual Basis and the Current State of Regulation. Laws, 14(3), 41. https://doi.org/10.3390/laws14030041
Leong, W. Y., & Zhang, J. B. (2025). Ethical design of AI for education and learning systems. ASM Science Journal20(1), 1–9. https://doi.org/10.32802/asmscj.2025.1917
Li, Y., Li, Y., Wei, M., & Li, G. (2024). Innovation and Challenges of Artificial Intelligence Technology in Personalized Healthcare. Scientific Reports, 14(1), 1-9. https://doi.org/10.1038/s41598-024-70073-7
Liao, Q. V., Gruen, D., & Miller, S. (2020). Questioning the AI: informing design practices for explainable AI user experiences. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1–15).‏ https://doi.org/10.1145/3313831.3376590
Mennella, C., Maniscalco, U., Pietro, G. D., & Esposito, M. (2024). Ethical and regulatory challenges of AI technologies in healthcare: A narrative review. Heliyon, 10(4), e26297. https://doi.org/10.1016/j.heliyon.2024.e26297
Mishara, P. (2024). The Ethical Implications of AI in Education: Privacy, Bias, and Accountability. J. Inform. Educ. Res4, 3550. https://doi.org/10.52783/jier.v4i2.1827
Mujtaba, B. G. (2025). Human-AI Intersection: Understanding the Challenges, Opportunities, and Governance Protocols for a Changing Data-Driven Digital World. Business Ethics and Leadership, 9(1), 109‒126. http://doi.org/10.61093/bel .
Nguyen, A., Ngo, H.N., Hong, Y., Dang, B., & Nguyen, B. T. (2023). Ethical principles for artificial intelligence in education. Educ Inf Technol 28, 4221–4241. https://doi.org/10.1007/s10639-022-11316-w
Nguyen, K.V. (2025). The Use of Generative AI Tools in Higher Education: Ethical and Pedagogical Principles. J Acad Ethics, 23, 1435–1455. https://doi.org/10.1007/s10805-025-09607-1
Nye, E., Melendez‐Torres, G. J., & Bonell, C. (2016). Origins, methods, and advances in qualitative meta‐synthesis. Review of Education4(1), 57–79. https://doi.org/10.1002/rev3.3065
Oncioiu I, Bularca AR. (2025). Artificial Intelligence Governance in Higher Education: The Role of Knowledge-Based Strategies in Fostering Legal Awareness and Ethical Artificial Intelligence Literacy. Societies. 15(6), 144. https://doi.org/10.3390/soc15060144
Oye, E., Frank, E., & Owen, J. (2024). Ethical considerations in AI-driven education. https://www.researchgate.net/publication/387275777_Ethical_Considerations_in_AI Driven_Education
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., McGuinness, L. A., … Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ (Clinical research ed.)372, n71. https://doi.org/10.1136/bmj.n71
Pasipamire, N., & Muroyiwa, A. (2024). Navigating algorithm bias in AI: Ensuring fairness and trust in Africa. Frontiers in Research Metrics and Analytics, 9, 1486600. https://doi.org/10.3389/frma.2024.1486600
Pellicelli, M. (2023). Managing the supply chain: Technologies for digitalization solutions. The Digital Transformation of Supply Chain Management, 101–152. https://doi.org/10.1016/B978-0-323-85532-7.00002-5
Polat, M., Karataş, İ. H., & Varol, N. (2025). Ethical Artificial Intelligence (AI) in Educational Leadership: Literature Review and Bibliometric Analysis. Leadership and Policy in Schools, 24(1), 46-76. https://doi.org/10.1080/15700763.2024.2412204
Poornesh, M. (2024). Through a Teacher’s Lens: Combating Bias in AI-Powered Education for a Just Future. The Clearing House: A Journal of Educational Strategies, Issues and Ideas97(4), 119–124. https://doi.org/10.1080/00098655.2024.2393153
Porayska-Pomsta, K., Holmes, W., & Nemorin, S. (2023). The ethics of AI in education. In Handbook of Artificial Intelligence in Education (pp. 571-604). Edward Elgar Publishing.
Pourkarimi, J. & Azizi, M. (2025). Ethical-behavioral competencies of Managers in turbulent environments (A metasynthesis study). Strategy for Culture17(67), 127–154. https://doi.org/10.22034/jsfc.2025.466056.2685 (in Persian).
Pourkarimi, J. & Azizi, M. (2025). Organizational Strategies in Turbulent Environments: A Meta-Synthesis Study. Journal of Business Management17(2), 454–480. https://doi.org/10.22059/jibm.2024.375005.4774 (in Persian).
Pourkarimi, J., Abili, K. & Azizi, M. (2025). Educational Managers' Competencies in Turbulent Environments (A Meta-Synthesis Study). Interdisciplinary Journal of Management Studies18(3), 565–581. https://doi.org/10.22059/ijms.2025.385092.677146.
Radanliev, P. (2025). AI Ethics: Integrating Transparency, Fairness, and Privacy in AI Development. Applied Artificial Intelligence39(1). https://doi.org/10.1080/08839514.2025.2463722
Rajabiyan Dehzireh, M. (2024). Identifying the challenges and capabilities of artificial intelligence in teaching and learning by providing solutions. Technology of Education Journal (TEJ)18(4), 921–950. https://doi.org/10.22061/tej.2024.10777.3058 (in Persian).
Ramnani, S. (2024). Exploring Ethical Considerations of Artificial Intelligence in Educational Settings: An Examination of Bias, Privacy, and Accountability. International Journal of Novel Research and Development (IJNRD)9(2), 2456–4184. http://doi.one/10.1729/Journal.37869
Rao, G. T., & Suhasini, N. (2025). Integrating Artificial Intelligence in Higher Education to Enhance Teaching and Learning. Computer Applications in Engineering Education, 33(6), e70085. https://doi.org/10.1002/cae.70085
Reiss, M.J. (2021). The use of AI in education: Practicalities and ethical considerations. London Review of Education, 19 (1), 5, 1–14. https://doi.org/10.14324/LRE.19.1.05
Ryan, M., & Stahl, B. C. (2021). Artificial Intelligence Ethics Guidelines for Developers and Users: Clarifying Their Content and Normative Implications. Journal of Information, Communication and Ethics in Society19(1), 61–86. https://doi.org/10.1108/JICES-12-2019-0138?urlappend=%3Futm_source%3Dresearchgate
Saidin, N. F., Halim, N. D. A., & Yahaya, N. (2015). A review of research on augmented reality in education: Advantages and applications. International education studies, 8(13), 1–8. https://doi.org/10.5539/ies.v8n13p1
Salloum, S.A. (2024). AI Perils in Education: Exploring Ethical Concerns. In: Al-Marzouqi, A., Salloum, S.A., Al-Saidat, M., Aburayya, A., Gupta, B. (eds) Artificial Intelligence in Education: The Power and Dangers of ChatGPT in the Classroom. Studies in Big Data, vol 144. Springer, Cham. https://doi.org/10.1007/978-3-031-52280-2_43
Sanchez, T. W., Brenman, M., & Ye, X. (2024). The Ethical Concerns of Artificial Intelligence in Urban Planning. Journal of the American Planning Association91(2), 294–307. https://doi.org/10.1080/01944363.2024.2355305
Sandelowski, M., Barroso, J., & Voils, C. I. (2007). Using qualitative metasummary to synthesize qualitative and quantitative descriptive findings. Research in nursing & health30(1), 99–111. https://doi.org/10.1002/nur.20176
Şenocak, D., Bozkurt, A., & Koçdar, S. (2024). Exploring the Ethical Principles for the Implementation of Artificial Intelligence in Education: Towards a Future Agenda. In R. Sharma & A. Bozkurt (Eds.), Transforming Education with Generative AI: Prompt Engineering and Synthetic Content Creation (pp. 200-213). IGI Global. https://doi.org/10.4018/979-8-3693-1351-0.ch010
Siau, K., & Wang, W. (2020). Artificial intelligence (AI) ethics: ethics of AI and ethical AI. Journal of Database Management (JDM)31(2), 74-87. https://doi.org/10.4018/JDM.2020040105
Stahl, B.C. (2023). Embedding responsibility in intelligent systems: from AI ethics to responsible AI ecosystems. Sci Rep, 13, 7586. https://doi.org/10.1038/s41598-023-34622-w
Tang, L. & Su, Y.S. (2024). Ethical Implications and Principles of Using Artificial Intelligence Models in the Classroom: A Systematic Literature Review, International Journal of Interactive Multimedia and Artificial Intelligence, vol. 8, issue Special issue on Generative Artificial Intelligence in Education, 5, 25–36. https://doi.org/10.9781/ijimai.2024.02.010
Tong, A., Flemming, K., McInnes, E. et al. (2012). Enhancing transparency in reporting the synthesis of qualitative research: ENTREQ. BMC Med Res Methodol 12, 181. https://doi.org/10.1186/1471-2288-12-181
Varsik, S. & L. Vosberg (2024). The potential impact of Artificial Intelligence on equity and inclusion in education. OECD Artificial Intelligence Papers, No. 23, OECD Publishing, Paris, https://doi.org/10.1787/15df715b-en.
Verma, S., & Garg, N. (2023). The trend and future of techno-ethics: a bibliometric analysis of three decades. Libr. Hi Tech, 42, 1579-1600. https://doi.org/10.1108/lht-10-2022-0477.
Vieriu, A. M., & Petrea, G. (2025). The Impact of Artificial Intelligence (AI) on Students’ Academic Development. Education Sciences, 15(3), 343. https://doi.org/10.3390/educsci15030343
Walsh, D., & Downe, S. (2005). Meta-synthesis method for qualitative research: a literature review. Journal of Advanced Nursing50(2), 204–211. https://doi.org/10.1111/j.1365-2648.2005.03380.x
Yadav, S. (2025). Leveraging AI to Enhance Teaching and Learning in Education (pp. 211–238). igi global. https://doi.org/10.4018/979-8-3693-7863-2.ch008
Yambal, S., & Waykar, Y. A. (2025). Future of Education Using Adaptive AI, Intelligent Systems, and Ethical Challenges. In Effective Instructional Design Informed by AI (pp. 171–202). IGI Global Scientific Publishing.
Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students' cognitive abilities: A systematic review. Smart Learning Environments, 11(1), 1-37. https://doi.org/10.1186/s40561-024-00316-7