Artificial intelligence technologies and ethics in educational processes: solution suggestions and results
DOI:
https://doi.org/10.24310/ijtei.102.2024.19806Keywords:
artificial intelligence, artificial intelligence ethics, artificial intelligence in educationAbstract
Artificial intelligence is a technology used to imitate the human-like thinking and decision-making abilities of computer systems. This technology enables computers to perform complex tasks such as data analysis, learning, problem solving and decision making. It is used in the field of education as well as in every field. While the use of artificial intelligence in the field of education provides advantages such as providing personalized learning experiences to students, providing teachers with intuition about student performance and developing educational materials, the ethical dimension should not be ignored. Therefore, the aim of this study is to produce solutions to ethical problems in the teaching and evaluation processes of artificial intelligence technologies in education. Qualitative research method was used in this study. It has adopted the phenomenological research approach among qualitative research methods. The concept of phenomenon is also the ethics of artificial intelligence. The working group consists of teachers, educational technologists and academicians. When selecting the working group, it was taken into consideration that there were teachers who use artificial intelligence applications in education and academics and technologists working in this field. Document analysis and focus group interviews were used as data collection tools. Content analysis was performed on the data obtained. According to the results of the study, ethical problems encountered with the use of artificial intelligence in education were identified and solution suggestions were offered.
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Alzahrani, A. (2022). A systematic review of artificial intelligence in education in the Arab world. Amazonia Investiga, 11(54), 293–305. https://doi.org/10.34069/AI/2022.54.06.28
Anyoha, R. (2017). The history of artificial intelligence. Science in the News, 28.
Baltacı, A. (2017). Miles-Huberman model in qualitative data analysis. Ahi Evran University Journal of Institute of Social Sciences, 3(1), 1-14.
Baxter, P., & Jack, S. (2008). Qualitative case study methodology: Study design and implementation for novice researchers. The qualitative report, 13(4), 544-559. https://doi.org/10.46743/2160-3715/2008.1573
Baz, F. Ç. & Denizer, E. (2018, 23-25 November). An overview of research on the use of artificial intelligence in the field of education in Turkey: a content analysis study. Cemil Meriç - 10th Social Sciences and Sports Congress, Hatay.
Binns, R. (2018). Fairness in machine learning: Lessons from political philosophy. Proceedings of the 2018 Conference on Fairness, Accountability, and Transparency, 81, 149-159.
Bryman, A. (2016). Social research methods. Oxford university press.
Chen, L., Chen, P., & Lin, Z. (2020, January 1). Artificial Intelligence in Education: A Review. Institute of Electrical and Electronics Engineers, 8, 75264-75278. https://doi.org/10.46793/TIE22.223K
Crawford, K. (2021). The Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press.
Creswell, J. W., & Creswell, J. D. (2017). Research design: Qualitative, quantitative, and mixed methods approaches. Sage publications.
Creswell, J.W. (2016). Qualitative research methods. Qualitative research and research design according to five approaches. Ankara: Siyasal Yayın Dağıtım.
Duggan, S. (2020). AI in Education: Change at the speed of learning. UNESCO Institute for Information Technologies in Education.
Educause. (2018). The NMC Horizon Report: 2018 higher education edition. Educause. https://library.educause.edu/~/media/files/library/2018/8/2018horizonreport.pdf
Educause. (2023). 2023 EDUCAUSE horizon report: teaching and learning edition. Educause. https://library.educause.edu/-/media/files/library/2023/4/2023hrteachinglearning.pdf
Evans, P. C., & Gawer, A. (2016). The rise of the platform enterprise: A global survey. The center for global enterprise.
Floridi, L., & Cowls, J. (2019). A unified framework of five principles for AI in society. Harvard Data Science Review, 1(1). https://doi.org/10.1162/99608f92.8cd550d1
Güçlü, İ. (2019). Qualitative research methods in social sciences. Nika Publishing House.
Harry, A. (2023) Role of AI in education, Interdiciplinary Journal and Humanity (INJURITY), 2(3), 260-268. https://doi.org/10.58631/injurity.v2i3.52
Islam, M. A. (2023). AI & Blockchain as sustainable teaching and learning tools to cope with the 4IR. Cornell University.
Kalayci Onac, A., Cetin, M., Sevik, H., Orman, P., Karci, A., & Gonullu Sutcuoglu, G. (2021). Rethinking the campus transportation network in the scope of ecological design principles: case study of Izmir Kâtip Çelebi University Çiğli Campus. Environmental Science and Pollution Research, 28(36), 50847-50866. https://doi.org/10.1007/s11356-021-14299-2
Ma, X., & Jiang, C. (2023). On the Ethical Risks of Artificial Intelligence Applications in Education and Its Avoidance Strategies. Journal of Education, Humanities and Social Sciences, 14, 354-359. https://doi.org/10.54097/ehss.v14i.8868
Mello, R. F., Freitas, E. L. S. X., Pereira, F. D., Cabral, L. D. S., Tedesco, P., & Ramalho, G. (2023). Education in the age of Generative AI: Context and Recent Developments. Cornell University.
Merriam, S. B., & Grenier, R. S. (Eds.). (2019). Qualitative research in practice: Examples for discussion and analysis. John Wiley & Sons.
Müller, V. C. (2020). Ethics of artificial intelligence and robotics. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy. Stanford University.
Nabiyev, V., and Erümit, A. K., (2020). Prediction with machine learning. Pegem.
OECD (2021), OECD Digital Education Outlook 2021: pushing the frontiers with artificial intelligence, blockchain and robots, OECD. https://doi.org/10.1787/589b283f-en
Olga, A., Tzirides., Saini, A. S., Zapata, G. C., Searsmith, D., Cope, B., Kalantzis, M., Castro, V., Kourkoulou, T., Jones, J. H., Silva, R. A. D., Whiting, J., & Kastania, N. P. (2023). Generative AI: Implications and Applications for Education. Cornell University.
Regan, P. M., & Jesse, J. (2019). Ethical challenges of edtech, big data and personalized learning: Twenty-first century student sorting and tracking. Ethics and Information Technology, 21, 167-179. https://doi.org/10.1007/s10676-018-9492-2
Sullivan, C., & Forrester, M. A. (Eds.). (2018). Doing qualitative research in psychology: A practical guide. Sage.
Tapalova, O., & Zhiyenbayeva, N. (2022). Artificial intelligence in education: AIEd for personalized learning pathways. Electronic Journal of e-Learning, 20(5), 639-653. https://doi.org/10.34190/ejel.20.5.2597
Tiwari, R. (2023). The integration of AI and machine learning in education and its potential to personalize and improve student learning experiences. International Journal of Scientific Research in Engineering and Management, 7(2), 1. https://doi.org/10.55041/IJSREM17645
Wang, Y., Hu, M., Zhou, Y., Li, Q., Yao, N., Zhai, G., & Yang, X. (2020). Unobtrusive and automatic classification of multiple people's abnormal respiratory patterns in real time using deep neural network and depth camera. IEEE Internet of Things Journal, 7(9), 8559-8571. https://doi.org/10.1109/JIOT.2020.2991456
Whittlestone, J., Nyrup, R., Alexandrova, A., & Cave, S. (2019). The role and limits of principles in AI ethics: Towards a focus on tensions. Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 195-200.
Williamson, B., & Eynon, R. (2020). Historical threads, missing links, and future directions in AI in education. Learning, Media and Technology, 45(3), 223-235. https://doi.org/10.1080/17439884.2020.1798995
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), 1-27. https://doi.org/10.1186/s41239-019-0171-0
Zhu, Y. (2021). Research on English teaching of professional skilled talents training based on artificial intelligence. IOS Press, 1-12.
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