Ethical Awareness of Educators Toward AI Usage: A Study on Bias, Privacy, and Responsible Implementation

Wardani Wardani; Mutia Velli Agusta

doi:10.58524/aidie.v1i2.87

Authors

Wardani Wardani UIN Jurai Siwo Lampung Author
Mutia Velli Agusta UIN Raden Intan Lampung Author

DOI:

https://doi.org/10.58524/aidie.v1i2.87

Keywords:

AI ethics, educators’ awareness, algorithmic bias, data privacy, responsible implementation

Abstract

The increasing use of artificial intelligence in education has intensified concerns regarding algorithmic bias, data privacy, and the ethical responsibilities of educators, yet little is known about how educators understand and respond to these ethical challenges. This quantitative study examined the extent to which educators’ awareness of bias and privacy predicts their commitment to responsible AI implementation. A total of 214 educators participated in a cross-sectional survey that included validated measures of bias awareness, privacy awareness, and responsible implementation. Data were collected online and analyzed using descriptive statistics, correlations, and multiple regression. Results showed that both bias awareness and privacy awareness were significant predictors of responsible AI use, with the model explaining 46% of the variance. Educators reported moderate to high awareness across ethical domains, and effect sizes indicated meaningful relationships among variables. These findings highlight the central role of ethical literacy in shaping how educators adopt and regulate AI tools in classroom contexts. The study contributes a data-driven understanding of ethical awareness in AI-mediated education and underscores the need for professional development and policy frameworks that equip educators to navigate emerging ethical challenges.

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References

Abbasnejad, B., Soltani, S., Taghizadeh, F., & Zare, A. (2025). Developing a multilevel framework for AI integration in technical and engineering higher education: insights from bibliometric analysis and ethnographic research. Interactive Technology and Smart Education, December. https://doi.org/10.1108/ITSE-12-2024-0314

Adams, C., Pente, P., Lemermeyer, G., & Rockwell, G. (2023). Ethical principles for artificial intelligence in K-12 education. Computers and Education: Artificial Intelligence, 4, 4221–4241. https://doi.org/10.1016/j.caeai.2023.100131

Akbarighatar, P. (2025). Operationalizing responsible AI principles through responsible AI capabilities. AI and Ethics, 5(2), 1787–1801. https://doi.org/10.1007/s43681-024-00524-4

Al-Abdullatif, A. M. (2025). Auditing AI Literacy Competency in K–12 Education: The Role of Awareness, Ethics, Evaluation, and Use in Human–Machine Cooperation. Systems, 13(6). https://doi.org/10.3390/systems13060490

Angela, L., & Erandaru, E. (2022). STUDI PERBANDINGAN TEORI DAN PRAKTEK PROSES PERANCANGAN UI/UX di ARYANNA. Jurnal DKV Adiwarna, 1.

Avsec, S., & Rupnik, D. (2025). From Transformative Agency to AI Literacy: Profiling Slovenian Technical High School Students Through the Five Big Ideas Lens. Systems, 13(7), 1–57. https://doi.org/10.3390/systems13070562

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

Bandara, R. J., Biswas, K., Akter, S., Shafique, S., & Rahman, M. (2025). Addressing Algorithmic Bias in AI-Driven HRM Systems: Implications for Strategic HRM Effectiveness. Human Resource Management Journal, Chen 2023, 1047–1063. https://doi.org/10.1111/1748-8583.12609

Berson, I. R., Berson, M. J., & Luo, W. (2025). Innovating responsibly: ethical considerations for AI in early childhood education. AI, Brain and Child, 1(1), 1–15. 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. In International Journal of Artificial Intelligence in Education (Issue 0123456789). Springer New York. https://doi.org/10.1007/s40593-025-00466-w

Bulathwela, S., Pérez-Ortiz, M., Holloway, C., Cukurova, M., & Shawe-Taylor, J. (2024). Artificial Intelligence Alone Will Not Democratise Education: On Educational Inequality, Techno-Solutionism and Inclusive Tools. Sustainability (Switzerland), 16(2), 1–20. https://doi.org/10.3390/su16020781

Chedrawi, C., Haddad, G., Tarhini, A., Osta, S., & Kazoun, N. (2025). Exploring the impact of responsible AI usage on users’ behavioral intentions. Journal of Innovation and Knowledge, 10(6), 100813. https://doi.org/10.1016/j.jik.2025.100813

Chee, H., Ahn, S., & Lee, J. (2025). A Competency Framework for AI Literacy: Variations by Different Learner Groups and an Implied Learning Pathway. British Journal of Educational Technology, 56(5), 2146–2182. https://doi.org/10.1111/bjet.13556

Choopani, A., Arabloo, J., Arkian, S. H., & Vatankhah, S. (2024). Identification of the contextual factors influencing the successful implementation of in-service training policies for the health workforce in Iran. BMC Medical Education, 24(1). https://doi.org/10.1186/s12909-024-06336-8

Ding, X., Swatdikun, T., Chen, X., & Mahadi, N. (2025). Exploring the Role of Corporate Financial Strategy on Sustainability Performance: The Intervention of Corporate Culture of Automobile Companies in Guangxi, China. Sustainability, 17(19), 8610. https://doi.org/10.3390/su17198610

Esteves, A. M. (2024). A Code of Ethics for the social performance profession. Extractive Industries and Society, 20(November), 101573. https://doi.org/10.1016/j.exis.2024.101573

Gauthier, A., Rizvi, S., Cukurova, M., & Mavrikis, M. (2022). Is it time we get real? A systematic review of the potential of data-driven technologies to address teachers’ implicit biases. Frontiers in Artificial Intelligence, 5. https://doi.org/10.3389/frai.2022.994967

Ghasemaghaei, M., & Kordzadeh, N. (2025). Ethics in the Age of Algorithms: Unravelling the Impact of Algorithmic Unfairness on Data Analytics Recommendation Acceptance. Information Systems Journal, 35(4), 1166–1197. https://doi.org/10.1111/isj.12572

Goncalves, M., Hu, Y., Aliagas, I., & Cerdá, L. M. (2024). Neuromarketing algorithms’ consumer privacy and ethical considerations: challenges and opportunities. Cogent Business and Management, 11(1). https://doi.org/10.1080/23311975.2024.2333063

Hammerschmidt, T., Hafner, A., Stolz, K., Passlack, N., Posegga, O., & Gerholz, K. H. (2025). A Review of How Different Views on Ethics Shape Perceptions of Morality and Responsibility within AI Transformation. In Information Systems Frontiers (Issue 0123456789). Springer US. https://doi.org/10.1007/s10796-025-10596-0

Huerta, M. V., Sajadi, S., Schibelius, L., Ryan, O. J., & Fisher, M. (2024). An exploration of psychological safety and conflict in first-year engineering student teams. Journal of Engineering Education, 113(3), 635–666. https://doi.org/10.1002/jee.20608

Jedličková, A. (2025). Ethical approaches in designing autonomous and intelligent systems: a comprehensive survey towards responsible development. AI and Society, 40(4), 2703–2716. https://doi.org/10.1007/s00146-024-02040-9

Leslie, D., & Perini, A. M. (2024). Future Shock: Generative AI and the International AI Policy and Governance Crisis. Harvard Data Science Review, Special Issue 5. https://doi.org/10.1162/99608f92.88b4cc98

Micheluzzi, V., Cascio, A. Lo, Capoferri, M., Piredda, M., & Sandri, E. (2025). Beverage Consumption Patterns in Spanish and Italian Adults : A Comparative Study. 1–22.

Moussa, M. A., & Ismail Al-Nersh, H. I. (2025). Data analysis errors and limitations in educational research. In International Journal of Research in Educational Sciences (IJRES) (Vol. 8, Issue 2).

Mouta, A., Torrecilla-Sánchez, E. M., & Pinto-Llorente, A. M. (2025). Comprehensive professional learning for teacher agency in addressing ethical challenges of AIED: Insights from educational design research. In Education and Information Technologies (Vol. 30, Issue 3). Springer US. https://doi.org/10.1007/s10639-024-12946-y

Mutimukwe, C., Viberg, O., McGrath, C., & Cerratto-Pargman, T. (2025). Privacy in online proctoring systems in higher education: stakeholders’ perceptions, awareness and responsibility. Journal of Computing in Higher Education. https://doi.org/10.1007/s12528-025-09461-5

Nah, S., Luo, J., & Joo, J. (2024). Mapping Scholarship on Algorithmic Bias: Conceptualization, Empirical Results, and Ethical Concerns. International Journal of Communication, 18, 548–569.

Neubauer, C., Pollard, K. A., Benbow, K., Rabin, A. H., Forster, D. E., Nguyen, R., Kochert, J., Bonsignore, E., & Campbell, S. (2024). Measuring and Predicting Technical Fluency: How Knowledge, Skills, Abilities, and Other Behaviors Can Contribute to Technological Savviness.

Oyetade, K., & Zuva, T. (2025). Advancing Equitable Education with Inclusive AI to Mitigate Bias and Enhance Teacher Literacy. Educational Process: International Journal, 14. https://doi.org/10.22521/edupij.2025.14.87

Pangrazio, L., & Bunn, A. (2024). Assessing the privacy of digital products in Australian schools: Protecting the digital rights of children and young people. Computers and Education Open, 6, 100187. https://doi.org/10.1016/j.caeo.2024.100187

Revesai, Z. (2025). Generative AI dependency: the emerging academic crisis and its impact on student performance—a case study of a university in Zimbabwe. Cogent Education, 12(1). https://doi.org/10.1080/2331186X.2025.2549787