Ethical Horizons in AI-Driven Educational Research

Abstract

This chapter discusses the ethical problems around applying artificial intelligence (AI) to educational research. With Transformative Learning Theory and Technological Pedagogical Content Knowledge (TPACK) as its conceptual foundations, it explores the impact of AI on data privacy, bias, transparency, and accountability. The qualitative research conducted in a private university in Selangor, Malaysia, includes semi-structured interviews with lecturers and students about the ethics and the use of AI in responsible ways. There are four main themes: Data Privacy Issues, Bias and Fairness, Transparency and Accountability, and Responsible and Ethical Use of AI. Codes and themes are written with NVivo software. The results emphasise the need for ethical oversight such as informed consent, digital literacy training, and human-centred ways to avoid overreliance on AI. Limitations include situation-dependent attention and bias of participant self-report. Its ramifications require cross-discipline cooperation, moral policy-making and holistic training to make AI use in a well-controlled way to boost learning and preserve ethics. The result emphasises that AI is a transformative force for learning. Still, such an investment it should be undertaken with uncompromising ethical commitment so that the technology can complement rather than supersede the human component in education.

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