Generative AI as the 'Third Eye' of Academic Advising: Ethical, Pedagogical, and Methodological Perspectives in Research Supervision

The rapid advancement of generative artificial intelligence (GenAI) has reshaped the landscape of research supervision in higher education, raising critical ethical, pedagogical, and methodological questions. This mixed-methods study, titled Generative AI as the “Third Eye” of Academic Advising: Ethical, Pedagogical, and Methodological Perspectives in Research Supervision, investigated how higher education research advisers integrate GenAI tools into the supervision of student research. Employing a convergent parallel mixed-methods design, the study gathered data from 30 research advisers across various academic disciplines in a private higher education institution in Laguna, Philippines. The quantitative component utilized a validated 41-item, four-point Likert scale questionnaire designed to measure the extent to which GenAI influences ethical standards, pedagogical practices, methodological decisions, and perceptions of authenticity and originality. The qualitative phase, on the other hand, involved semi-structured interviews with purposively selected participants to explore their lived experiences, ethical reflections, and policy perspectives regarding GenAI use. Quantitative results revealed that advisers uphold ethical principles, adopt transformative pedagogical practices, and integrate GenAI tools into methodological decision-making to a great extent (M = 3.54). Qualitative findings supported these results, generating themes such as enhanced efficiency and precision, heightened ethical vigilance, challenges in verifying originality and authorship, and the continued importance of human judgment in AI-assisted supervision. Despite these advancements, issues related to student overreliance, citation transparency, and unverifiable references were identified as persistent challenges. The study culminates in the development of a Proposed Institutional Policy Framework on the Ethical Use of Generative AI in Research Supervision, advocating disclosure protocols, AI literacy training, and verification mechanisms. This framework positions GenAI as a “third eye” that enhances rather than replaces human discernment. Overall, the study contributes actionable insights for policymakers, educators, and institutions, ensuring that AI-driven innovation aligns with ethical integrity, academic rigor, and responsible research mentorship.