The Shift in Feedback Loops: Exploring Generative AI-Augmented Supervisory Discourse in Indonesian Doctoral Education - Sahril Nur; Geminastiti Sakkir; Auliyanti Sahril Nurfadhilah (Journal of Excellence in English Language Education, 2026)
This research investigates the transformation of doctoral supervisory discourse from dyadic to triadic interactions through Generative Artificial Intelligence (GenAI) in Indonesia. Utilizing a qualitative case study and Computer-Mediated Discourse Analysis (CMDA) of ten supervisory triads, the study examines how AI-augmented loops influence Scholarly Dignity, well-being, and persistence. By synthesizing the PERMA and HOPE models with the indigenous philosophy, findings reveal that GenAI functions as a "resilience scaffold." It fosters positive emotions and provides diverse cognitive pathways to academic goals, shifting the supervisor’s role toward epistemological mentorship. However, the study identifies risks of voice homogenization and "epistemological hollowing." Consequently, the Resilient Triadic Loop (RTL) model is proposed to harmonize algorithmic efficiency with human wisdom and metacognitive agency. The study concludes that institutional policies must move beyond detection toward a "metacognitive mentorship" framework to ensure the authentic scholarly voice remains central in an automated era.