"Smarter but Not Wiser": A Transdisciplinary CFA-GRM Simulation Pipeline for Mapping Human–GenAI Interaction

Background The integration of Generative AI (GenAI) in higher education creates a paradox between technical efficiency and cognitive depth. Current institutional responses rely more on fragmented oversight than on ecology- and process-oriented assessment. There is a lack of diagnostic tools to map psychometric thresholds when strategic cognitive shifts transition into functional dependence. Methods We present a simulation-based methodological framework using the Tripartite Confirmatory Factor Analysis–Graded Response Model (CFA-GRM). Grounded in the cognitive-affective-conative tripartite model, this study uses a Monte Carlo simulation (N = 1,000) to demonstrate how latent interaction pathways can be structurally validated and how item parameters can be calibrated against a pre-specified diagnostic threshold ( θ  ≈ 0.5), with a replication study to establish parameter recovery. Results Across 200 replications at each of N  = 1,000 and N  = 300, all 400 converged with admissible solutions and recovered the generating parameters with maximum absolute relative bias of 0.040; interval coverage met conventional criteria for 11 of 15 parameter groups at N  = 1,000 and 8 of 15 at N  = 300. In the single illustrative dataset, the fit is near-perfect (robust CFI = 0.995, RMSEA = 0.010) because the generating and estimated models coincide, a property of the design rather than evidence for the model. Test information peaks at θ  ≈ 0.07–0.22, not at the proposed threshold of θ  ≈ 0.5. Furthermore, we introduce a Transdisciplinary Calibration Matrix that translates these psychometric signals into context-specific pedagogical interventions across four epistemic layers, in line with SDG 4. Conclusions This study does not claim empirical generalization. It provides a methodological blueprint, a recovered parameter set, and a shared diagnostic language for future empirical work on the ethical and adaptive integration of GenAI in higher education, aligned with SDG 4.