Tang (2026) — PhD Dissertation, University of Missouri.
Synthesis
This dissertation presents an integrated AI framework for campus well-being spanning prevention (improving feedback collection) and intervention (advancing mental health detection). It represents an important application of llm and generative-ai technologies to student-experience that extends beyond academic learning to holistic student support in higher-ed.
On the prevention side, TigerGPT — a personalized survey chatbot grounded in conversational design and engagement theory — achieved 75% usability and 81% satisfaction, demonstrating that AI-mediated feedback collection can improve on traditional survey instruments. AURA, an adaptive follow-up question framework using reinforcement learning, dynamically selects question types (validate, specify, reflect, probe) to deepen responses, achieving a +0.12 mean quality gain (p=0.044, d=0.66).
On the intervention side, PsychoGPT provides explainable mental health assessment built on DSM-5 and PHQ-8 guidelines — a affective-computing application that prioritizes clinical grounding and interpretability over black-box classification. The Stacked Multi-Model Reasoning (SMMR) architecture reduces hallucination risk by layering expert models: early layers handle localized subtasks while later layers reconcile findings, outperforming single-model solutions on the DAIC-WOZ benchmark.
The integrated framework — where adaptive survey insights flow into specialized mental health detection models — represents a novel edtech-platform architecture for campus well-being. For the administrator perspective, this work provides a concrete roadmap for universities seeking to deploy AI tools that monitor student satisfaction and detect mental health risks — areas where many institutions currently lack effective methods.
Related Pages
- affective-text-wearable-student-health — Empirical evidence: ultra-brief affective text enriches wearable physiological data
- higher-ed — Primary context for campus well-being applications
- student-experience — Holistic student support beyond academics
- llm — Core technology powering TigerGPT and PsychoGPT
- affective-computing — Related domain for emotion/well-being AI applications
- edtech-platform — Integrated AI platform architecture in education
- administrator — Institutional adoption perspective
- ai-literacy — Student and staff understanding of AI well-being tools
- hallucination-risk — Addressed through the SMMR architecture
Citation
APA: Tang, J. (2026). New AI-Driven Tools for Enhancing Campus Well-being: A Prevention and Intervention Approach [PhD Dissertation, University of Missouri]. arXiv:2605.10804.