# TigerGPT: A New AI Chatbot for Adaptive Campus Climate Surveys

arXiv: https://arxiv.org/abs/2504.13925 · HTML: https://mlsanity.com/paper/2504.13925/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Apr 2025.

## Built on by (most cited first, 1 of 1)

- [AquaSentinel: Next-Generation AI System Integrating Sensor Networks for Urban Underground Water Pipeline Anomaly Detection via Collaborative MoE-LLM Agent Architecture](https://mlsanity.com/paper/2511.15870/) (2025)

## Abstract (arXiv)

Campus climate surveys play a pivotal role in capturing how students, faculty, and staff experience university life, yet traditional methods frequently suffer from low participation and minimal follow-up. We present TigerGPT, a new AI chatbot that generates adaptive, context-aware dialogues enriched with visual elements. Through real-time follow-up prompts, empathetic messaging, and flexible topic selection, TigerGPT elicits more in-depth feedback compared to traditional static survey forms. Based on established principles of conversational design, the chatbot employs empathetic cues, bolded questions, and user-driven topic selection. It retains some role-based efficiency (e.g., collecting user role through quick clicks) but goes beyond static scripts by employing GenAI adaptiveness. In a pilot study with undergraduate students, we collected both quantitative metrics (e.g., satisfaction ratings) and qualitative insights (e.g., written comments). Most participants described TigerGPT as engaging and user-friendly; about half preferred it over conventional surveys, attributing this preference to its personalized conversation flow and supportive tone. The findings indicate that an AI survey chatbot is promising in gaining deeper insight into campus climate.