Campus AI vs. Commercial AI: Comparing How Students and Employees Perceive their University's LLM Chatbot vs. ChatGPT
Leon Hannig, Annika Bush, Meltem Aksoy, Tim Trappen, Steffen Becker, Greta Ontrup
Abstract
As the use of Large Language Model (LLM) chatbots by students and researchers becomes more prevalent, universities are pressed to develop AI strategies. One strategy that many universities pursue is to customize pre-trained LLM-as-a-service (LLMaaS) chatbots. While most studies on LLMaaS chatbots prioritize technical adaptations, these systems are often mainly characterized by user-salient front-end customizations, e. g., interface changes. Yet, no existing studies have examined how users perceive such systems compared to commercial LLM chatbots. In a field study, we investigate how students and employees (N = 526) at a German university perceive and use their institution’s customized LLMaaS chatbot compared to ChatGPT. Participants using both systems (n = 116) reported greater trust, higher perceived privacy, and less perceived hallucinations with their university’s customized LLMaaS chatbot compared to ChatGPT. We discuss implications for research on users’ trustworthiness assessment process, and offer guidance for the design and deployment of LLMaaS chatbots.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Builds on6
- Deep Learning with Differential PrivacyMartín Abadi, Andy Chu, Ian J. Goodfellow, H. Brendan McMahan et al.CCS 2016 · 7,620 citations
- To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-makingZana Buçinca, Maja Barbara Malaya, Krzysztof Z. GajosCSCW 2021 · 962 citations
- Out of Context: Investigating the Bias and Fairness Concerns of "Artificial Intelligence as a Service"Kornel Lewicki, Michelle Seng Ah Lee, Jennifer Cobbe, Jatinder SinghCHI 2023 · 31 citations
- 'I'm Categorizing LLM as a Productivity Tool': Examining Ethics of LLM Use in HCI Research PracticesShivani Kapania, Ruiyi Wang, Toby Jia-Jun Li, Tianshi Li et al.CSCW 2025 · 31 citations
- The Janus Interface: How Fine-Tuning in Large Language Models Amplifies the Privacy RisksXiaoyi Chen, Siyuan Tang, Rui Zhu, Shijun Yan et al.CCS 2024 · 18 citations
Related papers
- Understanding the Effect of Risk Perception on the Acceptance and Use of Large Language Models Among University StudentsMichael T. Rücker, Carolin Büchting, Thomas KoschCSCW 2025 · 4 citations
- CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language ModelsJuhye Ha, Hyeon Jeon, DaEun Han, Jinwook Seo et al.CHI 2024 · 66 citations
- Privacy and Trust vs. Utility: Adoption of Commercial vs. Institutional AI assistants Among University UsersYuting Yang, Zixin Wang, Rongjun Ma, Florian SchaubCHI 2026 · 1 citation
- Exploring the Impact of Avatar Representations in AI Chatbot Tutors on Learning ExperiencesChek Tien Tan, Indriyati Atmosukarto, Budianto Tandianus, Songjia Shen et al.CHI 2025 · 16 citations
- Understanding the Role of Large Language Models in Personalizing and Scaffolding Strategies to Combat Academic ProcrastinationAnanya Bhattacharjee, Yuchen Zeng, Sarah Yi Xu, Dana Kulzhabayeva et al.CHI 2024 · 39 citations
