我（不再）信任你！——学生使用LLM对高等教育中讲师—学生信任的影响
I don't trust you (anymore)! -- The effect of students' LLM use on Lecturer-Student-Trust in Higher Education
AI总结：
本研究通过基于23名有效受访者的定量调查和PLS-SEM分析，考察学生使用LLM如何经由信息公正、程序公正影响团队信任与预期绩效，发现使用透明度是提升团队信任的关键。
摘要：
信任在涵盖教学与研究方面的讲师—学生协作中发挥着关键作用。大型语言模型（LLM）出现在Open AI的ChatGPT等平台中，加之其成本效益和高质量结果，促使大学生迅速采用这些工具。然而，对讲师而言，辨别学生真实输入与LLM生成输出构成了一项挑战。这一困境危及讲师与学生之间的信任关系，并可能影响大学的下游活动，尤其是协作研究计划。尽管已有研究尝试为学生使用LLM制定指南，但在高等教育中仍缺乏一个对讲师和学生互利的清晰框架。本研究回应以下研究问题：学生使用LLM如何影响信息公正和程序公正，进而影响团队信任与预期团队绩效？在方法上，我们采用了基于构念的定量调查，并运用结构方程模型（PLS-SEM）技术进行评估，以考察这些构念之间的潜在关系。基于来自Ndejje University的23名有效受访者，我们的研究结果表明，讲师并不那么担心LLM使用本身的公平性，而是更关注学生使用LLM的透明度；这种透明度会对团队信任产生显著的正向影响。本研究为关于在教育中整合和监管LLM及后续模型的全球讨论作出贡献。我们建议，相关指南应支持LLM使用，同时在讲师—学生协作中强制要求透明度，以培育团队信任和绩效。本研究为制定相关政策提供了有价值的见解，使教育中能够合乎伦理且透明地使用LLM，从而确保协作学习环境的有效性。
英文摘要：
Trust plays a pivotal role in Lecturer-Student-Collaboration, encompassing teaching and research aspects. The advent of Large Language Models (LLMs) in platforms like Open AI's ChatGPT, coupled with their cost-effectiveness and high-quality results, has led to their rapid adoption among university students. However, discerning genuine student input from LLM-generated output poses a challenge for lecturers. This dilemma jeopardizes the trust relationship between lecturers and students, potentially impacting university downstream activities, particularly collaborative research initiatives. Despite attempts to establish guidelines for student LLM use, a clear framework mutually beneficial for lecturers and students in higher education remains elusive. This study addresses the research question: How does the use of LLMs by students impact Informational and Procedural Justice, influencing Team Trust and Expected Team Performance? Methodically, we applied a quantitative construct-based survey, evaluated using techniques of Structural Equation Modelling (PLS- SEM) to examine potential relationships among these constructs. Our findings based on 23 valid respondents from Ndejje University indicate that lecturers are less concerned about the fairness of LLM use per se but are more focused on the transparency of student utilization, which significantly influences Team Trust positively. This research contributes to the global discourse on integrating and regulating LLMs and subsequent models in education. We propose that guidelines should support LLM use while enforcing transparency in Lecturer-Student- Collaboration to foster Team Trust and Performance. The study contributes valuable insights for shaping policies enabling ethical and transparent LLMs usage in education to ensure effectiveness of collaborative learning environments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
