Trust in Generative AI among students: An Exploratory Study

October 07, 2023 ยท Declared Dead ยท ๐Ÿ› Technical Symposium on Computer Science Education

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Authors Matin Amoozadeh, David Daniels, Daye Nam, Aayush Kumar, Stella Chen, Michael Hilton, Sruti Srinivasa Ragavan, Mohammad Amin Alipour arXiv ID 2310.04631 Category cs.HC: Human-Computer Interaction Citations 107 Venue Technical Symposium on Computer Science Education Last Checked 2 months ago
Abstract
Generative artificial systems (GenAI) have experienced exponential growth in the past couple of years. These systems offer exciting capabilities, such as generating programs, that students can well utilize for their learning. Among many dimensions that might affect the effective adoption of GenAI, in this paper, we investigate students' \textit{trust}. Trust in GenAI influences the extent to which students adopt GenAI, in turn affecting their learning. In this study, we surveyed 253 students at two large universities to understand how much they trust \genai tools and their feedback on how GenAI impacts their performance in CS courses. Our results show that students have different levels of trust in GenAI. We also observe different levels of confidence and motivation, highlighting the need for further understanding of factors impacting trust.
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