University students have begun to use Artificial Intelligence (AI) in many different ways in their undergraduate education, some beneficial to their learning, and some simply expedient to completing assignments with as little work as possible. This exploratory qualitative study examines how undergraduate students used AI in a large General Education course on sustainability and technology at a research university in the United States in 2023. Thirty-nine students documented their use of AI in their final course project, which involved analyzing conceptual networks connecting core sustainability concepts. Through iterative qualitative coding, we identified key patterns in students’ AI use, including higher-order writing tasks (understanding complex topics, finding evidence), lower-order writing tasks (revising, editing, proofreading), and other learning activities (efficiency enhancement, independent research). Students primarily used AI to improve communication of their original ideas, though some leveraged it for more complex tasks like finding evidence and developing arguments. Many students expressed skepticism about AI-generated content and emphasized maintaining their intellectual independence. While some viewed AI as vital for improving their work, others explicitly distinguished between AI-assisted editing and their original thinking. This analysis provides insight into how students navigate AI use when it is explicitly permitted in coursework, with implications for effectively integrating AI into higher education to support student learning.
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Use of AI-Generated Visual Media in Interviews to Understand Power Differentials in Gender, Romantic, and Sexual Minority Students
This work-in-progress briefly outlines the theoretical background, methods, and preliminary results of a qualitative study conducted with gender, romantic, and sexual minority (GRSM) students immersed in higher education spaces. We elaborate on the efficacy of our innovative qualitative methodologies through the use of AI-human art-making interactions during our interviews, which helped to produce richer qualitative data from our participants. Our methodology was constructed using a Foucauldian theoretical framework to inform the framework of this study, focusing explicitly on GRSM students’ experiences with power in higher education and when using technology, as well as the ways in which they resist power through the use of technology and AI-generated visual media.
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- Award ID(s):
- 1830730
- PAR ID:
- 10280230
- Date Published:
- Journal Name:
- IEEE Frontiers in Education
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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