{"id":1139162,"date":"2025-05-13T23:08:40","date_gmt":"2025-05-14T06:08:40","guid":{"rendered":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/?post_type=msr-research-item&#038;p=1139162"},"modified":"2025-11-24T20:21:08","modified_gmt":"2025-11-25T04:21:08","slug":"the-new-calculator-practices-norms-and-implications-of-generative-ai-in-higher-education","status":"publish","type":"msr-research-item","link":"https:\/\/cm-edgetun.pages.dev\/en-us\/research\/publication\/the-new-calculator-practices-norms-and-implications-of-generative-ai-in-higher-education\/","title":{"rendered":"The New Calculator? Practices, Norms, and Implications of Generative AI in Higher Education"},"content":{"rendered":"<p>Generative AI (GenAI) has introduced myriad opportunities and challenges for higher education. Anticipating this potential transformation requires understanding students&#8217; contextualised practices and norms around GenAI. We conducted semi-structured interviews with 26 students and 11 educators from diverse departments across two universities. Grounded in Strong Structuration Theory, we find diversity in students&#8217; uses and motivations for GenAI. Occurring in the context of unclear university guidelines, institutional fixation on plagiarism, and inconsistent educator communication, students&#8217; practices are informed by unspoken rules around appropriate use, GenAI limitations and reliance strategies, and consideration of agency and skills. Perceived impacts include changes in confidence, and concerns about skill development, relationships with educators, and plagiarism. Both groups envision changes in universities&#8217; attitude to GenAI, responsible use training, assessments, and integration of GenAI into education. We discuss socio-technical implications in terms of current and anticipated changes in the external and internal structures that contextualise students&#8217; GenAI use.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Generative AI (GenAI) has introduced myriad opportunities and challenges for higher education. Anticipating this potential transformation requires understanding students&#8217; contextualised practices and norms around GenAI. We conducted semi-structured interviews with 26 students and 11 educators from diverse departments across two universities. Grounded in Strong Structuration Theory, we find diversity in students&#8217; uses and motivations for [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"arxiv","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Auste Simkute, Viktor Kewenig, Abigail Sellen, Sean Rintel, and Lev Tankelevitch. 2025. The New Calculator? 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