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A Learning Agreement for Generative AI Use in University Courses: A Pilot Study

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Title: A Learning Agreement for Generative AI Use in University Courses: A Pilot Study
Language: English
Authors: Marc Beardsley (ORCID 0000-0002-3874-0739), Patricia Santos (ORCID 0000-0002-7337-2388), Ishari Amarasinghe (ORCID 0000-0003-2960-4804), Emily Theophilou (ORCID 0000-0001-8290-9944), Milica Vujovic (ORCID 0000-0003-0963-7182), Davinia Hernández-Leo (ORCID 0000-0003-0548-7455)
Source: Innovations in Education and Teaching International. 2025 62(5):1574-1592.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 19
Publication Date: 2025
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Foreign Countries, Universities, Engineering, College Freshmen, Artificial Intelligence, Pilot Projects, Ethics, Technology Uses in Education, Performance Contracts
Geographic Terms: Spain
DOI: 10.1080/14703297.2025.2535444
ISSN: 1470-3297
1470-3300
Abstract: The rapid development of Generative AI (GenAI) tools presents challenges for their ethical and responsible use. This pilot study examines student learning agreements as a governance tool for GenAI use in a first-year engineering course. These agreements included ethical and social considerations that students accepted if they chose to use GenAI. Pre- and post-course surveys and group assignments were analysed. Most students responded positively to the approach, though only one of the ten groups using GenAI explicitly acknowledged its limitations, as required by the agreement. Thematic analysis of student feedback highlighted the need for clearer language, more specific examples and opportunities to revisit the agreement during the course. Overall, the findings suggest that learning agreements can serve as a flexible mechanism to support student autonomy and ethical decision-making when engaging with GenAI tools, helping bridge the gap between rapidly evolving technologies and responsible academic use.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1483679
Database: ERIC
FullText Text:
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  Data: A Learning Agreement for Generative AI Use in University Courses: A Pilot Study
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  Data: <searchLink fieldCode="AR" term="%22Marc+Beardsley%22">Marc Beardsley</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-3874-0739">0000-0002-3874-0739</externalLink>)<br /><searchLink fieldCode="AR" term="%22Patricia+Santos%22">Patricia Santos</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0002-7337-2388">0000-0002-7337-2388</externalLink>)<br /><searchLink fieldCode="AR" term="%22Ishari+Amarasinghe%22">Ishari Amarasinghe</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-2960-4804">0000-0003-2960-4804</externalLink>)<br /><searchLink fieldCode="AR" term="%22Emily+Theophilou%22">Emily Theophilou</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8290-9944">0000-0001-8290-9944</externalLink>)<br /><searchLink fieldCode="AR" term="%22Milica+Vujovic%22">Milica Vujovic</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0963-7182">0000-0003-0963-7182</externalLink>)<br /><searchLink fieldCode="AR" term="%22Davinia+Hernández-Leo%22">Davinia Hernández-Leo</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-0548-7455">0000-0003-0548-7455</externalLink>)
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  Data: <searchLink fieldCode="SO" term="%22Innovations+in+Education+and+Teaching+International%22"><i>Innovations in Education and Teaching International</i></searchLink>. 2025 62(5):1574-1592.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Universities%22">Universities</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering%22">Engineering</searchLink><br /><searchLink fieldCode="DE" term="%22College+Freshmen%22">College Freshmen</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+Intelligence%22">Artificial Intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Pilot+Projects%22">Pilot Projects</searchLink><br /><searchLink fieldCode="DE" term="%22Ethics%22">Ethics</searchLink><br /><searchLink fieldCode="DE" term="%22Technology+Uses+in+Education%22">Technology Uses in Education</searchLink><br /><searchLink fieldCode="DE" term="%22Performance+Contracts%22">Performance Contracts</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Spain%22">Spain</searchLink>
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  Data: 10.1080/14703297.2025.2535444
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  Data: 1470-3297<br />1470-3300
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The rapid development of Generative AI (GenAI) tools presents challenges for their ethical and responsible use. This pilot study examines student learning agreements as a governance tool for GenAI use in a first-year engineering course. These agreements included ethical and social considerations that students accepted if they chose to use GenAI. Pre- and post-course surveys and group assignments were analysed. Most students responded positively to the approach, though only one of the ten groups using GenAI explicitly acknowledged its limitations, as required by the agreement. Thematic analysis of student feedback highlighted the need for clearer language, more specific examples and opportunities to revisit the agreement during the course. Overall, the findings suggest that learning agreements can serve as a flexible mechanism to support student autonomy and ethical decision-making when engaging with GenAI tools, helping bridge the gap between rapidly evolving technologies and responsible academic use.
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  Data: 2025
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  Label: Accession Number
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  Data: EJ1483679
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