阿根廷vs墨西哥竞猜
 library logo
    • login
    view item 
    •   knowledge commons home
    • electronic theses and dissertations
    • electronic theses and dissertations from 2009
    • view item
    •   knowledge commons home
    • electronic theses and dissertations
    • electronic theses and dissertations from 2009
    • view item
    javascript is disabled for your browser. some features of this site may not work without it.
    quick search

    browse

    all of knowledge commonscommunities & collectionsby issue dateauthorstitlessubjectsdisciplineadvisorcommittee memberthis collectionby issue dateauthorstitlessubjectsdisciplineadvisorcommittee member

    my account

    login

    policies, procedures, and guidelines: are universities effectively ensuring ai (academic integrity) in the era of generative ai?

    thumbnail
    view/open
    nagpalh2024m-1a.pdf (1.040mb)
    date
    2024
    author
    nagpal, himanshi
    metadata
    show full item record
    abstract
    the objective of this study was to analyze generative ai guidelines and policies at canadian universities, examining how these universities are ensuring academic integrity in the face of challenges posed by using generative ai tools in academic work. focusing on assessment redesign, ai-content citation, and ai-detection, the study employed qualitative document analysis of policies and guidelines from the top twenty canadian universities according to times higher education world rankings. this purposive sampling strategy, focused on leading institutions from different provinces, aimed to provide a representative overview of best practices and emerging trends in generative ai policy and guideline development. the analysis revealed both commonalities and differences in institutional approaches. while universities generally emphasize transparency through documentation, updated academic integrity policies, and instructor autonomy in ai use, they differ in their approaches to ai detection tools, as well as ai acknowledgment and citation. these results show canadian universities' varied strategies to address the complexities of generative ai in academic environments. the study identifies key recommendations for instructors, 世界杯2022赛程表淘汰赛 , researchers, and staff, offering a foundation for developing comprehensive generative ai guidelines at the university level.
    uri
    https://knowledgecommons.lakeheadu.ca/handle/2453/5385
    collections
    • electronic theses and dissertations from 2009 [1612]

    阿根廷vs墨西哥竞猜 library
    contact us | send feedback

     

     


    阿根廷vs墨西哥竞猜 library
    contact us | send feedback