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    Examining First Year Student Learning in Generative AI supported Information Literacy Instruction: A Scholarship of Teaching and Learning (SoTL) Study

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    Title
    Examining First Year Student Learning in Generative AI supported Information Literacy Instruction: A Scholarship of Teaching and Learning (SoTL) Study
    Author
    Ryder, Rukmal
    Date
    2026
    Subject
    Information literacy
    First-year students
    Microsoft Copilot
    Academic libraries
    AI-supported instruction
    
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    URI
    http://hdl.handle.net/20.500.13013/3901
    Abstract
    This study examines the integration of Microsoft Copilot into a single, scaffolded, 75-minute library instruction session for first-year students and evaluates its association with students’ confidence using library databases and doing research. Using anonymous pre- and post-instruction surveys, we assessed baseline comfort with AI and library databases (pre) and post-session comfort and perceived helpfulness of Copilot (post). Because responses could not be reliably matched across time points, pre–post differences were analyzed as independent samples. Mean comfort with library databases increased from 2.88 (SD = 0.77, n = 26) to 3.47 (SD = 0.96, n = 19), representing a moderate effect size (Cohen’s d ≈ 0.69). Students rated Copilot’s helpfulness highly (M = 4.00, SD = 0.47, n = 19). Findings suggest that ethical, transparent incorporation of Copilot alongside librarian-led practice may enhance first-year students’ research confidence in academic database use.
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