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Examining First Year Student Learning in Generative AI supported Information Literacy Instruction: A Scholarship of Teaching and Learning (SoTL) Study
Ryder, Rukmal Ryder, Rukmal
Ryder, Rukmal
Ryder, Rukmal
Title
Examining First Year Student Learning in Generative AI supported Information Literacy Instruction: A Scholarship of Teaching and Learning (SoTL) Study
Date
2026-01-01
Subject
Information literacy
First-year students
Microsoft Copilot
Academic libraries
AI-supported instruction
First-year students
Microsoft Copilot
Academic libraries
AI-supported instruction
Material type
Collections
Files
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.