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Purpose

This case study explored graduate students’ uses and attitudes toward generative artificial intelligence (GenAI) for academic purposes at an iSchool.

Design/methodology/approach

Data on students’ demographics, GenAI tools, types and frequencies of use, attitudes toward GenAI and resources available to support GenAI use were collected through a questionnaire and focus groups. The data were analyzed using descriptive statistics and content analysis methods.

Findings

More than half of the participants frequently utilize GenAI tools for various academic tasks, primarily for brainstorming and writing, and credit GenAI with improving their learning or introducing them to new ideas. Findings indicate that GenAI is filling institutional or emotional gaps when students feel overwhelmed, unsupported or unsure of their abilities. Students who use GenAI regularly see its strengths as a supportive tool, but they also recognize and work around its limitations. GenAI received mixed feedback on its ability to enhance engagement or creativity, with many participants expressing concerns about potential adverse effects on their creativity, public image and self-esteem. Students felt uncertain about the appropriate academic uses of GenAI and did not feel adequately supported by their institution or instructors. One-third of participants reported not using GenAI regularly or frequently for academic tasks.

Research limitations/implications

It advances both information science and the learning sciences by providing empirical and theoretical insight into how graduate students integrate GenAI into academic work amid uncertainty and institutional, temporal and affective constraints.

Practical implications

The study offers practical recommendations for how institutions can foster critical, informed and responsible engagement with AI technologies.

Originality/value

The study explored the iSchool students’ perspectives on the adoption of GenAI for academic work. Data were collected, anonymized and analyzed by student peers, minimizing social desirability bias. While the majority of students use GenAI, they felt bad about it and did not trust the outputs. The study contributes to information and learning sciences by proposing paths for both theoretical and practical improvements in the integration of GenAI into the student learning environment. Gaining insight into iSchool student experiences and the challenges they face contributes meaningfully to the ongoing discourse on preparing the next generation of interdisciplinary information professionals.

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