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The Normalization of Unease: The Case Study of GenAI Use by iSchool Students

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Title: The Normalization of Unease: The Case Study of GenAI Use by iSchool Students
Language: English
Authors: Irene Lopatovska, Conor Mack, Ellen Connors, Penghao Zhu, Nina Keller, Simran Kaur, Merlyn Koonamparampath, Mikala Everett, Zoe Zapata, Pom Giordano, Jeffrey Yang, May Kim, Nikhil Shetty
Source: Information and Learning Sciences. 2026 127(3-4):170-194.
Availability: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
Peer Reviewed: Y
Page Count: 25
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Artificial Intelligence, Information Science, Technology Uses in Education, Student Behavior, Student Attitudes, Graduate Students, Library Education, Library Science, Library Schools, Technology Integration
Geographic Terms: New York (New York)
DOI: 10.1108/ILS-08-2025-0125
ISSN: 2398-5348
2398-5356
Abstract: 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.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1507137
Database: ERIC
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  Data: Emerald Publishing Limited. Howard House, Wagon Lane, Bingley, West Yorkshire, BD16 1WA, UK. Tel: +44-1274-777700; Fax: +44-1274-785201; e-mail: emerald@emeraldinsight.com; Web site: http://www.emerald.com/insight
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  Data: 10.1108/ILS-08-2025-0125
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– Name: Abstract
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  Data: 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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