Survey of Library Science Faculty: Impact of AI on Library Science Education
Description
This comprehensive study offers an in-depth look at how library science educators are integrating artificial intelligence (AI) into their curricula, their attitudes toward AI, and the evolving landscape of academic integrity and policy in the age of AI.
What’s Inside the Report
The survey draws on responses from faculty across a range of institution types, academic ranks, and demographic backgrounds. Readers will find:
Detailed data tables and subgroup analyses
Open-ended faculty perspectives on AI policy
Trends in AI detection and academic integrity
Faculty attitudes toward curriculum changes
Breakdowns by institution, rank, age, gender, and more
Five Key Findings
AI Conversancy Is Widely Valued:
Two-thirds of faculty rate it “very” or “extremely” important for students to be conversant in AI applications, with the strongest consensus at BA-level institutions and private colleges1.
Policy Clarity Is Lacking:
While AI is seen as important, only one-third of faculty say rules for student use of AI are “very” or “extremely” clear. The most common response is “somewhat clear,” with notable ambiguity at BA-level institutions1.
Conditional Permission Is the Norm:
Most faculty allow AI for support tasks (idea generation, structure, grammar) but require disclosure/citation and prohibit full content generation. Policies vary by course, with some outright bans and a minority fully encouraging AI use1.
Academic Integrity Concerns:
Faculty estimate that a median of 10% of students use AI to cheat, but the average is higher (24%), with some subgroups reporting rates up to 100%. Perceived cheating is highest among adjuncts, males, and mid-enrollment schools1.
Detection Tools Are Common:
Nearly half of faculty have used AI or detection applications to assess student work, with higher usage among those at MA/Doctoral institutions, private colleges, and those with heavier teaching loads1.
What’s Inside the Report
The survey draws on responses from faculty across a range of institution types, academic ranks, and demographic backgrounds. Readers will find:
Detailed data tables and subgroup analyses
Open-ended faculty perspectives on AI policy
Trends in AI detection and academic integrity
Faculty attitudes toward curriculum changes
Breakdowns by institution, rank, age, gender, and more
Five Key Findings
AI Conversancy Is Widely Valued:
Two-thirds of faculty rate it “very” or “extremely” important for students to be conversant in AI applications, with the strongest consensus at BA-level institutions and private colleges1.
Policy Clarity Is Lacking:
While AI is seen as important, only one-third of faculty say rules for student use of AI are “very” or “extremely” clear. The most common response is “somewhat clear,” with notable ambiguity at BA-level institutions1.
Conditional Permission Is the Norm:
Most faculty allow AI for support tasks (idea generation, structure, grammar) but require disclosure/citation and prohibit full content generation. Policies vary by course, with some outright bans and a minority fully encouraging AI use1.
Academic Integrity Concerns:
Faculty estimate that a median of 10% of students use AI to cheat, but the average is higher (24%), with some subgroups reporting rates up to 100%. Perceived cheating is highest among adjuncts, males, and mid-enrollment schools1.
Detection Tools Are Common:
Nearly half of faculty have used AI or detection applications to assess student work, with higher usage among those at MA/Doctoral institutions, private colleges, and those with heavier teaching loads1.
Table of Contents
45 Pages
- Table 1.1 How important do you believe it is for your students to be conversant in the use of artificial intelligence application?
- Table 2.1 In your view how clearly defined are the rules on how students should be able to use artificial intelligence applications in your classes?3.1 In any given semester, about what percentage of your students do you believe cheat or in some way try to attain an unfair or unattributed advantage through undisclosed use of AI?
- Table 4.1 Have you ever used AI itself, or an application designed to detect AI use, to assess the use of AI in papers or other work done by your students?
- Table 5.1 Which phrase best summarizes your personal attitude towards how (or if) AI applications should be incorporated into the curriculum in your field?
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