Survey of Computer Science Faculty: Impact of AI on Computer Science Curriculum
Description
This comprehensive study offers an in-depth look at how artificial intelligence is reshaping computer science education, drawing on responses from faculty across a diverse range of institutions. The report provides actionable insights for educators, administrators, and policymakers seeking to understand current trends, challenges, and opportunities in AI curriculum development.
What’s Inside the Report?
The report features:
Detailed survey results from computer science faculty at colleges and universities of varying sizes and types
Analysis of attitudes toward AI integration in curriculum
Subgroup breakdowns by institution type, faculty rank, age, gender, and scholarly focus
Open-ended commentary on curriculum changes and future directions
Data tables, charts, and verbatim responses
Five Key Findings:
Majority Support for Interdisciplinary AI Training:\ Over half of respondents (50.72%) agree that their department should offer internal workshops to train faculty and PhD candidates in fields outside computer science in AI, with 17.39% strongly agreeing and 33.33% agreeing. Only 10.15% opposed this idea.
Departments Feel “On Par” with Peers in AI Coding Education:\ Most faculty (53.62%) believe their department is “about where our peers are” in helping students learn to code with AI and use AI tools. However, more respondents say their department is behind (20.29%) than ahead (8.70%).
Mixed Institutional Effort to Promote AI Courses for Non-CS Disciplines:\ Just under a third (31.88%) report that their university has made “a great deal” or “a lot” of effort to push the CS department to offer AI courses for other disciplines, while 26.08% say there has been “a little” or “none at all” .
Responsibility for Teaching AI to Non-CS Students Is Divided:\ The most popular choice for who should teach basic AI courses to non-CS students is the computer science department (37.68%), followed by the disciplines requiring such training (24.64%). A significant portion (28.99%) did not respond, indicating uncertainty or disagreement.
Faculty Call for More Practical, Applied, and Interdisciplinary Curriculum: Open-ended responses reveal a strong desire for curricula that emphasize hands-on AI and machine learning, responsible AI practices, and interdisciplinary collaboration. Many advocate for integrating AI into programming education and updating curricula to reflect current industry practices, while some express concern about AI’s growing dominance.
What’s Inside the Report?
The report features:
Detailed survey results from computer science faculty at colleges and universities of varying sizes and types
Analysis of attitudes toward AI integration in curriculum
Subgroup breakdowns by institution type, faculty rank, age, gender, and scholarly focus
Open-ended commentary on curriculum changes and future directions
Data tables, charts, and verbatim responses
Five Key Findings:
Majority Support for Interdisciplinary AI Training:\ Over half of respondents (50.72%) agree that their department should offer internal workshops to train faculty and PhD candidates in fields outside computer science in AI, with 17.39% strongly agreeing and 33.33% agreeing. Only 10.15% opposed this idea.
Departments Feel “On Par” with Peers in AI Coding Education:\ Most faculty (53.62%) believe their department is “about where our peers are” in helping students learn to code with AI and use AI tools. However, more respondents say their department is behind (20.29%) than ahead (8.70%).
Mixed Institutional Effort to Promote AI Courses for Non-CS Disciplines:\ Just under a third (31.88%) report that their university has made “a great deal” or “a lot” of effort to push the CS department to offer AI courses for other disciplines, while 26.08% say there has been “a little” or “none at all” .
Responsibility for Teaching AI to Non-CS Students Is Divided:\ The most popular choice for who should teach basic AI courses to non-CS students is the computer science department (37.68%), followed by the disciplines requiring such training (24.64%). A significant portion (28.99%) did not respond, indicating uncertainty or disagreement.
Faculty Call for More Practical, Applied, and Interdisciplinary Curriculum: Open-ended responses reveal a strong desire for curricula that emphasize hands-on AI and machine learning, responsible AI practices, and interdisciplinary collaboration. Many advocate for integrating AI into programming education and updating curricula to reflect current industry practices, while some express concern about AI’s growing dominance.
Table of Contents
43 Pages
- Table 1.1 To what extent do you agree with the following statement: My department should offer internal workshops to train faculty and PHD candidates in fields other than computer science in AI.
- Table 2.1 Your department is ahead of the curve or behind the curve on helping students learn to code with AI and use AI tools to their advantage?
- Table 3.1 How much of an effort has your university made to push the computer science department to offer AI courses aimed at those in other disciplines. such as business. healthcare and the humanities?
- Table 4.1 In your view, the responsibility to teach basic AI courses to those in disciplines other than computer science should rest with which entity?
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