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Generative AI use and misuse call for assessment reform in higher education
Igor Chirikov1, Ivan Smirnov2,3, René F Kizilcec4
1Center for Studies in Higher Education, Goldman School of Public Policy, University of California, Berkeley, Berkeley, CA, USA.
Science (New York, N.Y.)
|May 21, 2026
Summary
The increasing misuse and unequal access to artificial intelligence (AI) tools necessitate that universities fundamentally change their methods for evaluating student learning and academic integrity.
Area of Science:
- Educational Technology
- Artificial Intelligence Ethics
- Higher Education Pedagogy
Background:
- Artificial intelligence (AI) tools are increasingly prevalent in academic settings.
- Concerns exist regarding the misuse of AI for academic dishonesty.
- Unequal access to AI tools may exacerbate educational disparities.
Purpose of the Study:
- To highlight the urgent need for universities to re-evaluate their assessment strategies.
- To address the challenges posed by AI in academic learning environments.
- To propose a shift in how educational outcomes are measured in the age of AI.
Main Methods:
- This study is a conceptual analysis and literature review.
- It synthesizes current research on AI in education and academic integrity.
- It examines ethical considerations surrounding AI tool usage.
Main Results:
- Current assessment methods are vulnerable to AI-driven academic misconduct.
- Disparities in AI access create an uneven playing field for students.
- A significant reevaluation of learning evaluation is imperative.
Conclusions:
- Universities must proactively adapt their assessment frameworks to uphold academic integrity.
- Policies addressing equitable AI access and ethical use are crucial.
- Rethinking learning evaluation is essential for future educational paradigms.
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