Academic Discipline

Study Finds Widespread Generative AI Use Among College Students, Signaling Urgent Need for Discipline-Specific Assessment Reform

May 20, 2026

BERKELEY, CA — A new study led by Igor Chirikov, a senior researcher at UC Berkeley’s Center for Studies in Higher Education (CSHE) reveals that two-thirds of undergraduates at major U.S. public research universities utilized generative artificial intelligence (GenAI) during the 2023–2024 academic year. Both AI adoption and AI-assisted misconduct vary dramatically depending on the student's academic field.

The paper, titled "...

Artificial Intelligence and Grade Inflation. CSHE Higher Education Working Paper Series. Vol 26-3

Igor Chirikov
2026

Generative AI tools can undermine the informational value of grades by performing graded course tasks. I analyze the impact of AI on grade distributions across more than 500,000 grades at a large research university from 2018 to 2025 using a difference-in-differences design. Courses with more AI-exposed tasks, such as writing and coding, saw substantial grade increases after ChatGPT’s release: the share of A grades rose by 13 percentage points, or about 30% relative to the 2022 baseline. These increases were larger where homework carried greater weight, consistent with AI substituting for...

The Transformation of Academic Work: Facts and Analysis

Christine Musselin
2007

This paper outlines the main changes that have effected a transformation in the nature of academic work: on the one hand, the increasing diversification and specialisation of academic tasks, and on the other, new forms of control over academic work. An analysis of these trends leads to a discussion of the relationships between the evolution of academic work and non-academic work.

Institutional Versus Academic Discipline Measures of Student Experience: A Matter of Relative Validity, by Steve Chatman

Steve Chatman
2007

The University of California’s census survey of undergraduates, UCUES, presents an opportunity to measure both disciplinary and institutional differences in students’ academic experience. Results from nearly 60,000 responses (38% response rate) from the 2006 administration found greater variance among majors within an institution than between equivalent majors across institutions. Cluster analysis techniques were employed to establish disciplinary patterns, with traditional distinctions between hard and soft sciences generally supported. Reporting practices called into question range...