The Collision of Pedagogy and Algorithm: Emergence of a New Gender Gap?

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Key Points

The study explores the relationship between AI interaction scores and gender representation in academic disciplines, aiming to understand implications for career outcomes.
Developed a multi-rater protocol combining human judgment with three large language model architectures.
Analyzed data from 574,740 student interactions mapped onto a career-competency framework.
Conducted a macro-structural analysis of discipline-level patterns across educational fields.
Disciplines with high female representation show low AI interaction scores.
A $52,090 earnings gap exists between the highest and lowest-earning fields.
AI interaction scores correlate negatively with female representation and positively with median earnings.

Multi-rater analysis reveals a gender gap in AI interaction scores, highlighting economic disparities in education.

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Mullens et al. (2026) studied this question.

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