Measuring the Impact of AI-related Attitudes, Awareness, Skills and Usage on Students’ Learning Experience: A Gender-Based Exploration
Keywords:
higher education, artificial intelligence, educational technology, STEM, gender-gap, necessary condition analysisAbstract
International students, particularly in U.S. STEM graduate programs, often rely on artificial intelligence (AI) for translation, grammar, and writing aid. These programs have historically seen low female representation, reflecting a global gender gap in STEM education and technology usage due to systemic inequities. This study explores gender-based differences in AI-related dimensions and their impact on international students’ learning experience. Using Necessary Condition Analysis (NCA), we examined AI awareness, usage, perceptions, and education as predictors of positive learning outcomes. Surveying 422 Indian STEM students at a southeastern university, we found no gender-based differences across AI categories. Except for AI awareness, which proved a poor predictor for both genders, all other AI-related dimensions emerged as significantly necessary for higher learning experiences. These findings challenge existing research on the digital gender gap, offering implications for faculty and higher education administrators. We also discuss study limitations and propose future research directions.
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