Perceived learning gains and career orientation of STEM undergraduates in the AI Era: A quantitative study from Qatar

This study examines undergraduate STEM students' perceived learning gains and career orientation within Artificial Intelligence (AI)-prevalent higher education environments in Qatar, with particular attention to engagement, satisfaction, and technological experiences. A cross-sectional, perception-based survey design was employed. A structured literature mapping process informed construct identification, followed by instrument development and refinement through a Delphi method with expert input. The finalized questionnaire was administered to 175 undergraduate STEM students, and data were analyzed using SPSS, including reliability testing, normality assessment, Mann–Whitney U tests, and descriptive and visual analyses. The results revealed a statistically significant gender difference in career orientation scores, with female students reporting higher perceived learning gains and career orientation than male students ( p = 0.010). Differences based on nationality were not statistically significant, although descriptive trends indicated higher perceived impacts among expatriate students. Visual analyses suggested that career orientation generally increased with age and academic progression. Grounded in Social Cognitive Theory and the Technology Acceptance Model, the findings conceptualize AI as an embedded feature of contemporary learning environments rather than a discrete instructional intervention. The study highlights the importance of pedagogical integration of AI in shaping students’ engagement, learning perceptions, and career-related thinking in STEM education. • Examine STEM undergraduates' learning perceptions in AI-prevalent higher education environments. • Uses a perception-based survey design informed by Social Cognitive Theory and TAM. • Identifies statistically significant gender differences in career orientation. • Conceptualizes AI as an embedded educational context rather than a discrete intervention. • It indicates that career perceptions relate to how AI is integrated into learning environments, not simply its presence.