Paper Title
EVALUATING THE LEARNING EFFICACY OF AI IN SHAPING THE UNDERGRADUATE STUDENT’S CAREER ASPIRATIONS IN STEM DISCIPLINES

Abstract
Purpose: This study, part of a summer internship program, evaluates the influence of Artificial Intelligence (AI) on undergraduate students' persistence in STEM disciplines and its impact on shaping their career aspirations. It explores AI's psychological, educational, and technological effects on student engagement, satisfaction, and career pathways. Methodology: Following the PRISMA framework, a comprehensive literature review was conducted. A structured survey questionnaire was developed and validated using the Delphi method and distributed to undergraduate STEM students via Microsoft Forms. Reliability was tested using Cronbach's alpha, and normality was assessed through the Shapiro-Wilk test. Data were analyzed using SPSS, and databases such as Web of Science, ERIC, and SCOPUS informed the literature review. Findings: The psychological impact of AI showed non-normal distributions in students aged 15-18 and 19-22, as well as in third-year undergraduates. Other age groups and students exhibited normal distributions. Notably, first-year female students experienced a significantly higher psychological impact than their male peers, though this difference diminished by the fourth year. A balanced distribution of participants across variables contributed to the reliability of the findings. The study underscores AI's transformative role in shaping student experiences and career aspirations in STEM education.