Confidence at the crossroads: A systematic review of AI literacy, parental influence, and self-confidence in students’ career choice
DOI:
https://doi.org/10.17509/ijotis.v6i1.104402Kata Kunci:
AI literacy, Career choice, Career decision self-efficacy, Parental influence, PRISMA 2020 systematic review, Vocational education (TVET)Abstrak
Artificial intelligence is reshaping labour markets, positioning AI literacy as an understudied antecedent of students’ career choice alongside established influences such as parental support and self-confidence. This systematic review mapped the trends, theoretical frameworks, measurement instruments, and analytical methods linking these constructs and asked whether they had been examined jointly. Following PRISMA 2020 and a retrospectively registered protocol (Open Science Framework; registration pending), a single Scopus search in July 2026, limited to English-language articles and reviews, returned 107 records; independent dual screening with third-reviewer adjudication of disagreements yielded 79 studies, each appraised for methodological quality (AXIS/JBI). Because the query required an explicit self-efficacy, self-confidence, or self-esteem term, all coverage findings were limited to studies that measured self-confidence. The evidence base was dominated by Social Cognitive Career Theory (43 of 79 studies, 54.4%; 55 of 79, 69.6%, for the wider social-cognitive family) and by structural equation modelling; self-confidence, chiefly career decision self-efficacy, mediated contextual effects in 33 of the 41 studies that specified a mediator. Parental influence appeared in 74 studies but AI literacy in only six, all from 2025–2026, and just one measured all four constructs together. Within this corpus, no study modelled AI literacy and parental influence jointly through self-confidence. The review consolidated the framework, validated instruments, and methods needed to test such an integrative model and delineated the specific gap it would fill, offering a foundation for confirmatory research and AI-literacy instruction in vocational (SMK/TVET) science and engineering education.
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Hak Cipta (c) 2026 Hafid Fadilah, Isma Widiaty, Ahmad Satibi, Kennedy Barfi Yaw Agyeibi
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