A systematic review of 31 sources from Google Scholar, Scopus, ACM, IEEE Xplore and Web of Science examined AI and VR for job-seeking skills. It identified promise in personalised learning, multimodal interview practice and adaptive assessment, but most evidence was theoretical or component-specific, with few direct empirical tests of integrated AI–VR systems.
Key findings
- Reported systems emphasised personalised feedback, virtual interviews, multimodal practice and adaptive difficulty. Gaps included privacy, algorithmic fairness, accessibility and long-term evaluation, with limited evidence comparing fully integrated AI–VR systems against standard training.
Why this matters globally
The review sets a research agenda for universities, career services and edtech developers before deployment, especially bias audits, informed data use and disability-inclusive design.
Thai researcher contribution
Wenhao Dai is affiliated with Chongqing Polytechnic University and Rajamangala University of Technology Krungthep. The publisher page mislabels the Thai institution's country, while independent scholarly sources confirm its Bangkok affiliation. No evidence supports RMUT Isan for this paper, so the record has been corrected.
Limitations to consider
Only 31 sources were included and study-level risk-of-bias procedures are unclear, limiting confidence in the synthesis. Technology changes quickly, publication bias is plausible, and satisfaction or confidence does not equal employment success.