Zianatul Makwa, Widihastuti Widihastuti, Nuryake Fajaryati
Computationally driven validation frameworks are increasingly required to support efficient, accurate, and replicable instrument validation in technical and vocational education and training assessment, as conventional approaches remain fragmented, time-consuming, and prone to human error. Accordingly, this study proposes a hybrid AI-assisted analytical framework integrating classical statistical validation methods with AI-supported computational workflows implemented in R and Shiny. To address these limitations, the proposed framework transforms conventional psychometric procedures into an integrated analytical system. The framework automates key validation workflows through an integrated, algorithm-driven analytical pipeline, including content validity assessment, construct validity through factor analysis, and reliability testing using principal axis factoring with Promax rotation. The system was implemented using pilot data collected from vocational school students covering four main constructs, namely professional identity, self-efficacy, entrepreneurial intention, and career adaptability. R automation confirmed the overall quality of the instrument through a systematic and high-precision validation process, in which content validity reflected strong expert agreement, sample adequacy satisfied algorithmic requirements for factor analysis, and internal consistency indicated reliable measurement performance across constructs. Beyond these statistical outcomes, the primary advantage of the proposed approach lies in the R-Shiny-based visualization layer, which enables real-time exploration of correlation structures, factor patterns, and data distributions, thereby supporting transparent interpretation, analytical traceability, and computational replicability of the psychometric results. This study offers a practical and scalable methodological solution that supports open science practices in vocational education research. © 2026 Copyright held by the owner/author(s).
Technology Vocational and Education, State University of Yogyakarta, Special Region of Yogyakarta, Yogyakarta, Indonesia; Educational Research and Evaluation, State University of Yogyakarta, Special Region of Yogyakarta, Yogyakarta, Indonesia
