Trainees’ experienced vocational education and training quality: formative assessment of scale development and validation

Purpose The study aims to propose and validate a multidimensional measure of trainees’ experienced vocational education and training quality (TEVETQ) in an Indian context. Design/methodology/approach This study explains a deductive approach in conceptualizing TEVETQ as a second-order, reflective-formative construct and its subsequent validation using SmartPLS version 3. The antecedent construct was assessed using an embedded two-stage method and finalized with five constructs, i.e. training facilities and equipment, trainer quality, placement counseling services, industrial exposure and extracurricular activities. The researcher analyzed the measurement invariance of composite models to ensure the power of statistical tests. The study findings conceptualize vocational education training as a formative construct in industries and can be generalized and extended to other sectors of the economy as well. Findings The current study developed a conceptually congruent and empirically validated multidimensional measure of vocational education and training (VET) quality. Further, the study has found industrial exposure as a significant formative indicator for TEVETQ. With the novel TEVETQ construct, the study on the antecedents and consequences of VET quality has substantial scope to progress. Research limitations/implications The current study is cross-sectional, and the data pertain to VET students in the Indian context. This limits the generalizability of the findings of this research. Practical implications The TEVETQ construct, with its integral dimensions, imparts an appreciation of how the trainees define VET quality. The authors propose TEVETQ as an additional key metric in evaluating VET quality. Originality/value Although extant literature on VET quality collectively concurs on its multidimensional nature, there is a limitation in validated measurements of VET quality. Hence, the current study addresses the research gaps by conceptualizing and validating a multidimensional measure of TEVETQ.