Educational researchers, as well as researchers in other disciplines, often work with ordinal data, such as Likert item responses and test item scores. Critical questions arise when researchers attempt to implement statistical models to analyse ordinal data, given that many statistical techniques assume the data analysed to be continuous. Could ordinal data be treated as continuous data, that is, assuming the ordinal data to be continuous and then applying statistical techniques as if analysing continuous data? Why and why not? Focusing on structural equation models (SEMs), particularly confirmatory factor analysis (CFA), this article discusses an ongoing debate on the treatment of ordinal data and reports a short review on the practices of conducting and reporting SEMs, in the context of mathematics education research. The author reviewed 70 publications in mathematics education research that reported a study involving SEMs to analyse ordinal data, but less than half discussed how data were treated or guided readers through the analysis; it is therefore harder to repeat such an analysis and evaluate the results. This article invites methodological discussions on SEMs with ordinal variables in the practices of educational research. Subsequently, a standard for reporting SEMs with ordinal data is proposed, followed by an example. This standard contributes to educational research by enabling researchers (self and others) to evaluate SEMs reported. The example demonstrates, using real-life research data, how two different approaches for analysing ordinal data (as continuous or as a product of discretisation from some continuous distributions) can lead to results that disagree.

Vocational education plays a pivotal role in nurturing talent and supporting national development. However, challenges such as outdated talent development concepts, insufficient teacher training, and a lack of attention to soft skills cultivation from both schools and students have hindered the comprehensive development of secondary vocational students. This study aims to explore the direct effect of perceived teachers’ transformational leadership on the soft skills of 324 secondary vocational students in China and to examine the mediating role of students’ self-efficacy in this relationship. Using Structural Equation Modeling (SEM), the results show that teachers’ transformational leadership has a significant positive effect on students’ soft skills (β = 0.33, p < .01). Moreover, self-efficacy partially mediates this relationship (indirect effect β = 0.07, p < .05), accounting for 22.6% of the total effect. These findings suggest that teachers’ inspirational motivation, individualized consideration, and intellectual stimulation directly foster students’ communication, teamwork, and problem-solving skills, while also indirectly strengthening them by enhancing students’ confidence. Practically, the study underscores the need for teacher training in transformational leadership and for policy initiatives that integrate soft skills into vocational curricula.