Identification of critical factors for success of engineering graduates using structural equation modeling by means of the partial least square technique

The identification of important non-cognitive attributes (constructs) as critical factors of success (CFS) in engineering education has been an important topic of discussion in contemporary issues of higher education. The literature reports cultural intelligence, academic self-efficacy, experiential learning, and similar constructs (latent variables) as improving factors of student's readiness to enter the job market, although limited experimental data is available in the literature. The aim of this research was to investigate the influence of CFS in producing more competitive graduates. In this study, a theoretical model was used to explore the linear relationships between CFS and a culture of academic quality. The model was empirically validated by means of a second generation multivariate analysis defined as Structural Equation Modeling (SEM) using the partial least squares technique (PLS). Data was collected through a survey/questionnaire and analyzed using the SmartPLS 3.0 software. The findings indicated that the proposed CFSs have a significant effect on a culture of academic quality and suggested that self-efficacy in academic settings is influenced by experiential learning and intercultural situations. The results also inferred that institutions of higher education may be able to improve the overall academic preparedness of future graduates by incorporating experiential learning opportunities that nurture and promote students' self-efficacy and cultural intelligence. Although these findings are consistent with the hypothesis that universities are providing sound technical preparedness to students regardless of experiential learning activities, the findings led to the conclusion that subjective components of higher education linked to human behaviors, dispositions and perceptions should be further studied.;The findings of this research may provide the basis for more advanced investigations to study the subjective components of quality in higher education. It is recommended that future research may be complemented with longitudinal studies with larger samples. It is expected that the approach outlined in this study may be replicated in other institutions in order to analyzed similar or adapted path models.