Scalar consistency of collaborative learning: bifactor structural equation modeling

Abstract

The way of learning in higher education needs a revaluation, which should consider cooperation as one of the principles to improve the cognitive, procedural, and attitudinal learning of students whose training will allow them to integrate effectively into the work environment. The objective of the study was to validate the consistency of the collaborative learning scale (CLS) using the bifactor structural equation model (SEM) in university students from Junín. It presented a quantitative approach, through a deductive method, of demonstrative and inferential scope and a non-experimental design. The sample was of the probabilistic type, composed of 361 students of the Faculty of Health Sciences from cycles I to VIII at Huancayo University-2023. The results verified that the use of an original bifactor SEM allows the identification of multidimensional sources present in complex psychological measures, such as the evaluation instrument under study. In conclusion, thanks to the analysis of the Chi-square differences between the second-order model and the bifactor model, it can be verified that the bifactor model has a better fit than the second-order model because it has a lower X², a lower root mean square error of approximation (RMSEA), a lower weighted root mean residual (WRMR), and a higher ω.