Skill levels and gains in university STEM education in China, India, Russia and the United States.

Universities contribute to economic growth and national competitiveness by equipping students with higher-order thinking and academic skills. Despite large investments in university science, technology, engineering and mathematics (STEM) education, little is known about how the skills of STEM undergraduates compare across countries and by institutional selectivity. Here, we provide direct evidence on these issues by collecting and analysing longitudinal data on tens of thousands of computer science and electrical engineering students in China, India, Russia and the United States. We find stark differences in skill levels and gains among countries and by institutional selectivity. Compared with the United States, students in China, India and Russia do not gain critical thinking skills over four years. Furthermore, while students in India and Russia gain academic skills during the first two years, students in China do not. These gaps in skill levels and gains provide insights into the global competitiveness of STEM university students across nations and institutional types.

Calibrating the Test of Relational Reasoning: New Information From Oblique Bifactor Models.

Relational reasoning (RR) is believed to be an essential construct for studying higher education learning. Relational reasoning is defined as an ability to discern meaningful patterns within any stream of information. Nonetheless, studies of RR are limited by the psychometric structure of the construct. For many instances, the composite nature of RR has been described as a bifactor structure. Bifactor models limit possibilities for studying the inner structure of composite constructs by demanding orthogonality of latent dimensions. Such assumption severely limits the interpretation of the results when it is applied to psychological constructs. However, over the last 10 years, advances in the fields of Rasch measurement led to the development of the oblique bifactor models, which relax the constraints of the orthogonal bifactor models. We show that the oblique bifactor models exhibit model fit, which is superior compared to the orthogonal bifactor model. Then, we discuss their interpretation and demonstrate the advantages of these models for investigating the inner structure of the test of RR. The data are a nationally representative sample of Russian engineering students (N = 2,036).

Multicomponent framework for students' subjective well-being in elementary school.

The study proposes a multicomponent model of subjective well-being (SWB) in elementary school. The model includes satisfaction with school, affect toward school, well-being related to communication with peers, and subjective physical well-being. The aim of this study is to verify whether well-being related to different aspects of school life can be explained by a general SWB factor in school. A sample of 1,704 third-grade students (M age = 8.89; SD = 0.4; 48.4% girls) was asked to complete a survey consisting of Likert-type scales. The psychometric analysis investigated the internal structure of the data. Multidimensional models from the Rasch modeling framework of item response theory were applied. A correlated factors model, a bifactor model, and oblique bifactor models were compared. Two models fit the data well: the extended Rasch testlet model and the correlated factor model. The findings indicate that a general SWB factor can be extracted from the data through the extended Rasch testlet model. However, the extended Rasch testlet model provides only 1 usable general factor. For the extraction of detailed information by means of scales, the correlated factor model can be applied. Implications for practitioners and limitations of the study are also discussed. (PsycInfo Database Record (c) 2020 APA, all rights reserved).