A Model of Causal Relationships between Psychosocial Climate, Mood Patterns and Cognitive Achievement of Volleyball Subject by Using Trajectory Analysis

Abstract

In general, research tends to use quantitative measurement methods and statistical approaches to classify scientific phenomena and analyze mutual relations on an objective basis, which requires the researcher to collect data from a number of variables and search for interrelationships between them, and hence the importance of multivariate analysis methods, including modeling with the structural equation.

The modeling process with structural equations by advanced statistical methods is represented in the process of data analysis, with the aim of testing the validity of the interconnected relationships between the variables (theoretical models) that the researcher assumes without dividing the assumed relationships into parts. Where the researcher performs statistical analysis of the data after building the theoretical model, in order to verify the conformity of the data he collects with the assumed model.The importance of this study comes through revealing the effect of some factors (mood patterns, psychosocial climate) on students' cognitive achievement in volleyball subject, so the representation of the relationship between mood patterns, psychosocial climate and cognitive achievement among students of the College of Physical Education and Sports Sciences at the University of Muthanna, and simulation That relationship through a theoretical model, which is an artificially symbolic expression or conception of the current research problem, which helps in good perception as a basis for appropriate decision-making. . . If the sample data supports the theoretical model, then more complex theoretical models can be assumed. If the data do not support the theoretical model, either the original model will be modified and tested, or other theoretical models will be developed and tested.