Cognitive Factors Explaining Procedural Knowledge: A Multiple Linear Regression Analysis

Abstract

This study analyzes how conditional knowledge, planning, and filtering contribute to the development of procedural knowledge through a multiple linear regression model. Data from a significant sample were analyzed, showing that all independent variables had positive and significant effects on the dependent variable. The results indicate that planning and conditional knowledge have the most notable impacts, while filtering contributes to a lesser extent. The model demonstrated good overall fit (R2=0.435R^2 = 0.435R2=0.435), meeting the assumptions of linearity, normality, homoscedasticity, and absence of multicollinearity. This study provides an empirical framework emphasizing the importance of key cognitive factors in the development of procedural knowledge.