Analysis of Non-intellectual Factors Affecting K-12 Student Academic Performance Using the Random Forest Model

Objective: A random forest algorithm was used to analyze non-intellectual factors that directly affect student achievement at the K-12 level and provide targeted strategies for addressing these factors. Methodology: Student learning data from the Kalboard 360 Learning Management System were selected. Non-intellectual influences on student performance were assessed using a single-factor analysis and and random forest models to rank the importance of independent variables and the scores were categorized into three levels: high, medium, and low, for independent analysis. Results: The single-factor analysis revealed 11 non-intellectual factors that were statistically significant (P < 0.05). In the ranking of importance, the three predominant variables influencing academic performance are the frequency of course access, the number of hand-raising instances in class, and the grade level of absenteeism. The frequency of course access dominates the high score bracket, the number of instances of hand-raising in class dominates the medium score bracket, and the grade level of absenteeism dominates the low score bracket. Conclusion: School teachers should focus on non-intellectual factors besides traditional teaching techniques and adopt strategies such as providing rich online resources and motivating students to learn. Through this, educators can improve academic performance from a fresh perspective.