The Influence of Technology Utilization and Learning Motivation on Learning Concentration: SEM Analysis

Abstract

This study aims to analyze the influence of technology utilization and learning motivation on students' learning concentration. The study used a quantitative explanatory approach with the Structural Equation Modeling method based on Partial Least Squares (SEM-PLS). Data were collected through a Likert-scale questionnaire with 100 PGMI students as respondents. The research instrument consisted of 14 statement items divided into three variables: 4 statement items for the technology utilization variable, 5 statement items for the learning motivation variable, and 5 statement items for the learning concentration variable. Data were analyzed through evaluation of the measurement model and the structural model. The results of the validity and reliability tests showed that all constructs met the required criteria. Bootstrapping results show that learning motivation has a positive and significant effect on learning concentration (β = 0.748; T = 13.235; p < 0.001) with a very strong effect, while technology utilization also has a positive and significant effect on learning concentration (β = 0.127; T = 1.898; p = 0.029), although with a smaller influence strength. The R-square value of 0.689 (adjusted R-square = 0.682) indicates that 68.9% of the variation in learning concentration can be explained by learning motivation and technology utilization. The results of the effect size analysis (f-square) show that learning motivation has a very large effect on learning concentration (f-square = 1.155). In contrast, technology utilization has a small effect on learning concentration (f-square = 0.033). In conclusion, learning motivation is a dominant factor in improving learning concentration, while technology utilization plays a supporting role. Effective technology integration needs to be accompanied by motivation-enhancing strategies so that student learning concentration can be optimized.