Evaluating the Effectiveness of Smart Environment in Distance Learning: A PLS-SEM Approach

Abstract

This study investigates the factors that influence the effectiveness of distance learning in smart environments, focusing on teacher characteristics, student characteristics, and the use of smart technology. Using a sample of 203 students, Data were collected by a structured questionnaire and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that the attributes of both teachers and students substantially improve the efficacy of distant learning, with path coefficients of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\beta=0.518$</tex> and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\beta=0.577$</tex>, respectively. However, the correlation between technological utilization and learning effectiveness is negative and statistically non-significant (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\beta=-0.556, \mathrm{p}&gt;0.05$</tex>). These findings highlight the critical role of human factors, such as teacher expertise and student motivation, in achieving effective learning outcomes, while suggesting that the integration of smart technologies requires careful implementation and support. This study contributes to the current body of knowledge regarding intelligent learning environments. This work provides actionable suggestions for improving the design and implementation of distance education.