Factors influencing graduate students' behavioral intention to use Google Classroom: Case study-mixed methods research.

Abstract

Blended learning combines face-to-face instruction and online learning experiences. It capitalizes on online learning management systems, one of which is Google Classroom (GC). Nevertheless, empirical investigations have mirrored literature gaps in understanding how the GC platform affects students’ behavioral intention to harness it for web-based learning. Therefore, this case study applied a modified version of the extended unified theory of acceptance and use of technology (UTAUT2) as a theoretical underpinning to examine factors influencing graduate students’ behavioral intention to utilize the GC platform. Employing mixed methods explanatory sequential design, the study first analyzed survey data from 23 EFL graduate students implementing partial least squares structural equation modeling (PLS-SEM). Subsequently, it conducted a qualitative stage carrying out semi-structured interviews for data collection and thematic analysis for its evaluation. The study through PLS-SEM results revealed that the most crucial determinant of students’ behavioral intention toward the GC platform was habit, which hung on facilitating conditions and hedonic motivation. Besides, it evinced facilitating conditions as the most important performing interaction factor in determining graduate students’ behavioral intention. Nonetheless, it indicated that performance expectancy, effort expectancy, social influence, facilitating conditions, and hedonic motivation had no direct effect on behavioral intention. The follow-up qualitative findings explained that since the students mainly used the GC platform off-campus, the GC App on their smartphones and the interesting content on the GC platform sustained their habitual tendencies toward employing the GC platform. Accordingly, the study explicates implications and recommendations for theory, policy, and practice.