Constructing and Validating the Google Meet Mandarin Learning Scale (GMLS) for Malaysian Public Local University Students: Exploratory and Confirmatory Factor Analysis Approaches

Abstract

The widespread adoption of digital learning platforms during the COVID-19 pandemic has emphasized the need for proficiency in using tools like Google Meet (GM) for education. In Malaysia, the enforcement of the Movement Control Order (MCO) further accelerated the shift to online learning, particularly for language courses. However, research suggests that tertiary students' acceptance and effective use of Google Meet for Mandarin language learning remain suboptimal or unsatisfactory level. This study aims to address this issue by developing and validating the Google Meet Mandarin Learning Scale (GMLS) to assess key factors influencing learners’ adoption of GM for Mandarin learning. Grounded in the Technology Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of Technology (UTAUT), the study employed a cross-sectional research design. A pilot study with 139 responses underwent Exploratory Factor Analysis (EFA) using SPSS to refine the instrument, followed by Confirmatory Factor Analysis (CFA) on 366 responses using AMOS, ensuring the scale’s validity and reliability. The GMLS provides critical insights into the facilitators and barriers affecting students’ acceptance of Google Meet in Mandarin learning. The findings contribute to optimizing digital learning environments by offering a validated instrument for educators and policymakers to enhance students' engagement and learning outcomes. This study underscores the importance of technology integration in language education, supporting a more interactive and effective Mandarin learning experience.