Analysis and Evaluation of Factors Affecting the Use of Google Classroom in Albania: A Partial Least Squares Structural Equation Modelling Approach

Evgjeni Xhafaj,Daniela Halidini Qendraj,Etleva Halidini,Alban Xhafaj

doi:10.13189/ms.2021.090205

Evgjeni Xhafaj, Daniela Halidini Qendraj + Show 2 more

Open Access

https://doi.org/10.13189/ms.2021.090205

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Abstract

The study explores the number of factors that affect the use of Google Classroom in Albanian universities, by using the methodological developments of partial least squares structural equation modelling technique (PLS– SEM). This technique has been used because it allows flexibility in modelling the relationship between constructs (or factors) and in exploring theoretical concepts. An alternative model is introduced by extending the Unified Theory of Acceptance and Use of Technology (UTAUT2) and by integrating new relation between constructs. Our data are from a study of 528 students from 4 Albanian universities during the year 2020. Using Importance-Performance Matrix Analysis (IPMA) our analysis suggest that Habit is the construct that has the greatest importance in determining the Behavioral Intention towards Google Classroom, whereas Behavioral Intention has the greatest importance related to Use Behavior of Google Classroom. The results of the study show that Habit, and Hedonic Motivation have a greater impact on the Behavioral Intention to use Google Classroom. Additionally, we find that all constructs of the alternative model have an important influence to Behavioral Intention to Google Classroom and explain 65.3 per cent of its variance. This study will help the Higher Educations Institutions in assessing the factors that influence the use of Google Classroom, in such a way that this platform should be used as a support tool in the future.

Highlights

Due to the situation created by Covid-19, the traditional way of teaching and learning, in Albanian universities, moved towards e-learning tools, achieved through the implementation of the Learning Management Systems (LMSs)
Are compared the values of prediction errors in the context of root mean squared error (RMSE) obtained with the PLS-Structural Equation Model (SEM) method, if they give lower values than the prediction errors RMSE is obtained according to the linear regression model (LM) method
We present the values of importance, performance of each latent variable in relation to the target construct which in this case is use behavior (UB)

Summary

Introduction

Due to the situation created by Covid-19, the traditional way of teaching and learning, (i.e. face to face) in Albanian universities, moved towards e-learning tools, achieved through the implementation of the Learning Management Systems (LMSs). LMS are web-based systems that allow users such as instructors and /or students to share materials, submit, return assignments, and interact online with each other [1]. Students prefer Google Classroom compared to other LMS platforms because it is a free mobile application, easy to learn, and they can sign in from any computer or mobile device to access class assignments, course materials, and feedback, mobile application notifications. It is important for each university that before implementing e-learning tools to know the user acceptance of a new technology, i.e. what students need and accept [3]. The later model was developed further into the Unified Theory of Acceptance and Use of Technology (UTAUT2) [7]

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