Factors Affecting Students’ Acceptance of Mobile Learning Application in Higher Education during COVID-19 Using ANN-SEM Modelling Technique

Abstract

Due to the COVID-19 pandemic, most universities around the world started to employ distance-learning tools. To cope with these emergency conditions, some universities in Jordan have developed “mobile learning platforms” as a new tool for distance teaching and learning for students. This experience in Jordan is still new and needs to be evaluated in order to identify its advantages and challenges. Therefore, this study aims to investigate students’ perceptions about mobile learning platforms as well as to identify the crucial factors that influence students’ use of mobile learning platforms. An online quantitative survey technique using Twitter was employed to collect the data. A two-staged ANN-SEM modelling technique was adopted to analyze the causal relationships among constructs in the research model. The results of the study indicate that content quality and service quality significantly influenced perceived usefulness of mobile learning platforms. In addition, perceived ease of use and perceived usefulness significantly influenced behavioral intention to use mobile learning platforms. The study findings provide useful suggestions for decision makers, service providers, developers, and designers in the ministry of education as to how to assess and enhance mobile learning platform quality and understanding of multidimensional factors for effectively using mobile learning platforms.

Determinants of Behavioral Intention and Use of Interactive Whiteboard by K-12 Teachers in Remote and Rural Areas

“…Based on the results, the BI and UB of K-12 teachers in remote and rural areas were not influenced by PE, EE, and SI. This was slightly different from other previous reports, as PE and EE were often significantly affected (Estriegana et al, 2019;Almaiah et al, 2021;Alturki and Aldraiweesh, 2022). Meanwhile, Social Influence was predicted to have an impact on technology in some studies (Maduku, 2017;Asghar et al, 2021).…”

Grade Prediction Modeling in Hybrid Learning Environments for Sustainable Engineering Education

“…The immediate and often precipitous transformation of face-to-face learning environments into virtual online spaces has prompted trainers, instructors, and teachers to integrate numerous technology tools and platforms into the educational process [1,2]. Learning management systems (LMS) and learning platforms have been combined with social networking sites (SNS) to transmit as many synchronized courses as possible, share new knowledge, and facilitate academic communication on task support [3][4][5][6].…”

“…In the first year of this health crisis, when online education became the exclusive mode of learning, researchers became aware of an unexpected challenge: the transformation of the educational schema through the incorporation of technological tools that previously remained inert or undiscovered by students and instructors. Several aspects of these new learning environments have been investigated, revealing new parameters that affect the academic performance of students in exclusively distance learning environments, while demonstrating the effectiveness of the technological tools used, as well as their sustainability [6][7][8][9]. Virtual learning environments (VLE) could also make a contribution in this still uncertain global health context, especially since distance learning and asynchronous support for knowledge transmission have already been tested in strictly distance learning environments [7].…”

A Conceptual Framework for Determining Quality Requirements for Mobile Learning Applications Using Delphi Method

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