Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education

Al-Rahmi, Ali Mugahed; Al-Rahmi, Waleed Mugahed; Alturki, Uthman; Aldraiweesh, Ahmed; Almutairy, Sultan; Al-Adwan, Ahmad Samed

doi:10.3390/su13147893

Cited by 107 publications

(132 citation statements)

References 94 publications

(121 reference statements)

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“…Task-technology fit (TTF) was proposed with the establishment of five items as recommended by [52]. The concept of perceived ease of use (PEU) was presented, along with the development of five elements as suggested by experts [2,81]. The concept of perceived usefulness (PU) was presented, along with the creation of five elements as suggested by [2,81].…”

Section: The Instrumentationmentioning

confidence: 99%

“…The concept of perceived ease of use (PEU) was presented, along with the development of five elements as suggested by experts [2,81]. The concept of perceived usefulness (PU) was presented, along with the creation of five elements as suggested by [2,81]. The establishment of five elements in terms of student satisfaction (SS) was proposed [81].…”

Section: The Instrumentationmentioning

confidence: 99%

“…Education is a transformational process which involves using active teaching methods and incorporating technology into the classroom [1]. In particular circumstances such as the COVID-19 pandemic, using online training and mobile telecommunications to conduct the teaching and learning processes is critical [2]. Mobile technologies such as smart phones, provide a variety of features that enhance mobile student learning, such as customized interfaces, timely access to information, context sensitivity, rapid communication, and feedback opportunities [3].…”

Section: Introductionmentioning

confidence: 99%

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Students’ Perceptions of the Actual Use of Mobile Learning during COVID-19 Pandemic in Higher Education

Alturki

Aldraiweesh

2022

Sustainability

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Mobile learning (M-learning) has become a significant component of higher education technology. Moreover, M-learning allows students to study, collaborate, and exchange ideas while using the internet and technology. Furthermore, an acceptance of M-learning is necessary for students and educators when it comes to using M-learning systems. However, in Saudi Arabia, not enough studies have been conducted to address students’ perceptions of their actual use of mobile learning for the purpose of education during the COVID-19 pandemic. Therefore, the current research aims to examine students’ satisfaction with their behavioral intention to use mobile learning, as well as their perceptions of their actual use of mobile learning during the COVID-19 pandemic in higher education. The research is based on the Technology Acceptance Model (TAM). The satisfaction and behavioral intentions of students to utilize mobile learning to make real use of mobile education was measured using four separate variables. A TAM survey was used to collect the majority of the data, with questionnaires being randomly distributed to 300 students from King Saud University. SPSS and Smart-PLS3.3.3 were used to analyze the data. The results in terms of the students’ satisfaction and behavior in using M-learning show that M-learning has a good and constructive influence on the actual usage of M-learning during the COVID-19 pandemic in higher education. As a result, we encourage students to use M-learning in their classrooms and to collaborate with their peers at higher education institutions. The study’s empirical findings aid in the integration of the TAM model in order to increase students’ M-learning performance.

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Section: The Instrumentationmentioning

confidence: 99%

Section: The Instrumentationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Students’ Perceptions of the Actual Use of Mobile Learning during COVID-19 Pandemic in Higher Education

Alturki

Aldraiweesh

2022

Sustainability

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“…The perspectives of students on ICT are significant because they influence how they use technology, which has an impact on their academic and professional performance. A positive evaluation of ICT components does not guarantee that they will be employed in the learning process [13,14], but it is a solid starting point. In many aspects of social life, but particularly in education, information and communication technologies are becoming increasingly common and vital.…”

Section: Introductionmentioning

confidence: 99%

Factors Influencing University Students’ Adoption of Digital Learning Technology in Teaching and Learning

et al. 2022

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Education and learning have been significantly impacted by ICT. The purpose of this project is to create a new model and conduct confirmatory factor analysis in order to better understand how students utilize ICT in the classroom. An additional aim is to study, based on students’ attitudes and aspirations to utilize ICT for digital learning, their fundamental computer abilities, media-related skills, WBS, and adoption of digital learning technologies, by surveying students at Bisha University and King Faisal University. Structural equations modeling (SEM)-AMOS was used to survey 711 university students, and this study used an improved version of the Technology Acceptance Paradigm (TAM) approach as its research paradigm, as well as quantitative data collection and analytic methodologies. Students’ comments were divided into seven categories and analyzed to identify their attitudes toward and intentions for using ICT in learning environments. BCS, media-related abilities, and WBS all had a substantial influence on perceived usefulness and perceived ease of use, according to the research. This model, which was based on research, was successful in describing students’ attitudes and intentions about using ICT for digital learning.

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“…The second section is further divided into two main parts: the first part contains 18 scales borrowed from Davis et al (1989) and Venkatesh and Davis (2000). The other part integrates 24 scales that developed using DOI and reconstructed from the previous research (Davis et al, 1989;Moore and Benbasat, 1991;Karahanna et al, 2002), and 5 scales modified from (Al-Rahmi et al, 2020a;Al-Rahmi et al, 2021a;Alamri et al, 2020a). The instrument-items of the study were examined and assessed by two experts in the field.…”

Section: Developing Of the Research Instrumentmentioning

confidence: 99%

Adaptation of Big Data: an empirical investigation for sustainability of education

Alismaiel¹

2021

JESI

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The current study aims at developing a framework to assess big data use for education and encompassing the theoretical background of knowledge sharing and diffusion of innovations in the educational environment. This study hypothesizes that age and cultural diversity, and motivators can influence knowledge sharing, whereas the constructs of relative advantage, trialability, complexity, observability would impact innovations. Thus, innovations influence knowledge sharing and would be positively associated with behavioural intention to use big data and sustainability for education. This study utilized a version of knowledge sharing model and Diffusion of Innovations (DOI) theory as the study framework and implemented quantitative approach for data analysis by collecting 494 responses from university students who were elected using stratified random sampling technique. The data were processed using eleven factors to unveil and understand the predictors of big data use for education sustainability. The study adopts the quantitative approach and employs structure equation modelling (SEM) to data analysis. According to the study's findings, age and cultural diversity and motivators significantly determine knowledge management sharing, while relative advantage, trialability, complexity, and observability have a positive impact on innovations. The adoption of innovations, knowledge sharing, and big data are able to capture 78.9% of sustainability phenomenon on education. Further, the study concludes by reporting findings and implications for research and practitioners.

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Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education

Cited by 107 publications

References 94 publications

Students’ Perceptions of the Actual Use of Mobile Learning during COVID-19 Pandemic in Higher Education

Students’ Perceptions of the Actual Use of Mobile Learning during COVID-19 Pandemic in Higher Education

Factors Influencing University Students’ Adoption of Digital Learning Technology in Teaching and Learning

Adaptation of Big Data: an empirical investigation for sustainability of education

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