Investigating the Impact of Mobile Application on Learning Among Teachers Based on Technology Acceptance Model (TAM)

Saif, Naveed; Khan, Irfan Ullah; Khan, Gul Andaz

doi:10.31703/gesr.2020(v-ii).06

Cited by 8 publications

(6 citation statements)

References 25 publications

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“…Several studies [30][31][32] have been carried out to investigate the elements that impact consumers' adoption of M-learning. According to [33], academics did not take a thorough enough strategy while examining the attitudes of the pupils in a high school instructional situation.…”

Section: Research Backgroundmentioning

confidence: 99%

Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education

et al. 2021

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Mobile learning (M-learning) has become an important instructional technology component in higher education. The goal of this research is to determine how Malaysian university students use M-learning in higher education. The technology acceptance model (TAM) concept was used to construct a theoretical model of M-learning acceptability. In theory, five independent criteria were discovered as contributing to the actual usage of M-learning for educational sustainability by influencing students’ attitudes towards M-learning and their intention to use it. A questionnaire survey based on the technology acceptance model (TAM) was used as the primary data collection technique, with 200 students from UTHM University of Malaysia participating. The data were analyzed using SPSS and Structural Equation Modeling (SEM-Amos). The results of the students’ attitudes towards using M-learning and their behavioral intentions to use M-learning show a beneficial impact on the actual use of M-learning as well as the long-term sustainability of M-learning in higher education. In addition, both male and female students were satisfied with perceived usefulness, perceived ease of use, perceived enjoyment, attitude towards use, task-technology fit, behavioral intention to use, perceived resources and actual use of mobile learning for educational sustainability. This study contributes to the validation of the extended TAM for M-learning by demonstrating that the predicted model predicts students’ attitudes towards using M-learning and their behavioral intentions in Malaysian higher education.

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Section: Research Backgroundmentioning

confidence: 99%

Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education

et al. 2021

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“…Students and instructors have been shown to benefit from M-learning, with improved face-to-face and remote student involvement [8]. Several studies have investigated the impact of M-learning on consumer usage [9,10], and many students and instructors have been the focus of M-learning [11,12]. Although mobile devices are one of the main tools associated with learning, being entertained, and teaching [13], there are still very few guidelines on the sustainability and transfer of mobile learning initiatives [14].…”

Section: Introductionmentioning

confidence: 99%

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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“…Mobile App Usage (MAU): After a deep analysis of the existent literature, it can be highlighted that the impact of the mobile apps usage has directly influenced the TAM and that mobile app usage has had a positive impact on teacher performance and learning capabilities [31]. In this other study [32], it was observed that the perceived ease of use and perceived usefulness of mobile apps positively affected hotel consumers' experiences.…”

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confidence: 92%

Smart Cities and Citizen Adoption: Exploring Tourist Digital Maturity for Personalizing Recommendations

2023

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Due to the irruption of new technologies in cities such as mobile applications, geographic information systems, internet of things (IoT), Big Data, or artificial intelligence (AI), new approaches to citizen management are being developed. The primary goal is to adapt citizen services to this evolving technological environment, thereby enhancing the overall urban experience. These new services can enable city governments and businesses to offer their citizens a truly immersive experience that facilitates their day-to-day lives and ultimately improves their standard of living. In this arena, it is important to emphasize that all investments in infrastructure and technological developments in Smart Cities will be wasted if the citizens for whom they have been created eventually do not use them for whatever reason. To avoid these kinds of problems, the citizens’ level of adaptation to the technologies should be evaluated. However, although much has been studied about new technological developments, studies to validate the actual impact and user acceptance of these technological models are much more limited. This work endeavors to address this deficiency by presenting a new model of personalized recommendations based in the technology acceptance model (TAM). To achieve the goal, this research introduces an assessment system for tourists’ digital maturity level (DMT) that combines a fuzzy 2-tuple linguistic model and the analytic hierarchy process (AHP). This approach aims to prioritize and personalize the connection and communication between tourists and Smart Cities based on the digital maturity level of the tourist. The results have shown a significant correlation between technology usage and the potential for personalized experiences in the context of tourism and Smart Cities.

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Investigating the Impact of Mobile Application on Learning Among Teachers Based on Technology Acceptance Model (TAM)

Cited by 8 publications

References 25 publications

Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education

Exploring the Factors Affecting Mobile Learning for Sustainability in Higher Education

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

Smart Cities and Citizen Adoption: Exploring Tourist Digital Maturity for Personalizing Recommendations

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