An extended technology acceptance model of a mobile learning technology

2019 ◽  
Vol 27 (3) ◽  
pp. 721-732 ◽  
Author(s):  
Yu Zhonggen ◽  
Yu Xiaozhi
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Mobile Learning ◽  
Learning Technology ◽  
Mobile Learning Technology ◽  
Acceptance Model

Acceptance and Effectiveness of Rain Classroom in Linguistics Classes

2020 ◽  
Vol 12 (2) ◽  
pp. 77-90
Author(s):  
Zhonggen Yu ◽  
Han Yi
Keyword(s):  
Technology Acceptance ◽  
Structured Interview ◽  
Future Research ◽  
Knowledge Gain ◽  
Learning Technology ◽  
Significance Level ◽  
Mobile Learning Technology ◽  
Acceptance Model ◽  
Facilitating Conditions ◽  
And Linguistics

Rain Classroom, a mobile learning technology developed in China, has received great popularity. Research into its acceptance and effectiveness, however, remains sparse. Through research instruments, i.e. a questionnaire adapted from the Technology Acceptance Model (TAM), a semi-structured interview and linguistics knowledge tests, both quantitative and qualitative data were obtained to test research hypotheses. It was concluded that (1) Rain Classroom possesses significantly higher acceptance than traditional multimedia projecting systems in terms of performance expectancy, effort expectancy, social influence, facilitating conditions, and attitude at the significance level .05; and (2) Rain Classroom contributes to significantly higher linguistics knowledge gain than traditional multimedia projecting systems at the significance level .05. Future research could aim to improve and enhance the functions of Rain Classroom in order to pursue higher acceptance and effectiveness. Cross-disciplinary research could also be conducted to test its acceptance and effectiveness.

scholarly journals Avaliação do uso dos dispositivos móveis no ensino de Química por meio da adaptação dos Modelos de Aceitação (TAM) e Ajuste (TTF)

2020 ◽  
Vol 12 (27) ◽  
pp. 818
Author(s):  
Lediana Pereira Cardoso ◽  
Maria das Graças Cleophas
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Mobile Learning ◽  
Task Technology Fit ◽  
Acceptance Model

<p>Cada vez mais, as tecnologias móveis fazem parte de praticamente todos os contextos atrelados à vida humana. Contudo, quando se analisa o uso dessas tecnologias para o cenário educacional, percebe-se a existência de alguns paradigmas que ainda não foram superados. Este estudo usa o modelo adaptado de aceitação da tecnologia (<em>Technology Acceptance Model</em> - TAM), assim como o de ajuste Tecnologia-Tarefa (<em>Task-Technology Fit </em>–TTF) para examinar a aceitabilidade e ajuste de uma Sequência Didática que proporcionou a inserção da tendência BYOD na sala de aula de Química, por meio do uso de uma estratégia <em>mobile learning</em> que visava aplicar os dispositivos móveis dos alunos, em especial, os <em>smarthones</em>, como aporte ao processo de ensino e aprendizagem. Vale destacar que o estudo utilizou um desenho de investigação misto (qualitativo-quantitativo), e os dados foram coletados utilizando-se um questionário estruturado com alunos da Educação Básica de uma escola pública (N = 89). Os resultados apontam que a inserção das tecnologias móveis no ensino de química de modo planejado em sala de aula agregou benefícios para a aprendizagem dos alunos.</p>

THE ADOPTION OF E- LEARNING TECHNOLOGY FOR FARMERS USING EXTENSIONS TO TECHNOLOGY ACCEPTANCE MODEL (TAM)

2018 ◽  
Author(s):  
Buddhika Purnaka Siriwardena ◽  
Thippala Gamage Buddhika Dhanushka ◽  
Nisansala Priyadarshani Vidanapathirana
Keyword(s):  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Learning Technology ◽  
E Learning ◽  
Acceptance Model

scholarly journals An Empirical Study of Factors Driving the Adoption of Mobile Learning in Omani Higher Education

2016 ◽  
Vol 17 (4) ◽  
Author(s):  
Mohamed Sarrab ◽  
Ibtisam Al Shibli ◽  
Nabeela Badursha
Keyword(s):  
Higher Education ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Mobile Learning ◽  
Learning Technologies ◽  
Ease Of Use ◽  
Driving Factors ◽  
Just In Time ◽  
Short Supply ◽  
Acceptance Model

<p class="2">Mobile learning (M-learning) provides a new learning channel in which learners can access content and just in time information as required irrespective of the time and location. Even though M-learning is fast evolving in many regions of the world, research addressing the driving factors of M-learning adoption is in short supply. This article focuses on the driving factors in adoption of M-learning and the learner’s perceptions and willingness towards M-learning adoption. Technology Acceptance Model (TAM) has been shown to be a valid and powerful model in mobile and other learning technologies research. Based on Technology Acceptance Model theory, this paper analyzes the influencing factors on M-learning adoption and measure the acceptance of M-learning in Oman. The data collected from 806 participants in 17 different Omani higher education institutions using a survey questionnaire. Some factors of perceived innovative characteristics, such as ease of use, usefulness, enjoyment, suitability, social, and economic were found to have more influence on learners’ adoption of M-learning which help to facilitate and promote future empirical research. This effort is part of funded research project that investigate the development, adoption, and dissemination of M-learning in Oman.</p>

Extending the Learning Technology Acceptance Model of WeChat by Adding New Psychological Constructs

2020 ◽  
Vol 58 (6) ◽  
pp. 1121-1143
Author(s):  
Zhonggen Yu
Keyword(s):  
Language Learning ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Structural Equation ◽  
Large Scale ◽  
Equation Modeling ◽  
Future Research ◽  
Learning Technology ◽  
Significance Level ◽  
Acceptance Model

The extended constructs of technology acceptance model (TAM) have rarely been linked to psychological influence factors. This study complements for the missing link in literature through structural equation modeling and a nonparametric Mann–Whitney U test based on the data obtained from a large-scale questionnaire survey. It is concluded that (a) conformity behavior can be integrated into the TAM to establish a fit model in WeChat use in language learning at the significance level .05, (b) self-esteem can be integrated into the TAM to establish a fit model in WeChat use in language learning at the significance level .05, and (c) there are no significant gender differences in the extended constructs in the TAM in WeChat use in language learning at the significance level .05. Future research may extend the constructs further in psychology in order to complement for missing links in current literature. It is also promising to establish a sociocultural TAM with respect to mobile device acceptance in both western and eastern contexts.

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