Purpose-The purpose of this paper is to explore the ability of the integration of technology acceptance model (TAM) and theory of reasoned action (TRA) to predict and explain university students' intention to use m-learning in schools. Design/methodology/approach-In total, 487 students participated in this study. A seven-likert scale survey questionnaire which comprised of 23 items was completed by the students. Structural equation modeling was used as the statistical technique to analyze the data. Findings-The study found that the resulting model was fairly able to predict and explain behavioral intention (BI) among students in Ghana. In addition, this study found that attitudes toward use and subjective norm significantly influenced students' BI to use mobile learning. The model explained 23.0 percent of the variance in BI, 33.8 percent in perceived usefulness and 47.6 percent in attitudes toward use. Of all the three endogenous variables, attitude had the greatest effect on BI. Originality/value-Although, the above-mentioned models have been adopted in many studies, few or none have combined TRA and TAM as a research framework to predict and explain students' intention to use m-learning since m-learning is fairly new in educational environments. Therefore, a model that combines all constructs from TRA and TAM was proposed in this study to explore university students' intention to use m-learning in schools.
The purpose of this study was to study undergraduate students' acceptance and use of ICT in classrooms. A total of 361 students from four universities participated in the study. Survey questionnaires which comprised both closed-ended and open-ended questions were used to collect data. Descriptive statistics, Pearson correlation, repeated-measures of Analysis of variance and multiple regression were used to analyze the findings. The study revealed that students use technology for personal purposes rather than for instructional purposes. Despite, students' high acceptance of technology, their technology integration into learning has remained low. The analysis showed that students believing that technology can improve their relationship with other students significantly contributed to their acceptance of technology in schools. Understanding students' acceptance and their experiences of technology use offer insights into their integration of technology into learning.
Purpose
This paper aims to develop and test a research model to explore the factors that influence pre-service teachers’ intention to use learning management system (LMS).
Design/methodology/approach
A cross-section study was conducted. A survey questionnaire was used to collect data from participants. The total number of participants was 361 pre-service teachers. Partial least square structural equation model was used to analyze the data.
Findings
The findings of this study found that the research model explained approximately 43% of the variance in behavioral intention. Also, the findings revealed that attitude and social influence had an effect on behavioral intention to use technology, but the facilitating condition had no effect on behavior intention to use technology. Finally, performance expectancy, effort expectancy and social influence had an effect on attitude while facilitating condition had no effect on attitude.
Originality/value
In technology acceptance research, unified theory of acceptance and use of technology (UTAUT) and technology acceptance model (TAM) have been broadly designed and empirically tested to elucidate the determinants that impact users’ intention to operate technology in the developed world. However, research on the validation of TAM and UTAUT to explain the determinants that influence preservice teachers’ intention to use a LMS in developing countries is insufficient. Therefore, it is important to evaluate the efficacy of the integrated model of TAM and UTAUT to explain preservice teachers’ intention to use technology and explore the influential determinants that explain preservice teachers’ intention to use LMS.
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