Determinants of Economical High School Students’ Attitudes toward Mobile Devices Use

Due to recent considerable technology breakthroughs in the education sector, new tools have been developed to improve learning. Motivating students to use new devices for learning rather than just for amusement, however, is a difficulty. The COVID-19 pandemic prompted the adoption of technological devices for course delivery, thereby highlighting the significance of mobile learning (m-learning) and allowing educators, students, and other stakeholders in the education sector to recognize its potential, advantages, drawbacks, and challenges. As m-learning has been an essential aspect of education for some time now, there is growing interest in assessing its long-term viability and usefulness across various educational domains, including economics. New technologies like computers, the internet, and related tools can help by bringing life to the classroom, gauging student progress, simulating economic activities and phenomena, and teaching vital skills needed for the economic world, like entrepreneurship. This study aims to explore the potential of incorporating new technologies in economic education, we study the tendency of the economical high school students towards using mobile devices for learning activities. A total of 407 participants were involved in research, the data from these respondents being collected with the help of a questionnaire survey. The original technology acceptance model (TAM) has been extended and the role of various external factors such as the subjective norm, learning autonomy, facilitating conditions or self-efficacy has been addressed. A list of hypotheses was proposed to validate the underlying model and provide guidance on how external factors affect attitudes towards using mobile devices. The empirical results indicated that perceived ease of use and perceived usefulness are significant predictors to explain the attitudes towards mobile devices use and m-learning and the analyzed external factors have a positive influence on them. In terms of methods used, we characterize the perception of students by structural equations modelling (SEM). This study identifies and analyzes the factors that influence students’ attitude and readiness towards mobile technology use in education, providing valuable insights into improving the adoption of new technologies and to evaluate the sustainability of m-learning in economic education.