Predicting students’ intention to adopt mobile learning

Abstract

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.

Adoption of internet of things among Malaysian halal agro-food SMEs and its challenges

“…Apart from DOI, Theory of Reasoned Action (TRA) commonly used and adopted in various studies such as SMEs technologies adoption intention (Hanafizadeh et al, 2012;Dang and Pham, 2018), predicting students' intention to adopt mobile learning (Buabeng-andoh, 2018), and acceptance of wireless internet (Lu et al, 2003). Based on Al-ajam and Nor (2015), TRA considers a narrow perspective of only two variables (attitude and subjective norm) that may affect individuals' behavioral intention.…”

Adoption of e-technology in the context of training in sustainability programs, cultural characteristics and European experience

“…Three constructs, perceived usefulness (PU), perceived ease of use (PEU), and behavioral intention (BI), were measured using 6, 6, and 4 items, respectively, and were adapted from the empirical study by F. Davis and related work. Scales: social norms, use of technology, measured using 4 and 4 items, respectively, were adapted from the empirical works of Ajzen I. and Fishbein M. [24] Perceived Quality of work life (QWL) included factors motivating to master electronic technology. [25] In addition, four dimensions of culture: Individualism, Power Distance, Uncertainty Avoidance, Masculinity / Femininity were measured using six items each and were adapted from P. Dorfman and J. Howell and G. Hofstede.…”

“…[23] Since it was found that the quality of work life is usually valued more in feminine cultures, it should be expected that in higher education, the QWL will have a stronger influence on the behavioral intention of individuals from feminine cultures. [24] The goal of this study was to examine in detail the impact of cultural dimensions at the individual level on the main components of the TAM model in the context of e-learning in sustainable development curricula. For this, the following objectives were solved: the TAM model was applied in the context of modern Russian culture, taking into account social norms (SN), the quality of work life (QWL), the actual values of the culture of Russian youth were measured at the individual level.…”

Effect Digital Learning on Student Motivation during Covid-19

“…The application of digital learning makes students more independent in learning and deepening teaching materials because students can study anytime and anywhere, both online and offline. And learning evaluation is carried out by means of a digital process, so there is no need for manual corrections [13]. The evaluation results obtained will be faster, more accurate, and objective.…”