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1 – 10 of 81The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning…
Abstract
Purpose
The study aims to validate a mobile learning readiness scale through the technology readiness and acceptance model (TRAM), thereby assessing students' readiness to adopt m-learning in teaching and learning, including its acceptance.
Design/methodology/approach
A structured questionnaire was administered to open and distance learning (ODL) students in Odisha, India, to assess their readiness and acceptance of m-learning. 665 valid responses were collected, and collected data was analysed using statistical packages for social sciences (SPSS) and SmartPLS.
Findings
The findings of the study reveal that optimism contributes positively to perceived ease of use (PEOU) and perceived usefulness (PU) of m-learning (β = 7.921, p < 0.001; β = 2.123, p < 0.05), whereas innovativeness positively contributes to PEOU of m-learning (β = 2.227, p < 0.05), but not PU of m-learning. ODL student's optimism improves his/her PEOU and PU of m-learning, but innovativeness improves only his/her PEOU. Further, the impact of innovativeness is higher than that of optimism in the TRAM and innovativeness is the strong predictor to adopt m-learning. It also shows that the PU of m-learning positively influences behavioural intention to use m-learning (β = 4.757, p < 0.001). Integrating technology readiness (TR) with technology acceptance model (TAM) to predict students' acceptance of m-learning is very useful.
Practical implications
The paper will help decision-makers to adopt and use m-learning in higher educational institutions.
Originality/value
This paper is the first to explore the readiness and acceptance of m-learning in higher education in India.
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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…
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.
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Md Nahin Hossain, Md. Shamim Talukder, Abul Khayer and Yukun Bao
In the era of m-learning environments, multiple factors have been considered to explain adult learners' continuance usage intention, but largely without considering the role of…
Abstract
Purpose
In the era of m-learning environments, multiple factors have been considered to explain adult learners' continuance usage intention, but largely without considering the role of specific configurations of variables and how they may affect learners' intention. The purpose of this study is to show how cognitive need, subjective norms, perceived usefulness, satisfaction, confirmation, attitude and perceived ease of use combine to predict learners' frequent use intentions.
Design/methodology/approach
It is empirically validated through configurational analysis, using fuzzy-set qualitative comparative analysis (fsQCA) on 211 adult learners with experience in using Mobile learning applications (MLA).
Findings
The findings show learners' satisfaction of MLA usage combined with the cognitive need and attitude were found to be core conditions reinforcing learners' continuance intention.
Research limitations/implications
This study was conducted in the context of adult learners MLA whereby the motivations for continued usage and the nature of technological innovation could differ. In this regard, findings from this study may not be generalizable to other technological contexts.
Practical implications
In the planning and development of learning apps, software developers should pay attention to practical functions and extend key features that are frequently required for solving a problem using the new skill. On the marketing side, MLA companies should emphasize the full functionality of their apps to cater efficiently to the different needs and expectations of the learners.
Originality/value
This study contributes by extending existing knowledge on how cognitive need, satisfaction and attitude combine to increase or mitigate continuance intention to use toward the development of new configurational theories. This study fills the gap in the literature by introducing adult learners' continuance intention to use MLA and introducing through a methodological approach of fsQCA in adult learners' context.
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Abstract
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Bargavi Ravichandran and Kavitha Shanmugam
This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption…
Abstract
Purpose
This conceptual study investigates the adoption of education technology (EdTech) products among college students, focusing on identifying the key factors influencing the adoption process within educational institutions. Technology integration in education has rapidly gained prominence, with EdTech offering innovative solutions to enhance teaching and learning experiences. However, understanding the determinants that affect EdTech adoption remains critical for its successful implementation and impact. This paper aims (1) to identify the factors influencing the adoption of EdTech by college students (2) to create a conceptual model that shows the connections between the elements that lead to college students adopting EdTech.
Design/methodology/approach
The research employed a mixed-methods approach, combining qualitative data analysis and conceptual modeling to achieve the objectives. The underlying knowledge required to create a qualitative data gathering tool was obtained through a thorough literature analysis on innovation dissemination, educational psychology and technology adoption. College students, teachers and administrators participated in semi-structured interviews, focus groups and surveys to provide detailed perspectives on their attitudes about and experiences with EdTech. The Scopus and Web of Science databases are searched for relevant information in an organized manner in order to determine the factors influencing the adoption of EdTech. Second, an extended version of the technology adoption model is adopted to develop a qualitative data-based conceptual framework to analyze EdTech adoption in the Indian context.
Findings
Overall, by highlighting the critical components that emotionally influence college students' adoption of EdTech products in educational institutions, this course adds to the body of information already in existence. The conceptual framework model serves as a roadmap for educational stakeholders seeking to leverage EdTech effectively to enrich the learning environment and improve educational outcomes. By recognizing the significance of the identified factors, academic institutions can make informed decisions to foster a climate conducive to successful EdTech integration.
Research limitations/implications
A comprehensive conceptual framework model was developed based on qualitative data analysis to illustrate the interrelationships between the identified factors influencing EdTech adoption. This model presents a valuable tool for educational institutions, policymakers and EdTech developers to comprehend the complex dynamics of implementing these technological solutions.
Originality/value
The findings of this study demonstrated a number of important variables that affect the uptake of EdTech products in educational settings. These factors encompassed technological infrastructure, ease of use, perceived usefulness, compatibility with existing academic practices, institutional support, financial constraints and individual attitudes towards technology. Additionally, the research explored the significance of institutional preparation for embracing technological advancements as well as the influence of socio-cultural elements.
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Enrique Sánchez-Rivas, Manuel Fernando Ramos Núñez, Magdalena Ramos Navas-Parejo and Juan Carlos De La Cruz-Campos
The aim of this paper is to explore whether the use of an active learning methodology implemented through a mobile phone can help future teachers to develop more effective reading…
Abstract
Purpose
The aim of this paper is to explore whether the use of an active learning methodology implemented through a mobile phone can help future teachers to develop more effective reading promotion activities than those based on traditional learning methodologies.
Design/methodology/approach
A study was conducted based on the comparison of perceptions of two groups of teacher training students. The experimental group was trained in an active methodology to promote reading on mobile phones, whilst the control group was trained in a classical methodology also using the same devices. Variables were observed using a self-administered questionnaire, and the scores obtained were analysed from their descriptive statistics of the comparison of means of Kruskal–Wallis H test.
Findings
The results showed that students perceived significant improvements associated with active learning methodology. The variables with the most remarkable results were those related to better use of the class, participation and satisfaction. However, the ubiquitous variable obtained the fewest differences, maybe because both learning methodologies were applied using mobile devices.
Originality/value
The conclusions of this study clearly suggest that combining active learning methodologies and the use of mobile phones to promote reading could lead to better results than applying traditional learning methodologies. The value of this study paves the way for future research to move forward in the discovery of effective teaching strategies based on active methods and mobile devices.
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Chia-Chen Chen, Patrick C.K. Hung, Erol Egrioglu, Dickson K.W. Chiu and Kevin K.W. Ho