Elucidating user behavior of mobile learning
نویسندگان
چکیده
Purpose – The purpose of this paper is to propose and verify that the technology acceptance model (TAM) can be employed to explain and predict the acceptance of mobile learning (M-learning); an activity in which users access learning material with their mobile devices. The study identifies two factors that account for individual differences, i.e. perceived enjoyment (PE) and perceived mobility value (PMV), to enhance the explanatory power of the model. Design/methodology/approach – An online survey was conducted to collect data. A total of 313 undergraduate and graduate students in two Taiwan universities answered the questionnaire. Most of the constructs in the model were measured using existing scales, while some measurement items were created specifically for this research. Structural equation modeling was employed to examine the fit of the data with the model by using the LISREL software. Findings – The results of the data analysis shows that the data fit the extended TAM model well. Consumers hold positive attitudes for M-learning, viewing M-learning as an efficient tool. Specifically, the results show that individual differences have a great impact on user acceptance and that the perceived enjoyment and perceived mobility can predict user intentions of using M-learning. Originality/value – There is scant research available in the literature on user acceptance of M-learning from a customer’s perspective. The present research shows that TAM can predict user acceptance of this new technology. Perceived enjoyment and perceived mobility value are antecedents of user acceptance. The model enhances our understanding of consumer motivation of using M-learning. This understanding can aid our efforts when promoting M-learning.
منابع مشابه
User Interface Design in Mobile Educational Applications
Introduction: User interfaces are a crucial factor in ensuring the success of mobile applications. Mobile Educational Applications not only provide flexibility in learning, but also allow learners to learn at any time and any place. The purpose of this article is to investigate the effective factors affecting the design of the user interface in mobile educational applications. Methods: Quantita...
متن کاملBehavioral Considerations in Developing Web Information Systems: User-centered Design Agenda
The current paper explores designing a web information retrieval system regarding the searching behavior of users in real and everyday life. Designing an information system that is closely linked to human behavior is equally important for providers and the end users. From an Information Science point of view, four approaches in designing information retrieval systems were identified as system-...
متن کاملImproving the performance of recommender systems in the face of the cold start problem by analyzing user behavior on social network
The goal of recommender system is to provide desired items for users. One of the main challenges affecting the performance of recommendation systems is the cold-start problem that is occurred as a result of lack of information about a user/item. In this article, first we will present an approach, uses social streams such as Twitter to create a behavioral profile, then user profiles are clusteri...
متن کاملA Dynamic Structural Model of User Learning in Mobile Media Content
Consumer adoption and usage of mobile communication and multimedia content services has been growing steadily over the past few years in many countries around the world. In this paper, we develop and estimate a dynamic structural model of user behavior and learning with regard to content generation and usage activities in mobile multi-media environments. Users learn about two different categori...
متن کاملFuzzy Motivations for Evolutionary Behavior Learning by a Mobile Robot
In this paper we describe a fuzzy logic based approach for providing biologically based motivations to be used in evolutionary mobile robot learning. Takagi-Sugeno-Kang (TSK) fuzzy logic is used to motivate a small mobile robot to acquire complex behaviors and to perform environment recognition. This method is implemented and tested in behavior based navigation and action sequence based environ...
متن کامل