Mathematics Students’ Readiness for Mobile Learning

Abu-Al-Aish, Ahmad; Love, Steve; Hunaiti, Ziad

doi:10.4018/jmbl.2012100101

Cited by 21 publications

(12 citation statements)

References 14 publications

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“…M-learning promotes online self-study by accessing resources while exchanging knowledge with instructors/peers. M-learning occurs through online tools such as Moodle, WebCT, and Blackboard, along with traditional in-class teaching and learning (Abu-Al-Aish et al, 2012;V. Chang, 2016).…”

Section: Sage Openmentioning

confidence: 99%

M-Learning Improves Knowledge Sharing Over e-Learning Platforms to Build Higher Education Students’ Social Capital

Razzaque

2020

Sage Open

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The education sector is transforming from e-learning to m-learning due to its motivation capabilities that drive students toward self-motivated learning. However, this requires online participation through quality knowledge sharing (KS) of the social capital (SC) of resources. Past-reported low student participation calls for confirming whether social capital affects KS in m-learning. Scholars assessed this effect—however, not in the education sector—and revealed scant clarification of whether m-learning regulates SC through KS. Hence, this is the motivated aim reflected through a conceptual framework, that is, tested using multiple-regression analysis after collecting data from 334 Ahlia University undergraduate business students. The results confirm that m-learning moderates students’ SC through KS in e-/m-learning on Moodle. Implications for theory, practice, and society are revealed in this article.

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Section: Sage Openmentioning

confidence: 99%

M-Learning Improves Knowledge Sharing Over e-Learning Platforms to Build Higher Education Students’ Social Capital

Razzaque

2020

Sage Open

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“…The questionnaire for this study was a paper-based questionnaire which contained both closedand open-ended questions. The structure was adopted from [51], who conducted a similar study in a British University to investigate students' readiness for m-learning. The closed-ended questions included dichotomous questions, multiple-choice questions, and five-point Likert scale items.…”

Section: Data Collection and Analysismentioning

confidence: 99%

Readiness, Roles, and Responsibilities of Stakeholders for Sustainable Mobile Learning Adoption in Higher Education

2020

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The extant literature on mobile learning in higher education has mainly focused on students and academics. This study conducted in a Nigerian university considered a wider group of stakeholders (students, academics, IT personnel, and administrative leaders) in its investigation of stakeholders’ awareness, willingness, and readiness for mobile learning adoption, using a mixed methods approach. The findings revealed that while the awareness of mobile learning amongst students was low, they were keen on adoption. Academics were more tentative, for while they were willing, it was clear that a shift in their teaching philosophy and pedagogy would be required for mobile learning to work effectively. For those in IT and administrative leadership roles, their perceptions were more resource-focused. While this study only considered the views of internal stakeholders, it also uncovered the need for the involvement of external stakeholders. Building on these findings, a strategy table which outlines the roles and responsibilities of each stakeholder group was created. The table provides a blueprint which otherwise has been missing, to guide sustainable mobile learning adoption and implementation not only in higher education in developing countries, but which may have more global appeal.

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“…Users may not be willing to accept m-learning (Wang, Wu, & Wang, 2009). In addition, some university lecturers do not want to apply this technology or might face difficulties in trying to use it effectively as this new technology may require a lot of effort to implement (Abu-Al-Aish, Love, & Hunaiti, 2012).…”

Section: Introductionmentioning

confidence: 99%

Factors influencing students’ acceptance of m-learning: An investigation in higher education

Abu-Al-Aish

Love

2013

IRRODL

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147

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M-learning will play an increasingly significant role in the development of teaching and learning methods for higher education. However, the successful implementation of mlearning in higher education will be based on users' acceptance of this technology. Thus, the purpose of this paper is to study the factors that affect university students' intentions to accept m-learning. Based on the unified theory of acceptance and use of technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors that influence the acceptance of m-learning in higher education and to investigate if prior experience of mobile devices affects the acceptance of m-learning. A structural equation model was used to analyse the data collected from 174 participants.The results indicate that performance expectancy, effort expectancy, influence of lecturers, quality of service, and personal innovativeness were all significant factors that affect behavioural intention to use m-learning. Prior experience of mobile devices was also found to moderate the effect of these constructs on behavioural intention. The results of this research extend the UTAUT in the context of m-learning acceptance by adding quality of service and personal innovativeness to the structure of UTAUT and provide practitioners and educators with useful guidelines for designing a successful mlearning system.

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Mathematics Students’ Readiness for Mobile Learning

Cited by 21 publications

References 14 publications

M-Learning Improves Knowledge Sharing Over e-Learning Platforms to Build Higher Education Students’ Social Capital

M-Learning Improves Knowledge Sharing Over e-Learning Platforms to Build Higher Education Students’ Social Capital

Readiness, Roles, and Responsibilities of Stakeholders for Sustainable Mobile Learning Adoption in Higher Education

Factors influencing students’ acceptance of m-learning: An investigation in higher education

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