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doi:10.1002/asi.v58:13

Cited by 185 publications

(5 citation statements)

References 745 publications

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“…PLS is especially suitable for analyses with small or medium sample sizes (Lee, Cheung & Chen, 2007), whereas LISREL is suitable for analyses with large sample sizes (Hulland, 1999). Therefore, researchers in fields related to information management (Burton-Jones & Hubona, 2006;Turel et al, 2007) and education (Annear & Yates, 2010;Sørebø et al, 2009;Tselios et al, 2011) have tended to perform the model analysis for latent variables by PLS.…”

Section: Discussionmentioning

confidence: 99%

“…Table 3 presents an overall good reliability of the measured variables in the present study because all the factor loadings in the latent variables ranged from 0.8 to 0.96. Composite reliability (CR) and average variance extracted (AVE) are the two main indicators used to evaluate convergent validity (Lee et al, 2007). A composite reliability of a latent variable is formed by reliabilities of all the measured variables, which represents an internal consistency of a latent variable (or consistency between measured variables in a latent variable).…”

Section: Measurement Model Analysismentioning

confidence: 99%

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Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students

Chang

Yan

Tseng

2012

AJET

249

152

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Since convenience is one of the features for mobile learning, does it affect attitude and intention of using mobile technology? The technology acceptance model (TAM), proposed by David (1989), was extended with perceived convenience in the present study. With regard to English language mobile learning, the variables in the extended TAM and its explanatory power were analysed and antecedent factors that affected acceptance of English mobile learning were also examined. Participants were 158 college students from the middle part of Taiwan. After conducting English mobile learning with a PDA, data was collected by questionnaires. The results revealed that: a) perceived convenience, perceived ease of use and perceived usefulness were antecedent factors that affected acceptance of English mobile learning; b) perceived convenience, perceived ease of use and perceived usefulness had a significantly positive effect on attitude toward using; and c) perceived usefulness and attitude toward using had a significantly positive effect on continuance of intention to use. Overall, the extended TAM in the present study was effective at predicting and explaining the acceptance of English mobile learning. In the past, there were few mobile learning related studies examining the relationships between perceived convenience and other variables in the TAM. Therefore, the findings in the present study provide a reference for the future TAM and mobile learning related studies. IntroductionMobile learning is a method in which materials are delivered by mobile technology, such as mobile devices and wireless networks (Wang, Wu & Wang, 2009). Mobile learning contains the features of e-learning and the benefits of mobile technology, which include convenience, immediacy and expediency. Mobile learning is featured by mobility and ubiquity, so it becomes the next milestone of e-learning and educational technology (Peng, Su, Chou & Tsai, 2009). Mobile devices, such as PDAs ('personal digital asistants') and smart phones (Shih, Chuang & Hwang, 2010), are portable and can be instant communication tools (Lea & Callaghan, 2011;Tung, Chang & Chou, 2008). Wireless networks with functions of immediate connection and transmission (Chinnery, 2006) enable a learner's interactions with learning content, peers and instructors to foster a meaningful knowledge construction and to get the updated 810 Australasian Journal of Educational Technology, 2012, 28(5) knowledge (Wang et al., 2009). Mobile technologies can help students interact with one another, collect and analyse data and get instant knowledge and messages in a learning environment.Learners who study English as a foreign language (EFL) must listen to and practise the language over and over again in order to enhance their learning performance (Thornton & Houser, 2005). However, class hours are limited, so it is important to develop an efficient tool or method for English learning outside classroom hours. Mobile learning can provide ways for students to learn English at any time and any place. Tho...

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Section: Discussionmentioning

confidence: 99%

Section: Measurement Model Analysismentioning

confidence: 99%

Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students

Chang

Yan

Tseng

2012

AJET

249

152

View full text Add to dashboard Cite

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“…Furthermore, Scopus has been shown to have a more-accurate automated calculator for the h- index (vs Web of Science]) [74], to include more peer-reviewed conference proceedings than Web of Science [75] and to avoid the problems of duplicate records and false-positives associated with Google Scholar [74-76]. …”

Section: Methodsmentioning

confidence: 99%

Two h-Index Benchmarks for Evaluating the Publication Performance of Medical Informatics Researchers

Emam¹,

Arbuckle²,

Jonker³

et al. 2012

J Med Internet Res

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BackgroundThe h-index is a commonly used metric for evaluating the publication performance of researchers. However, in a multidisciplinary field such as medical informatics, interpreting the h-index is a challenge because researchers tend to have diverse home disciplines, ranging from clinical areas to computer science, basic science, and the social sciences, each with different publication performance profiles.ObjectiveTo construct a reference standard for interpreting the h-index of medical informatics researchers based on the performance of their peers.MethodsUsing a sample of authors with articles published over the 5-year period 2006–2011 in the 2 top journals in medical informatics (as determined by impact factor), we computed their h-index using the Scopus database. Percentiles were computed to create a 6-level benchmark, similar in scheme to one used by the US National Science Foundation, and a 10-level benchmark.ResultsThe 2 benchmarks can be used to place medical informatics researchers in an ordered category based on the performance of their peers. A validation exercise mapped the benchmark levels to the ranks of medical informatics academic faculty in the United States. The 10-level benchmark tracked academic rank better (with no ties) and is therefore more suitable for practical use.ConclusionsOur 10-level benchmark provides an objective basis to evaluate and compare the publication performance of medical informatics researchers with that of their peers using the h-index.

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“…The two main indicators used to evaluate convergent validity are the composite reliability (C.R.) and average variance extracted (AVE) (Lee et al, 2007). The composite reliability of latent variables is formed by the reliabilities of all the measured variables which represent an internal consistency between measured variables in a latent variable.…”

Section: Confirmatory Factor Analysismentioning

confidence: 99%

Influence of the link between resources and behavioural factors on the entrepreneurial intentions of electrical installation and maintenance work students

Ohanu

Shodipe

2021

J Innov Entrep

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With a theory of planned behaviour (TPB) framework, this study examined how the link between resources and behavioural factors influence the entrepreneurial intentions of electrical installation and maintenance work (EIMW) students. It showed how available resources, which are defined as those controlled by the technical institutions but are accessible by the students, influence their behaviour and consequently their entrepreneurial intention. Different approaches are used in the study to analyse the primary data collected from EIMW students and an empirical analysis was done using structural equation model. The study showed the robustness of TPB model in the face of available resource that attitude, subjective norms and perceived behavioural control are behavioural factors that can be positively influence by several exogenous factors to enhance EIMW students’ entrepreneurial intentions. The results of the study enhance the institutional training of staff and instructors at all management to give career counselling services and be vast in the career opportunities available in the field of study. This skill will motivate EIMW students towards establishing their business venture.

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Untitled

Cited by 185 publications

References 745 publications

Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students

Perceived convenience in an extended technology acceptance model: Mobile technology and English learning for college students

Two h-Index Benchmarks for Evaluating the Publication Performance of Medical Informatics Researchers

Influence of the link between resources and behavioural factors on the entrepreneurial intentions of electrical installation and maintenance work students

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