Measuring General Computer Self-Efficacy: The Surprising Comparison of Three Instruments in Predicting Performance, Attitudes, and Usage

Downey, James P.

doi:10.1109/hicss.2006.268

Cited by 19 publications

(18 citation statements)

References 36 publications

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“…Several studies have found SE to be an important determinant that directly influences the user's behavioural intention and actual usage of IT (Downey, 2006;Shih & Fang, 2004;Guo & Barnes, 2007;Yi & Hwang, 2003;Hernandez, Jimenez, & Jose Martin, 2009) and e-learning acceptance (Chang & Tung, 2008;Yuen & Ma, 2008;Park, 2009;Vijayasarathy, 2004;Chatzoglou et al, 2009;Roca, Chiu, & Martínez, 2006;Darawsheh et al, 2016). On the contrary, Venkatesh et al (2003) did not find a casual direct relationship between SE and BI.…”

Section: E-learning and Self-efficacymentioning

confidence: 45%

Technology, Demographic Characteristics and E-Learning Acceptance: A Conceptual Model Based on Extended Technology Acceptance Model

Tarhini¹,

Elyas²,

Akour

et al. 2016

HES

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The main aim of this paper is to develop an amalgamated conceptual model of technology acceptance that explains how individual, social, cultural and organizational factors affect the students' acceptance and usage behaviour of the Web-based learning systems. More specifically, the proposed model extends the Technology Acceptance Model (TAM) to include four constructs namely, Quality of work life; Social Norm; Facilitating Conditions and self-efficacy. In addition, Individual differences-namely, age, gender, and experience-are hypothesized to moderate the effects of these constructs on behavioral intention and technology use. A comprehensive understanding of this model will provide valuable insights into the factors that influence the acceptance or resistance of web-based learning system by intended users and offers opportunities for future research in understanding the acceptance of technology. Further, understanding these variables is helpful for instructors to design meaningful educational activities to promote student knowledge construction and make learning more effective and appealing.

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Section: E-learning and Self-efficacymentioning

confidence: 45%

Technology, Demographic Characteristics and E-Learning Acceptance: A Conceptual Model Based on Extended Technology Acceptance Model

Tarhini¹,

Elyas²,

Akour

et al. 2016

HES

View full text Add to dashboard Cite

show abstract

“…Venkatesh and Davis (1996) found that computer self-efficacy ( CSE) acts as a determinant of perceived ease of use (PEU) both before and after hands-on use with a system (V. Venkatesh & Davis, 1996). Other researchers have also found an influence of CSE on the TAM (Chen, Huang, & Shih, 2002;Downey, 2006;Strong, DiShaw, & Brady, 2006). Researchers have also evaluated the influence of users' self-efficacy toward the type or subject of the targeted system, such as Internet and e-learning self-efficacy, on the TAM.…”

Section: Holden and Rada External Variablesmentioning

confidence: 95%

Understanding the Influence of Perceived Usability and Technology Self-Efficacy on Teachers’ Technology Acceptance

Holden

Rada

2011

Journal of Research on Technology in Education

371

228

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“…In their study, Grandon et al (2005) found that e-learning self-efficacy has an indirect effect on students' intentions through perceived ease of use. Other TAM researchers have found an influence of SE on different TAM variables (Chen, Huang, & Shih, 2002;Downey, 2006;Saadé & Kira, 2009;Strong, Deneen, & Ng, 2006). As a result, this study hypothesizes the following: H1: Self-efficacy has a significant effect on perceived ease of use of using MyMathLab.…”

Section: Self-efficacy (Se)mentioning

confidence: 99%

University Student Perceptions of Technology Use in Mathematics Learning

et al. 2015

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Although most universities and educators are relying on implementing various technological tools in the curriculum, acceptance of such tools among students is still not sufficient. The Technology Acceptance Model (TAM) has been widely used by researchers to test user's acceptance of technology in business, education and other domains. This research study is an attempt that tests the integration of TAM and user satisfaction in the educational field. It particularly investigates students' acceptance to use MyMathLab, a technological tool, in university math classes in the Middle East. Structural equation modelling with various constructs was used. Findings support the theoretical model showing the great influence of user satisfaction on perceived ease of use and subjective norm on behavioural intention. The findings of this study also demonstrate that selfefficacy, user satisfaction, subjective norms, perceived usefulness, perceived ease of use, and students' attitude constructs all have a positive impact on students' behavioural intentions to adopt and use technological tools in a mathematics class room. Findings of this research have greater implications for educators and students worldwide.

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Measuring General Computer Self-Efficacy: The Surprising Comparison of Three Instruments in Predicting Performance, Attitudes, and Usage

Cited by 19 publications

References 36 publications

Technology, Demographic Characteristics and E-Learning Acceptance: A Conceptual Model Based on Extended Technology Acceptance Model

Technology, Demographic Characteristics and E-Learning Acceptance: A Conceptual Model Based on Extended Technology Acceptance Model

Understanding the Influence of Perceived Usability and Technology Self-Efficacy on Teachers’ Technology Acceptance

University Student Perceptions of Technology Use in Mathematics Learning

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