The two perfect scorers for technology acceptance

Reddy, Pritika and Chaudhary, Kaylash C. and Sharma, Bibhya N. and Chand, Ronil (2021) The two perfect scorers for technology acceptance. Education and Information Technologies, 26 . pp. 1505-1526. ISSN 1360-2357

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Abstract

This research paper examines the acceptance of technology for learning by senior secondary school students and university newcomers. The objectives of the study are to measure the computer competency, computer self-efficacy of selected student cohorts on the acceptance of technology for learning. The study uses the extended Technology Acceptance Model (TAM) with two additional attributes, computer competencies and computer self-efficacies to examine students’ behavior towards learning with technology. Two sets of data were collected; one was from Year 12 and Year 13 students from 33 secondary schools in Fiji, and the other from newcomers of a regional university in the South Pacific. The cohorts were surveyed with a unipolar Likert scale 1–5 questionnaire. The results were analysed using the “Statistical Package for the Social Sciences” – SPSS software and the proposed extended TAM model was analysed using the Smart Partial least squares (SmartPLS) software. The results from the regression analysis confirmed that the two attributes had a significant positive impact on the acceptance of the technology, that is, computer competency and computer self – efficacy were significant predictors of students’ intention to continue using technology for learning. Therefore, a new model incorporating the two perfect scorers is designed and presented in this paper. The high values for Cronbach’s alpha also show that the results were reliable and valid. Finally, the study shows that computer competencies and computer self-efficacies are essential contributors to the continuous use of technology for learning.

Item Type:	Journal Article
Subjects:	L Education > L Education (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Divisions:	School of Information Technology, Engineering, Mathematics and Physics (STEMP)
Depositing User:	Ms Shalni Sanjana
Date Deposited:	21 Mar 2021 23:41
Last Modified:	17 Feb 2022 22:26
URI:	https://repository.usp.ac.fj/id/eprint/12720

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