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The two perfect scorers for technology acceptance

机译:技术验收的两个完美评分

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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.
机译:本研究论文探讨了高中学生和大学新手学习技术的接受。该研究的目标是衡量计算机能力,计算机的自我效能,对选定的学生队列的接受学习技术。该研究采用扩展技术验收模型(TAM),具有两种额外的属性,计算机能力和计算机自我效能,以研究学生对学习技术的行为。收集两套数据;一年是来自斐济三中学的12年级和13名学生,另一所学生,另一所区域大学的新人在南太平洋。与单极李克特量表1-5问卷调查,队列进行了调查。使用“社会科学统计包”分析结果 - 使用智能偏最小二乘(SmartPLS)软件分析SPSS软件和所提出的扩展TAM模型。回归分析的结果证实,两种属性对技术接受具有显着的积极影响,即计算机能力和计算机自我效能是学生继续使用技术的意图的重要预测因素。因此,在本文中设计和介绍了一种包含两个完美分光仪的新模型。 Cronbach的alpha的高值也表明结果是可靠的和有效的。最后,研究表明,计算机能力和计算机自我效力是对学习技术的不断使用的基本贡献者。

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