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Exploratory centered PCA for dimensionality reduction on security modelling of TAM: An e-learning perspective

机译:以探索性为中心的PCA,以减少TAM的安全性模型的维数:电子学习的角度

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Software organizations and educational institutions rely heavily upon e-learning technologies nowadays. There is a requirement to know how numerous interventions can influence the recognized determinants of IT design, acceptance and usage. The statistical meta-analysis of several prototypes, particularly the technology acceptance model (TAM) studies have shown that it is a valid and robust model that has been very widely used, but which hypothetically has broader applicability. Though TAM has been considered to be one of the most widely used models in Information Systems and Technology, however, it is imperfect. There have been numerous researches in TAM involving students, professionals and general users. There are no studies till date that have considered into the trait of trust, perceived security, perceived privacy and information quality in e-learning technologies. To address this gap in the literature, the research work tries to draw from the existing research, particularly the work on the determinants of perceived usefulness and perceived ease of use, and to develop a more robust model. The research work aims in calculating the validity of the data using Cronbach's alpha on the data set. Dimensionality reduction of the data is attempted by using Principal Component Analysis (PCA). This method of Dimensionality reduction offers a robust way of factor identification by constructing Rotated Component matrices, and by thus proposing an efficient user-centric design model for software establishments and educational institutions in evolving e-learning solutions. The results of the proposed research would append up literature to the design and implementation phases of software engineering concepts.
机译:如今,软件组织和教育机构严重依赖电子学习技术。需要了解大量干预措施如何影响公认的IT设计,接受和使用的决定因素。几个原型的统计荟萃分析,尤其是技术接受模型(TAM)研究表明,它是一种有效而强大的模型,已被广泛使用,但假设其具有更广泛的适用性。尽管TAM被认为是信息系统和技术中使用最广泛的模型之一,但是它并不完善。在TAM中有许多研究涉及学生,专业人员和一般用户。到目前为止,还没有研究考虑到电子学习技术中信任,感知安全性,感知隐私和信息质量的特征。为了弥补文献中的这一空白,研究工作试图从现有研究中汲取经验,尤其是关于确定有用性和易用性的决定因素的工作,并开发出更可靠的模型。该研究工作旨在使用数据集上的Cronbach's alpha计算数据的有效性。通过使用主成分分析(PCA)尝试减少数据的维数。这种降维方法通过构造旋转组件矩阵,从而为不断发展的电子学习解决方案的软件机构和教育机构提出了一种以用户为中心的高效设计模型,从而提供了一种可靠的因子识别方法。拟议研究的结果将把文献补充到软件工程概念的设计和实施阶段。

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