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首页> 外文期刊>Knowledge Management & E-Learning: An International Journal >Utilization decision towards LMS for blended learning in distance education: Modeling the effects of personality factors in exclusivity
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Utilization decision towards LMS for blended learning in distance education: Modeling the effects of personality factors in exclusivity

机译:远程教育中混合学习的LMS利用决定:在排他性中建模人格因素的影响

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Over the decades, personality factors (attitude, self-efficacy, anxiety and computer experience) have pervaded the underpinning determinants of behavioural intentions to accept and use emerging technologies, chiefly in purviews where integration is into the working processes that may be pro traditional. The chasm in the literature has been how these technology personality factors extensively relate within and among themselves in a definite model exclusive to these factors, and their overall variance explained in usage intentions. In view of this, the study adopted a quantitative design and employed the questionnaire for data collection from 267 distance education tutors from a countrywide spread. Findings from structural equation modeling (SEM) technique revealed 'technology attitude' and 'technology experience' to be major predictors of usage intentions. The direct effects of technology anxiety and self-efficacy on behavioural intention were fully mediated by technology attitude. Non-linear relationships showed that technology selfefficacy, experience and anxiety were all antecedents of attitude towards LMS, while 'technology experience' alone determined 'technology self-efficacy'. The Important-Performance Map Analysis (IPMA) revealed attitude as the most important and performing construct in determining behavioural intention. Technology attitude had technology related self-efficacy as its most important and performing construct determinant. The overall variance explained by the derived model was 35%. The study recommended that technology attitude and experience should be prioritized in LMS-related blended learning implementation in distance education. It further proposed that future studies include moderators on technology personality factors in determining usage intentions to further improve the model's robustness.
机译:几十年来,人格因素(态度,自我效力,焦虑和计算机经验)遍历了行为意图的支撑决定因素,接受和使用新兴技术,主要是在Pureviews,其中一体化进入了可能是职业传统的工作流程。文献中的鸿沟一直是如何在对这些因素专用的明确模型中广泛地联系在一起,以及它们在使用意图中解释的整体方差。鉴于此,该研究采用了定量设计,并聘请了来自267名远程教育导师的数据收集问卷。结构方程建模(SEM)技术的调查结果显示了“技术态度”和“技术经验”成为使用意图的主要预测因子。技术焦虑和自我效能对行为意向的直接影响得到了技术态度。非线性关系表明,技术的自息,经验和焦虑是对LMS态度的所有前辈,而“技术经验”单独确定“技术自我效能”。重要绩效地图分析(IPMA)透露了态度,作为确定行为意图中最重要和最重要的构造。技术态度具有技术相关的自我效能,是其最重要和最重要的构建决定因素。衍生模型解释的整体方差为35%。该研究建议在远程教育中的LMS相关混合学习实施中优先考虑技术态度和经验。它进一步提出了未来的研究包括技术人格因素的主持人,以确定使用意图进一步提高模型的鲁棒性。

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