首页> 外文期刊>Education and information technologies >M-learning adoption of management students': A case of India
【24h】

M-learning adoption of management students': A case of India

机译:M-Learning采用管理学生:印度案例

获取原文
获取原文并翻译 | 示例
       

摘要

The present study aims to interpret management student's motivation to adopt m-learning and assesses the determinates impacting the behavioral intent of m-learning adoption. A comprehensive research archetype is proposed by integrating two prominent theoretical models, namely UTAUT and UGT. The research model is tested using multi-analytic structural equation modeling (SEM) and advanced neural network (ANN) approach. The quantitative data was gathered and measured from 220 management students. The study outcomes reported that affective need, performance expectancy, effort expectancy, social influence and facilitating conditions positively impacted the student's intent to use m-learning, whereas cognitive need was found to be insignificant in predicting and explicating the m-leaming adoption. The results of sensitivity analysis revealed that effort expectancy showed the highest normalized importance (100%) followed by performance expectancy (97.2%) in explicating the m-learning adoption. The research archetype was able to elucidate 66% of variance in student's intent towards m-learning adoption. In addition to that, Cohen's f-square statistic resulted in effect size as 0.771 indicating that the study findings were relevant and substantial with the empirical data collected. Conclusively, the theoretic and managerial implications are described for the proposed model.
机译:本研究旨在解释管理学生采用M-Learning的动机,并评估影响M学习采用的行为意图的决定。通过整合两个突出的理论模型,即Utaut和UGT来提出全面的研究原型。使用多分析结构方程建模(SEM)和先进的神经网络(ANN)方法进行测试。从220名管理学生收集和衡量定量数据。研究结果报告说,情感需求,性能预期,努力预期,社会影响力和促进条件对学生的使用M-Learning产生了积极影响,而认知需要在预测和透析M-Leaming采用方面是微不足道的。敏感性分析结果表明,努力期望率显示出最高的归一化重要性(100%),然后进行绩效预期(97.2%)在阐述M学习采用时。该研究模拟能够阐明学生意图阐明的66%的差异,对M学习采用。除此之外,Cohen的F-Square统计结果效果大小为0.771,表明研究结果与收集的经验数据相关和大幅值。结论,描述了所提出的模型的理论和管理的影响。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号