首页> 外文会议>Yogyakarta International Conference on Educational Management/Administration and Pedagogy >Analyzing Student Readiness of e-Learning Implementation in Middle School
【24h】

Analyzing Student Readiness of e-Learning Implementation in Middle School

机译:分析中学电子学习实施的学生准备

获取原文

摘要

E-learning is a widely developed mean to support learning process in class. However, student readiness may hinder its application, thus results in its deployment failure. One of the methods to assess student readiness is blended learning model from Tang and Chaw. This model analyzes student readiness by measuring how each student behaves towards six learning aspects namely learning flexibility, online learning, study management, technology, online interaction, and classroom learning. To this point, we investigate the application of blended learning model in SMP Negeri 1 Jember, a middle school in Jember. We collect questionnaire data from the students after delivering one day's intensive training. Afterwards, we analyze the collected data using Generalized Structured Component Analysis (GeSCA) Software to understand the interdependency relationships among prescribed variables. From the analysis, we could individually gauge prescribed variables using e-Learning readines systems by Aydin and Tasci. This measurement is useful to categorize organization readiness level (from low to advance). In the end, we have found that 1) SMP Negeri 1 Jember is ready for e-learning implementation with minor fixes 2) There are four significant factors which contribute to student readiness namely Attitude towards learning flexibility, Attitude towards study management, Blended learning adaptability, and Attitude towards classroom learning 3) We also prescribe some recomendations to enhance student readiness in the elearning implementation.
机译:电子学习是一种广泛发展的意思,可以在课堂上支持学习过程。但是,学生准备就可以妨碍其应用,从而导致其部署失败。评估学生准备的方法之一是从唐和尖的学习模型混合。该模型通过测量每个学生对六个学习方面的行为如何,即学习灵活性,在线学习,学习管理,技术,在线互动和课堂学习来分析学生愿意。为此,我们调查混合学习模型在九年九所在中学的SMP Negeri 1 Jember。我们在提供一天的密集培训后从学生收集调查问卷数据。之后,我们使用广义结构分量分析(GESCA)软件来分析收集的数据,以了解规定变量之间的相互依赖关系。从分析中,我们可以使用Aydin和Tasci使用电子学习Readines系统单独衡量规定的变量。该测量可用于将组织准备水平分类(从低预期)进行分类。最终,我们已经发现了1)SMP Negeri 1 Jember已准备好进行电子学习实施与次要修复2)有四个重要因素有助于学生准备就绪,即学习灵活性,态度对学习管理,混合学习适应性和对课堂学习的态度3)我们还规定了一些重新推荐,以提高学生准备就绪。

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