教程粘性的混合模式

IF 0.7 Q4 EDUCATION, SCIENTIFIC DISCIPLINES Voprosy Obrazovaniya-Educational Studies Moscow Pub Date : 2022-01-01 DOI:10.17323/1814-9545-2022-3-7-35
A. Globa
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引用次数: 2

摘要

技术日益成为教学和学习的关键组成部分,特别是由于2019冠状病毒病(COVID-19)大流行正在迅速转向通过在线平台提供。在2020-2022年期间,在线学习的学生往往难以取得关键的学习成果,分数也低于在校学生,这表明他们在网络环境中的参与度降低。悉尼大学建筑、设计和规划学院共同关注的是为在线学习的学生提供物理体验的能力。本文详细介绍了我们提出的解决方案,通过“混合模型”提高在线教程的参与度:利用快速发展的虚拟现实技术;整合游戏化的基本原则,并将体验式学习融入学习过程。推荐的教程结构或时间比例模型进一步支持这三个关键领域。手稿提出了发展的理论混合模型告知现有的文献和研究;并通过实际实施和初步概念验证研究的例子来说明这一理论。手稿进一步讨论了未来的研究,将集中在深入的用户研究和方法的严格评估。
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Hybrid Model for Tutorial Engagement
Technology has increasingly become a key component of teaching and learning, particularly with the rapid shift to delivery through online platforms as a result of the ongoing COVID-19 pandemic. In 2020–2022, students who studied online often struggled to achieve key learning outcomes and receive lower marks than their on-campus peers, demonstrating reduced engagement in an online environment. A shared concern identified within the School of Architecture, Design, and Planning at the University of Sydney, was the ability to deliver a sense of physical experience to students who are studying online. This paper details our proposed solution to improve engagement in online tutorials through a "Hybrid Model" that: leverages rapidly advancing virtual reality technology; integrates the fundamental principles of gamification and incorporates experiential learning into the learning process. These three key areas are further supported by a recommended tutorial structure or time proportion model. The manuscript presents the developed theoretical hybrid model informed by existing literature and studies; and illustrates this theory by examples of practical implementation and initial proof-of-concept studies. The manuscript further discusses future research that will focus on in-depth user studies and rigorous evaluation of the approach.
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来源期刊
Voprosy Obrazovaniya-Educational Studies Moscow
Voprosy Obrazovaniya-Educational Studies Moscow EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
2.20
自引率
42.90%
发文量
23
期刊最新文献
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