设计和评估一个修订的ARCS动机模型,用于高等教育中的在线课程
Monica Maiti1, M Priyaadharshini1, Harini S1
1VIT University, Chennai, Tamil Nadu, India.
Heliyon
|December 25, 2023
概括
一个修改后的ARCS-PC模型增强了在线学习参与度和学生表现. 与传统方法相比,这种结合数字工具和专注于专业能力的方法提高了11.21%的学生成绩.
科学领域:
- 教育技术的教育技术
- 在线学习策略 在线学习策略
- 基于能力的教育 基于能力的教育
背景情况:
- 大规模开放在线课程 (MOOCs) 对于提高技能越来越受欢迎.
- 在线学习已经成为'新常态',需要更新教学策略.
- 辅导员必须积极地让学习者参与在线环境.
研究的目的:
- 评估在线课程中的学习者能力和动机.
- 引入一个修改后的动机模型,ARCS-PC (注意力,相关性,信心,满意度 - 专业能力).
- 提高专业能力技能,包括批判性思维,数字素养,创造力,解决问题和时间管理.
主要方法:
- 实施了ARCS-PC模型,包括数字测试,作业和交互式ICT活动.
- 通过微软团队 (MS Teams) 进行在线讲座和活动.
- 使用线性回归来分析ARCS-PC模型.
主要成果:
- 该ARCS-PC模型有效地让学生参与在线课程.
- 支持技术的课堂培养了终身学习,协作学习和以学生为中心的方法.
- 通过拟议的方法观察到学生成绩有11.21%的改善.
结论:
- 修改后的ARCS-PC模型显著提高了在线学习中的学生表现.
- 整合ICT和专注于专业能力是成功在线教育的关键.
- 拟议的方法为传统的在线学习模式提供了一种优越的方法.
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