在数字环境中测量遗产学习的校准尺度. 一个网络分析方法的方法
Olaia Fontal1, Alex Ibañez-Etxeberria2, Víctor B Arias3
1Didactics of Musical, Plastic and Corporal Expression, University of Valladolid, Campus Miguel Delibes, Valladolid, 47011, Spain.
Heliyon
|November 19, 2024
概括
本研究介绍了在数字环境中评估遗产学习的网络分析,验证了可靠和准确测量的新方法. 研究结果显示,网络结构稳定,为未来数字遗产教育研究铺平了道路.
科学领域:
- 数字人文学科 数字人文学科
- 教育测量教育的测量
- 文化遗产研究 文化遗产研究
背景情况:
- 关于在数字环境中对遗产学习评估的验证工具的研究有限.
- 网络分析方法在遗产学习研究中未得到充分利用.
研究的目的:
- 通过将网络分析应用于遗产学习评估来弥补研究缺口.
- 开发和验证数字遗产学习的测量工具.
- 调查遗产学习维度的结构和不变性.
主要方法:
- 使用高斯图形模型和规范化的网络分析方法.
- 分析了1323名参与者对遗产学习序列七个维度的反应.
- 通过网络估计和稳定性分析,确保准确性,有效性和可靠性.
主要成果:
- 实现了令人满意的网络结构,可预测性,可复制性和灵敏性.
- 在不同的人口群体 (男性/女性) 和随机子样本中证明了网络结构的不变性.
- 验证了网络分析用于遗产学习评估的应用.
结论:
- 网络分析为评估数字环境中的遗产学习提供了强大的方法.
- 开发的仪器显示出有希望的准确性,有效性和可靠性.
- 这些发现支持进一步研究使用网络分析对数字遗产教育评估的研究.
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