迈向一个支持学习的评分模型 生物学课程 课程
Stacy C Farina1, Catherine L Quinlan2
1Department of Biology, Howard University, Washington DC 20059, USA.
Integrative and comparative biology
|September 20, 2025
概括
这项研究探讨了高级生物学课程的创新分级,从传统方法转向开放的图形. 这种方法支持学生的代理和学习进步,即使在表现不佳后.
科学领域:
- 生物教育教育 生物学教育
- 认知科学在教育中的应用
背景情况:
- 高级生物学课程提出了重大学习挑战,COVID-19大流行加剧了这一挑战.
- 传统的分数可能不完全支持学生的学习进度或代理.
研究的目的:
- 调查高级生物学课程中开放分级方案的实施和影响.
- 为了使评分实践与知识获取的认知理论保持一致.
- 促进学生在STEM科目中的学习,改进和留学.
主要方法:
- 在两个高级生物学课程中分析观点和课程程序.
- 从传统的分级过渡到一个更开放的分级方案.
- 新模型与应用认知理论的调整.
主要成果:
- 开放的分级方案促进了学生的重大变化和学习.
- 该模型为学生提供了重新访问和改善对挑战性领域的理解的机会.
- 这种方法赋予学生权力,并支持他们在学习过程中发挥作用.
结论:
- 重组分级方案可以有效地解决高级生物学课程中的挑战.
- 一个开放的分级模型,由认知科学提供信息,促进更深入的学习和记忆.
- 这种方法为专注于学生进步的STEM教育工作者提供了一个有价值的替代方案.
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