Quantitative Assessment of Medical Student Learning through Effective Cognitive Bayesian Representation
Quantitative Assessment of Medical Student Learning through Effective Cognitive Bayesian Representation
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通过有效的认知贝叶斯表示对医学生学习进行定量评估
DOI：
10.5539/ies.v7n6p86
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Jingyan Lu
中科院分区：
文献类型：
--
作者：
Zhidong Zhang;Jingyan Lu
学习环境的变化和学习理论的发展越来越需要能够描述学习进展轨迹的反馈。有效的评估应该能够评估学习者如何获得知识和发展解决问题的技能。此外，它应该确定这些学习者在学习过程中有什么问题，以及他们为什么会有这些问题。本研究将认知任务的视觉表征描述为连接学习和评估的关键点。本研究是对复杂学习环境中这些认知任务的探索，并在认知结构中对这些可测量对象进行定量表征。
The changes of learning environments and the advancement of learning theories have increasingly demanded for feedback that can describe learning progress trajectories. Effective assessment should be able to evaluate how learners acquire knowledge and develop problem solving skills. Additionally, it should identify what issues these learners have during the learning processes and why they have these issues. This study depicts visual representations of cognitive tasks as crucial points to connect learning and assessment. This study is an exploration of these cognitive tasks in complex learning environments and a quantitative representation of these measureable objects in cognitive structures.