Impact of step-based tutoring on student learning in linear circuit courses
Impact of step-based tutoring on student learning in linear circuit courses
复制标题
分步辅导对学生线性电路课程学习的影响
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
Daniel H. Robinson
中科院分区：
文献类型：
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作者：
B. Skromme;V. Seetharam;Xuefeng Gao;Bhargav Korrapati;B. McNamara;Yih;Daniel H. Robinson
为了提高学生在初级线性电路分析课程中的学习效果，我们设计了一套分步教学系统。这种方法是基于在相同类型的问题解决练习中交替观看工作示例或解决方案的重要性，以避免在学习新技能时过度的认知负荷。该系统可以生成无限的电路问题（具有随机变化的拓扑结构），类似于教科书中的问题，以及相应的直流，交流和瞬态分析的完整解释解决方案。求解方法和主题包括电压和电流划分、节点和网格分析、叠加、thsamvenin和Norton等效、Bode图和拉普拉斯分析。在使用系统时，使用特殊的教学设备来减少不必要的认知负荷，例如对节点和方程项进行颜色编码。定性概念的主题，如串联和并联连接给予特别强调。迄今为止，该系统已被10所不同类型的学院和大学的71个班级的2860多名学生使用，学生评分普遍很好。评估包括在实验室和课堂环境中进行的一系列随机对照试验，以严格评估学生的学习成果以及材料对学生动机和偏好的影响。与基于出版商的家庭作业系统相比，节点分析的学习效率提高了0.72个标准偏差，与论文练习相比，串联和并行元素识别的标准偏差提高了0.97个标准偏差。
A step-based tutoring system is being developed to improve student learning in elementary linear circuit analysis courses. The approach is based on the known importance of viewing worked examples or solutions in alternation with problem-solving exercises of the same type, to avoid excessive cognitive loads when learning a new skill. The system can generate an unlimited supply of circuit problems (with randomly varying topologies) similar to those in textbooks and corresponding fully explained solutions for both DC, AC, and transient analysis. Solution methods and topics include voltage and current division, node and mesh analysis, superposition, Thévenin and Norton equivalents, Bode plots, and Laplace analysis. Special pedagogical devices are used to reduce extraneous cognitive load when using the system, such as color-coding nodes and equation terms. Qualitative conceptual topics such as series and parallel connections are given special emphasis. The system has been used to date by over 2860 students in 71 class sections at 10 different colleges and universities of widely varying types, with generally very favorable student ratings. Evaluation has included a series of randomized, controlled trials in both laboratory and classroom settings to rigorously assess student learning gains as well as the impact of the materials on student motivation and preferences. Learning improvements of 0.72 std. deviations are found in comparison to a publisher-based homework system for node analysis, and 0.97 std. deviations for identification of elements in series and parallel compared to paper exercises.