基于信息熵和动态积累水平的学习性能评价方法

Li-ling Yang, Chieh Hsu
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引用次数: 0

摘要

一般来说,学习评价大多采用算术平均分或加权平均分来衡量学生的学习效果。虽然评估过程简单易懂,但不够灵活,容易忽视学习过程中的真实情况。因此,它无法有效地描述学习过程中进步、回归或成绩分布是否稳定。本研究提出了学习评价的“动态积累水平”,通过指数平滑法计算考试成绩的动态积累,并引入“信息熵”来衡量学生的学习稳定性和学习水平。此外,本文还提出了动态稳定性评价方法,对学生的学习状况和成绩进行了更真实、更准确的分析。通过动态稳定性评价方法,教师可以及时调整自己的教学技巧,更有效地辅导学生,提高学习质量。Keywords-information熵;动态积累水平;学习的表现
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Better Method for Evaluating Learning Performance Based on Information Entropy and Dynamic Accumulation Level
In general, most of the learning assessment measures students' learning effectiveness by arithmetic average score or weighted average score. Although the assessment process is simple and easy to understand, it is not flexible and tends to ignore the real situation in the learning process. Therefore, it is unable to effectively describe whether progress, regression or grade distribution is stable in the learning process. This study puts forward "dynamic accumulation level" for learning evaluation, calculates the dynamic accumulation of the examination results through exponential smoothing method, and introduces "information entropy" to measure students' learning stability and learning level. Moreover, this paper promotes the thesis of dynamic stability evaluation method, which analyzes more realistically and precisely on students' learning condition and performance. With the dynamic stability evaluation method, teachers may timely adjust their teaching skills and counsel students in a more effective way to enhance the quality of learning. Keywords—information entropy; dynamic accumulation level; learning performance
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