Comparative assessment method between neural network & rubric

Punyapat Chanpet, K. Chomsuwan
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Abstract

This study aimed to design and develop to an E-portfolio assessment system on Project-based learning approach to teaching and learning oriented assessment. The researcher considered 60 pre-service senior teachers from two classes in university particularly on instruction media courses. The control group comprised 30 pre-service teachers who used E-portfolio system and analytic rubric assessment that was a coherent set of criteria for students' work. It included descriptions of levels of performance quality on the criteria. The experimental group comprised 30 pre-service teachers that served as who used E-portfolio system and neural network assessment. Neural Networks was a model of the work of human brain by using computer. It made computer as clever as the human learning, and trained to classify the data mining in E-portfolio. Experimental results indicate that the E-portfolio assessment system has no significant effect on pre-service teacher achievement, positive effect on self-learning. In addition, rubric assessment and neural network assessment of project-based learning achievements produced different results.
神经网络与规则的比较评价方法
本研究旨在设计并开发一套以专案为基础的电子档案评估系统,以教学与学习为导向的评估方法。研究人员选取了大学两个班的60名职前高级教师,特别是在教学媒体课程上。控制组由30名职前教师组成,他们使用电子档案系统和分析性标题评估,这是一套连贯的学生工作标准。它包括对标准的性能质量水平的描述。实验组由30名职前教师组成,采用电子档案系统和神经网络评估。神经网络是一种利用计算机模拟人脑工作的模型。它使计算机像人类学习一样聪明,并对电子投资组合中的数据挖掘进行分类训练。实验结果表明,电子档案袋评估系统对职前教师的学业成就无显著影响,对自主学习有正向影响。此外,基于项目的学习成果的标题评价和神经网络评价也产生了不同的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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