Research on College English Teaching Quality Assessment Method Based on K-Means Clustering Algorithm

Author:

Lang Wang1ORCID

Affiliation:

1. School of International Studies, Jingdezhen Ceramic University, Jingdezhen 333403, Jiangxi, China

Abstract

The evaluation of college teachers’ teaching ability is very important. Currently, the indicators for evaluating the quality of college English teaching are unclear and insufficient. This paper evaluates the quality of university classroom teaching from two aspects: students’ learning effect and teachers’ teaching work. This paper employs the K-means algorithm to analyze the relationship between the indicators in the evaluation model and teachers’ teaching ability, finds out the specific factors that affect teaching activities, and guides the implementation of teachers’ teaching work. At the same time, the K-means model is used to evaluate students’ learning effect, identify the relationship between the indicators in the model and teachers’ teaching ability, and find out the specific factors that affect teachers to guide the implementation of teachers’ teaching work. Experiments show that the method proposed in this paper can solve the problem that the evaluation indicators of traditional evaluation methods are not clear and insufficient and can be better applied to teaching evaluation.

Publisher

Hindawi Limited

Subject

General Engineering,General Mathematics

Reference16 articles.

1. Selection of learning parameters for CMAC-based adaptive critic learning

2. Applications of the self-organising map to reinforcement learning

3. Online adaptive algorithm for optimal control with integral reinforcement learning

4. The parti-game algorithm for variable resolution reinforcement learning in multidimensional state-spaces;A. Moore;Advances in Neural Information Processing Systems,1993

5. Tree-based policy learning in continuous domains through teaching by demonstration;S. Chernova

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3