Comparison of Three Learner Profiles under the Influence of the Double Reduction Policy — Evidence from the K-means Clustering Approach

Qinglin Huang, Zhili Zhang, Siyi Jiang, X. Liao, Heng Luo
{"title":"Comparison of Three Learner Profiles under the Influence of the Double Reduction Policy — Evidence from the K-means Clustering Approach","authors":"Qinglin Huang, Zhili Zhang, Siyi Jiang, X. Liao, Heng Luo","doi":"10.1109/IEIR56323.2022.10050061","DOIUrl":null,"url":null,"abstract":"The “double reduction” policy is a national educational policy issued by the Chinese government in 2021, aiming to reduce the amount of homework and study time of K-12 students. In this study, we collected various data on students’ demographic characteristics, learning patterns, and learning perceptions under the “double reduction” policy using a self-developed questionnaire, and obtained their standardized semester-end test results as measurement of learning outcomes. A total of 8100 5th graders from 45 primary schools in a school district in Wuhan participated in this study. Based on the K-means clustering results, we classified the students into three profile categories: Challenged Learners, Policy Followers, and Competitive Learners and further compared the three learner profiles to identify differences in learning load, learning motivation, and learning outcomes. The study results inform individualized education to accommodate profile differences and inform the sustainable implementation and refinement of the “double reduction” policy.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEIR56323.2022.10050061","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The “double reduction” policy is a national educational policy issued by the Chinese government in 2021, aiming to reduce the amount of homework and study time of K-12 students. In this study, we collected various data on students’ demographic characteristics, learning patterns, and learning perceptions under the “double reduction” policy using a self-developed questionnaire, and obtained their standardized semester-end test results as measurement of learning outcomes. A total of 8100 5th graders from 45 primary schools in a school district in Wuhan participated in this study. Based on the K-means clustering results, we classified the students into three profile categories: Challenged Learners, Policy Followers, and Competitive Learners and further compared the three learner profiles to identify differences in learning load, learning motivation, and learning outcomes. The study results inform individualized education to accommodate profile differences and inform the sustainable implementation and refinement of the “double reduction” policy.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
双约策略下三种学习者特征的比较——来自k均值聚类方法的证据
“双减”政策是中国政府于2021年出台的一项国家教育政策,旨在减少K-12学生的家庭作业量和学习时间。在本研究中,我们采用自行设计的调查问卷,收集了“双减”政策下学生的人口统计学特征、学习模式和学习感知的各种数据,并获得了学生标准化期末考试成绩作为学习成果的衡量标准。武汉市某学区45所小学的8100名五年级学生参与了本研究。基于K-means聚类结果,我们将学生分为三种类型:挑战型学习者、政策追随者和竞争型学习者,并进一步比较了三种学习者类型,以确定学习负荷、学习动机和学习成果的差异。研究结果为个性化教育提供了信息,以适应个人特征差异,并为“双减”政策的可持续实施和完善提供了信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Is the Research on AI Empowered Pedagogy in China Decaying? Explore the interrelationship of cognition, emotion and interaction when learners engage in online discussion Solving Word Function Problems in Line with Educational Cognition Way Comparative Analysis of Problem Representation Learning in Math Word Problem Solving Prompt-Based Missing Entity Recovery for Solving Arithmetic Word Problems
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1