中央棉兰老大学高中生国家成就测试成绩模型研究

Nathalie Joy G. Casildo, K. L. Bonifacio, Gladys S. Ayunar, M. R. Aguirre
{"title":"中央棉兰老大学高中生国家成就测试成绩模型研究","authors":"Nathalie Joy G. Casildo, K. L. Bonifacio, Gladys S. Ayunar, M. R. Aguirre","doi":"10.52751/vquk7429","DOIUrl":null,"url":null,"abstract":"The study is entitled Modeling the Performance of Senior High School Students’ National Achievement Test Performance in Central Mindanao University. It aims to develop a predictive model of the National Achievement Test performance of Senior High School students. The study intends to extract predictive features of students' National Achievement Test performance, find the extent of the relationship between the students' academic performance in the previous and current year to their National Achievement Test performance, and recommend pedagogical interventions concerning National Achievement Test performance's predictive features. There were two types of datasets, National Achievement Test and Periodic grades of batch 2017 – 2018 when they were in Grade 11 and Grade 12 before taking the National Achievement Test. After the data is collected, the Feature selection and Logistic regression model is applied using the data mining process's rapid miner application. Out of 30 attributes, there are only 14 subjects selected by the feature selection technique. The feature selection selected those subjects which contributed to the prediction. We found out that Philosophy and Arts in the Last Quarter and Semester before the National Achievement Test exam has the most significant effect on the National Achievement Test Result. This study was based on a CMU-funded research entitled Leveraging Educational Data Mining and Machine Learning Techniques in Developing Strategic Interventions for Senior High School Students.","PeriodicalId":429775,"journal":{"name":"Central Mindanao University Journal of Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Modeling the Performance of Senior High School Students’ National Achievement Test Performance in Central Mindanao University\",\"authors\":\"Nathalie Joy G. Casildo, K. L. Bonifacio, Gladys S. Ayunar, M. R. Aguirre\",\"doi\":\"10.52751/vquk7429\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The study is entitled Modeling the Performance of Senior High School Students’ National Achievement Test Performance in Central Mindanao University. It aims to develop a predictive model of the National Achievement Test performance of Senior High School students. The study intends to extract predictive features of students' National Achievement Test performance, find the extent of the relationship between the students' academic performance in the previous and current year to their National Achievement Test performance, and recommend pedagogical interventions concerning National Achievement Test performance's predictive features. There were two types of datasets, National Achievement Test and Periodic grades of batch 2017 – 2018 when they were in Grade 11 and Grade 12 before taking the National Achievement Test. After the data is collected, the Feature selection and Logistic regression model is applied using the data mining process's rapid miner application. Out of 30 attributes, there are only 14 subjects selected by the feature selection technique. The feature selection selected those subjects which contributed to the prediction. We found out that Philosophy and Arts in the Last Quarter and Semester before the National Achievement Test exam has the most significant effect on the National Achievement Test Result. This study was based on a CMU-funded research entitled Leveraging Educational Data Mining and Machine Learning Techniques in Developing Strategic Interventions for Senior High School Students.\",\"PeriodicalId\":429775,\"journal\":{\"name\":\"Central Mindanao University Journal of Science\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Central Mindanao University Journal of Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.52751/vquk7429\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Central Mindanao University Journal of Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.52751/vquk7429","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本研究题目为《棉兰老中央大学高中生国家成就测试成绩的建模》。本研究旨在建立高中生国家成就测试成绩的预测模型。本研究旨在提取学生国家成就测试成绩的预测特征,发现学生上一年和当年学业成绩与国家成就测试成绩的关系程度,并建议有关国家成就测试成绩预测特征的教学干预措施。有两种类型的数据集,国家水平测试和2017 - 2018批次的定期成绩,当时他们在参加国家水平测试之前是11年级和12年级。数据采集完成后,利用数据挖掘过程的快速挖掘应用,应用特征选择和逻辑回归模型。在30个属性中,特征选择技术只选择了14个主题。特征选择选择那些有助于预测的主题。我们发现,在国家水平测试考试前最后一个季度和学期的哲学和艺术对国家水平测试成绩的影响最为显著。这项研究基于cmu资助的一项名为“利用教育数据挖掘和机器学习技术为高中生制定战略干预措施”的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling the Performance of Senior High School Students’ National Achievement Test Performance in Central Mindanao University
The study is entitled Modeling the Performance of Senior High School Students’ National Achievement Test Performance in Central Mindanao University. It aims to develop a predictive model of the National Achievement Test performance of Senior High School students. The study intends to extract predictive features of students' National Achievement Test performance, find the extent of the relationship between the students' academic performance in the previous and current year to their National Achievement Test performance, and recommend pedagogical interventions concerning National Achievement Test performance's predictive features. There were two types of datasets, National Achievement Test and Periodic grades of batch 2017 – 2018 when they were in Grade 11 and Grade 12 before taking the National Achievement Test. After the data is collected, the Feature selection and Logistic regression model is applied using the data mining process's rapid miner application. Out of 30 attributes, there are only 14 subjects selected by the feature selection technique. The feature selection selected those subjects which contributed to the prediction. We found out that Philosophy and Arts in the Last Quarter and Semester before the National Achievement Test exam has the most significant effect on the National Achievement Test Result. This study was based on a CMU-funded research entitled Leveraging Educational Data Mining and Machine Learning Techniques in Developing Strategic Interventions for Senior High School Students.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信