Concept Maps Construction Based on Student-Problem Chart

J. Shieh, Yi-Ting Yang
{"title":"Concept Maps Construction Based on Student-Problem Chart","authors":"J. Shieh, Yi-Ting Yang","doi":"10.1109/IIAI-AAI.2014.73","DOIUrl":null,"url":null,"abstract":"Concept maps can help students learn more meaningfully. According to test scores only, students were divided into three groups of high-score, middle-score and low-score, in the previous works, researchers then applied data mining association rule technique to analysis different student groups' assessment data to construct corresponding concept maps. However, for considering more accurate to evaluate students' performance states and various possible distributions of students' assessment data, in this research, we apply student-problem chart to obtain students response patterns for grouping purpose. We generate six response pattern groups for 30131 students. Using association rule data mining technique also, we will construct more precise concept maps for students of different groups individually.","PeriodicalId":432222,"journal":{"name":"2014 IIAI 3rd International Conference on Advanced Applied Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IIAI 3rd International Conference on Advanced Applied Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IIAI-AAI.2014.73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6

Abstract

Concept maps can help students learn more meaningfully. According to test scores only, students were divided into three groups of high-score, middle-score and low-score, in the previous works, researchers then applied data mining association rule technique to analysis different student groups' assessment data to construct corresponding concept maps. However, for considering more accurate to evaluate students' performance states and various possible distributions of students' assessment data, in this research, we apply student-problem chart to obtain students response patterns for grouping purpose. We generate six response pattern groups for 30131 students. Using association rule data mining technique also, we will construct more precise concept maps for students of different groups individually.
基于学生问题图的概念图构建
概念图可以帮助学生更有意义地学习。仅根据考试成绩将学生分为高、中、低三组,在之前的工作中,研究者利用数据挖掘关联规则技术对不同学生群体的评价数据进行分析,构建相应的概念图。然而,为了更准确地评估学生的表现状态和学生评估数据的各种可能分布,在本研究中,我们采用学生问题图来获得学生的反应模式进行分组。我们为30131名学生生成了6个响应模式组。利用关联规则数据挖掘技术,我们将为不同分组的学生构建更精确的概念图。
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 求助全文
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