Feature-Aware Knowledge Tracing for Generation of Concept-Knowledge Reports in an Intelligent Tutoring System

Mithun Haridas, Nirmala Vasudevan, S. Gayathry, G. Gutjahr, R. Raman, Prema Nedungadi
{"title":"Feature-Aware Knowledge Tracing for Generation of Concept-Knowledge Reports in an Intelligent Tutoring System","authors":"Mithun Haridas, Nirmala Vasudevan, S. Gayathry, G. Gutjahr, R. Raman, Prema Nedungadi","doi":"10.1109/T4E.2019.00-34","DOIUrl":null,"url":null,"abstract":"In many Indian schools, a high student-teacher ratio makes it an uphill struggle for teachers to assess the knowledge of individual students and deficiencies in the students' understanding. Teachers should have a clear picture on what concepts each student has mastered, and which concepts the teacher needs to review in greater detail. This paper investigates the students' concept knowledge, based on the interaction of the students with an intelligent tutoring system. The Feature-Aware Student knowledge Tracing (FAST) algorithm was used, since the algorithm facilitates the separation of lesson-specific skills from concept knowledge. Data from 2400 first-grade students from 28 schools were used for the analysis. Findings include a moderate fit model and an easy interpretation of the model parameters.","PeriodicalId":347086,"journal":{"name":"2019 IEEE Tenth International Conference on Technology for Education (T4E)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Tenth International Conference on Technology for Education (T4E)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/T4E.2019.00-34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

Abstract

In many Indian schools, a high student-teacher ratio makes it an uphill struggle for teachers to assess the knowledge of individual students and deficiencies in the students' understanding. Teachers should have a clear picture on what concepts each student has mastered, and which concepts the teacher needs to review in greater detail. This paper investigates the students' concept knowledge, based on the interaction of the students with an intelligent tutoring system. The Feature-Aware Student knowledge Tracing (FAST) algorithm was used, since the algorithm facilitates the separation of lesson-specific skills from concept knowledge. Data from 2400 first-grade students from 28 schools were used for the analysis. Findings include a moderate fit model and an easy interpretation of the model parameters.
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
智能辅导系统中基于特征感知的知识跟踪生成概念知识报表
在许多印度学校,学生与教师的比例很高,这使得教师很难评估个别学生的知识水平和学生理解能力的不足。教师应该清楚地了解每个学生掌握了哪些概念,以及教师需要更详细地复习哪些概念。本文基于学生与智能辅导系统的互动,对学生的概念知识进行了调查。使用了特征感知学生知识跟踪(FAST)算法,因为该算法有助于将特定课程技能与概念知识分离开来。来自28所学校的2400名一年级学生的数据被用于分析。结果包括适度拟合模型和模型参数的简单解释。
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
Insights into Factors Affecting Success in Graduate Aptitude Test in Engineering for Indian Engineering Students using Learning Analytics Rural Health in Digital India: Interactive Simulations for Community Health Workers Heuristic Evaluation and User Experience Redesign of 'Think & Link' Learning Environment – A Case Study Musical Mimicry to Learn Audio Processing OMEGA: A Multiplayer Online Game for Improving User's Meta-Cognitive Skills
×
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