Customized course advising: investigating engineering student success with incoming profiles and patterns of concurrent course enrollment

Proceedings of the Fourth International Conference on Learning Analytics And Knowledge Pub Date : 2014-03-24 DOI:10.1145/2567574.2567589

Sungjin Nam, Steven Lonn, Thomas Brown, Cinda-Sue Davis, Darryl Koch

{"title":"Customized course advising: investigating engineering student success with incoming profiles and patterns of concurrent course enrollment","authors":"Sungjin Nam, Steven Lonn, Thomas Brown, Cinda-Sue Davis, Darryl Koch","doi":"10.1145/2567574.2567589","DOIUrl":null,"url":null,"abstract":"Every college student registers for courses from a catalog of numerous offerings each term. Selecting the courses in which to enroll, and in what combinations, can dramatically impact each student's chances for academic success. Taking inspiration from the STEM Academy, we wanted to identify the characteristics of engineering students who graduate with 3.0 or above grade point average. The overall goal of the Customized Course Advising project is to determine the optimal term-by-term course selections for all engineering students based on their incoming characteristics and previous course history and performance, paying particular attention to concurrent enrollment. We found that ACT Math, SAT Math, and Advanced Placement exam can be effective measures to measure the students' academic preparation level. Also, we found that some concurrent course-enrollment patterns are highly predictive of first-term and overall academic success.","PeriodicalId":178564,"journal":{"name":"Proceedings of the Fourth International Conference on Learning Analytics And Knowledge","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fourth International Conference on Learning Analytics And Knowledge","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2567574.2567589","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 22

Abstract

Every college student registers for courses from a catalog of numerous offerings each term. Selecting the courses in which to enroll, and in what combinations, can dramatically impact each student's chances for academic success. Taking inspiration from the STEM Academy, we wanted to identify the characteristics of engineering students who graduate with 3.0 or above grade point average. The overall goal of the Customized Course Advising project is to determine the optimal term-by-term course selections for all engineering students based on their incoming characteristics and previous course history and performance, paying particular attention to concurrent enrollment. We found that ACT Math, SAT Math, and Advanced Placement exam can be effective measures to measure the students' academic preparation level. Also, we found that some concurrent course-enrollment patterns are highly predictive of first-term and overall academic success.

查看原文本刊更多论文

定制课程建议:调查工程专业学生的成功概况和同步课程注册模式

每个大学生每学期都会从众多课程目录中注册课程。选择参加的课程，以及以何种组合，可以极大地影响每个学生学业成功的机会。从STEM学院获得灵感，我们想要确定平均绩点在3.0或以上的工程专业学生的特征。定制课程建议项目的总体目标是根据所有工程专业学生的入学特点和以前的课程历史和表现，确定最佳的学期课程选择，特别注意同时入学。我们发现ACT数学、SAT数学和大学先修课程考试是衡量学生学业准备水平的有效措施。此外，我们还发现，一些同步课程的入学模式对第一学期和整体学业成功具有很高的预测性。

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

Proceedings of the Fourth International Conference on Learning Analytics And Knowledge

自引率

0.00%

发文量