Using software metrics to predict the difficulty of code writing questions

S. Elnaffar
{"title":"Using software metrics to predict the difficulty of code writing questions","authors":"S. Elnaffar","doi":"10.1109/EDUCON.2016.7474601","DOIUrl":null,"url":null,"abstract":"Asking IT students, job interviewees, and competition contestants to write code is very common. Nevertheless, to properly assess the programming skills of such people, the anticipated difficulty level of these coding questions should be estimated and kept in mind throughout the preparation of such exams. Poor results coming out of these assessment tools may not be entirely attributed to exam takers, but rather to the poor design of the exams that fail to gauge the competency levels of each student via the ranked levels of difficulty of questions on the exam. In this research, we argue that we can develop a predictive tool, named the Predicted Difficulty Index (PDI), that is derived from the structure of the sample solutions to rank the questions based on the difficulty that students may encounter while solving them. Such prior knowledge about questions' complexity should help instructors assign questions the proper points and place them in a progressive order throughout the exam leading to a more reliable evaluation tool.","PeriodicalId":360311,"journal":{"name":"2016 IEEE Global Engineering Education Conference (EDUCON)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE Global Engineering Education Conference (EDUCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDUCON.2016.7474601","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Asking IT students, job interviewees, and competition contestants to write code is very common. Nevertheless, to properly assess the programming skills of such people, the anticipated difficulty level of these coding questions should be estimated and kept in mind throughout the preparation of such exams. Poor results coming out of these assessment tools may not be entirely attributed to exam takers, but rather to the poor design of the exams that fail to gauge the competency levels of each student via the ranked levels of difficulty of questions on the exam. In this research, we argue that we can develop a predictive tool, named the Predicted Difficulty Index (PDI), that is derived from the structure of the sample solutions to rank the questions based on the difficulty that students may encounter while solving them. Such prior knowledge about questions' complexity should help instructors assign questions the proper points and place them in a progressive order throughout the exam leading to a more reliable evaluation tool.
使用软件度量来预测代码编写问题的难度
让IT学生、面试者和竞赛选手写代码是很常见的。然而,为了正确地评估这些人的编程技能,在准备这些考试的过程中,应该估计和记住这些编码问题的预期难度水平。这些评估工具的糟糕结果可能并不完全归咎于考生,而是由于考试设计糟糕,未能通过考试中问题的难度等级来衡量每个学生的能力水平。在这项研究中,我们认为我们可以开发一种预测工具,称为预测难度指数(PDI),它来源于样本解决方案的结构,根据学生在解决问题时可能遇到的难度对问题进行排名。这种对问题复杂性的先验知识可以帮助教师为问题分配适当的分数,并在整个考试中按顺序排列,从而形成更可靠的评估工具。
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:604180095
Book学术官方微信