测试时间限制在筛选问题与程序员在线调查

A. Danilova, S. Horstmann, Matthew Smith, Alena Naiakshina
{"title":"测试时间限制在筛选问题与程序员在线调查","authors":"A. Danilova, S. Horstmann, Matthew Smith, Alena Naiakshina","doi":"10.1145/3510003.3510223","DOIUrl":null,"url":null,"abstract":"Recruiting study participants with programming skill is essential for researchers. As programming is not a common skill, recruiting programmers as participants in large numbers is challenging. Plat-forms like Amazon MTurk or Qualtrics offer to recruit participants with programming knowledge. As this is self-reported, participants without programming experience could still take part, either due to a misunderstanding or to obtain the study compensation. If these participants are not detected, the data quality will suffer. To tackle this, Danilova et al. [11] developed and tested screening tasks to detect non-programmers. Unfortunately, the most reliable screen-ers were also those that took the most time. Since screeners should take as little time as possible, we examine whether the introduction of time limits allows us to create more efficient (i.e., quicker but still reliable) screeners. Our results show that this is possible and we extend the pool of screeners and make recommendations on how to improve the process.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Testing Time Limits in Screener Questions for Online Surveys with Programmers\",\"authors\":\"A. Danilova, S. Horstmann, Matthew Smith, Alena Naiakshina\",\"doi\":\"10.1145/3510003.3510223\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recruiting study participants with programming skill is essential for researchers. As programming is not a common skill, recruiting programmers as participants in large numbers is challenging. Plat-forms like Amazon MTurk or Qualtrics offer to recruit participants with programming knowledge. As this is self-reported, participants without programming experience could still take part, either due to a misunderstanding or to obtain the study compensation. If these participants are not detected, the data quality will suffer. To tackle this, Danilova et al. [11] developed and tested screening tasks to detect non-programmers. Unfortunately, the most reliable screen-ers were also those that took the most time. Since screeners should take as little time as possible, we examine whether the introduction of time limits allows us to create more efficient (i.e., quicker but still reliable) screeners. Our results show that this is possible and we extend the pool of screeners and make recommendations on how to improve the process.\",\"PeriodicalId\":202896,\"journal\":{\"name\":\"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3510003.3510223\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3510003.3510223","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

摘要

招募具有编程技能的研究参与者对研究人员来说至关重要。由于编程不是一种常见的技能,因此大量招募程序员作为参与者是具有挑战性的。像Amazon MTurk或qualics这样的平台提供招聘具有编程知识的参与者。由于这是自我报告,没有编程经验的参与者仍然可以参加,可能是由于误解,也可能是为了获得研究补偿。如果没有检测到这些参与者,则数据质量将受到影响。为了解决这个问题,Danilova等人开发并测试了筛选任务来检测非程序员。不幸的是,最可靠的筛选者也是那些花费时间最多的人。由于筛选程序应该尽可能少花时间,我们研究了引入时间限制是否能让我们创建更有效(即更快但仍然可靠)的筛选程序。我们的结果表明,这是可能的,我们扩大了筛选池,并就如何改进这一过程提出了建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Testing Time Limits in Screener Questions for Online Surveys with Programmers
Recruiting study participants with programming skill is essential for researchers. As programming is not a common skill, recruiting programmers as participants in large numbers is challenging. Plat-forms like Amazon MTurk or Qualtrics offer to recruit participants with programming knowledge. As this is self-reported, participants without programming experience could still take part, either due to a misunderstanding or to obtain the study compensation. If these participants are not detected, the data quality will suffer. To tackle this, Danilova et al. [11] developed and tested screening tasks to detect non-programmers. Unfortunately, the most reliable screen-ers were also those that took the most time. Since screeners should take as little time as possible, we examine whether the introduction of time limits allows us to create more efficient (i.e., quicker but still reliable) screeners. Our results show that this is possible and we extend the pool of screeners and make recommendations on how to improve the process.
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