Android练习与云原生技术的自动评估

Daniel Bruzual, Maria L. Montoya Freire, M. D. Francesco
{"title":"Android练习与云原生技术的自动评估","authors":"Daniel Bruzual, Maria L. Montoya Freire, M. D. Francesco","doi":"10.1145/3341525.3387430","DOIUrl":null,"url":null,"abstract":"Mobile applications are very challenging to test as they usually have a complex graphical user interface and advanced functionality that involves interacting with remote services. Due to these features, student assessment in courses about mobile application development usually relies on assignments or projects that are manually checked by teaching assistants for grading. This approach clearly does not scale to large classrooms, especially for online courses. This article presents a novel system for automated assessment of Android exercises with cloud-native technologies. Different from the state of the art, the proposed solution leverages a mobile app testing framework that is largely used in the industry instead of custom libraries. Furthermore, the devised system employs software containers and scales with the availability of resources in a data center, which is essential for massive open online courses. The system design and implementation is detailed, together with the results from a deployment within a master-level course with 120 students. The received feedback demonstrates that the proposed solution was effective, as it provided insightful feedback and supported independent learning of mobile application development.","PeriodicalId":422384,"journal":{"name":"Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education","volume":"120 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Automated Assessment of Android Exercises with Cloud-native Technologies\",\"authors\":\"Daniel Bruzual, Maria L. Montoya Freire, M. D. Francesco\",\"doi\":\"10.1145/3341525.3387430\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile applications are very challenging to test as they usually have a complex graphical user interface and advanced functionality that involves interacting with remote services. Due to these features, student assessment in courses about mobile application development usually relies on assignments or projects that are manually checked by teaching assistants for grading. This approach clearly does not scale to large classrooms, especially for online courses. This article presents a novel system for automated assessment of Android exercises with cloud-native technologies. Different from the state of the art, the proposed solution leverages a mobile app testing framework that is largely used in the industry instead of custom libraries. Furthermore, the devised system employs software containers and scales with the availability of resources in a data center, which is essential for massive open online courses. The system design and implementation is detailed, together with the results from a deployment within a master-level course with 120 students. The received feedback demonstrates that the proposed solution was effective, as it provided insightful feedback and supported independent learning of mobile application development.\",\"PeriodicalId\":422384,\"journal\":{\"name\":\"Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education\",\"volume\":\"120 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3341525.3387430\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3341525.3387430","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

移动应用程序的测试非常具有挑战性,因为它们通常具有复杂的图形用户界面和涉及与远程服务交互的高级功能。由于这些特点,学生对移动应用程序开发课程的评估通常依赖于助教手动检查的作业或项目来评分。这种方法显然不适用于大型教室,尤其是在线课程。本文介绍了一种利用云原生技术自动评估Android练习的新系统。与目前的现状不同,提议的解决方案利用了一个在行业中广泛使用的移动应用测试框架,而不是自定义库。此外,设计的系统采用软件容器,并根据数据中心资源的可用性进行扩展,这对于大规模开放在线课程是必不可少的。详细介绍了系统的设计和实现,以及在120名学生的硕士课程中部署的结果。收到的反馈表明,提出的解决方案是有效的,因为它提供了深刻的反馈,并支持独立学习的移动应用程序开发。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Assessment of Android Exercises with Cloud-native Technologies
Mobile applications are very challenging to test as they usually have a complex graphical user interface and advanced functionality that involves interacting with remote services. Due to these features, student assessment in courses about mobile application development usually relies on assignments or projects that are manually checked by teaching assistants for grading. This approach clearly does not scale to large classrooms, especially for online courses. This article presents a novel system for automated assessment of Android exercises with cloud-native technologies. Different from the state of the art, the proposed solution leverages a mobile app testing framework that is largely used in the industry instead of custom libraries. Furthermore, the devised system employs software containers and scales with the availability of resources in a data center, which is essential for massive open online courses. The system design and implementation is detailed, together with the results from a deployment within a master-level course with 120 students. The received feedback demonstrates that the proposed solution was effective, as it provided insightful feedback and supported independent learning of mobile application development.
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:604180095
Book学术官方微信