Collaborative Research: Learning Software Engineering by Contributing to Real Projects With Chatbot Assistance

协作研究：通过聊天机器人协助为实际项目做出贡献来学习软件工程

• 批准号: 2303043
• 负责人: Anita Sarma
• 金额: $ 28.8万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2303043&HistoricalAwards=false
• 关键词: Collaborative; Research; Learning; Software; Engineering

Open Source Software (OSS) is an economic driving force providing software systems used through the entire development stack, from operating system kernels to sophisticated end-user applications. It is also an important platform for education. A large number of young developers join open source projects to improve their programming and other software engineering skills. It is not surprising, therefore, that many software engineering educators want to use OSS projects as a training ground for students to gain experience with real world software development problems. These experiences carry the added benefit that students contribute to the evolution of projects relevant to society and their own interests. Successful participation in open source projects also increases students' chances for professional success. However, students onboarding to OSS face many difficulties. Project documentation is often lacking, and core developers have little time to effectively mentor students, since they often are volunteers contributing during their spare time. To better support students in their journey toward contributing to open source software, this project proposes to design, develop, and evaluate a conversational agent (chatbot).This project investigates how a conversational agent can be designed as an effective teaching aid for OSS contribution by understanding the needs and expectations of students and instructors, investigating how students verbalize their expectations and dialog with the agent, and how to design such an agent. To achieve these goals, the project employs a multi-method approach, including participatory design, prototyping, and technological evaluation. The project also investigates how effective a chatbot is in helping students learn how to contribute to an open source project in lab and classroom settings.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

开源软件（OSS）是一种经济驱动力，可提供整个开发堆栈中使用的软件系统，从操作系统内核到复杂的最终用户应用程序。它也是教育的重要平台。许多年轻开发人员加入开源项目，以提高其编程和其他软件工程技能。因此，毫不奇怪，许多软件工程教育者都希望将OSS项目用作学生获得现实世界软件开发问题的经验的培训。 这些经验带来了学生为与社会及其利益相关的项目发展做出贡献的额外好处。成功参与开源项目还增加了学生获得职业成功的机会。但是，学生登上OSS面临许多困难。项目文档通常缺乏，核心开发人员几乎没有时间有效地指导学生，因为他们通常是志愿者在业余时间做出的贡献。为了更好地支持学生在为开源软件做出贡献的过程中，该项目建议设计，开发和评估对话代理（聊天机器人）。该项目如何通过理解学生和讲师的需求和期望来设计对话代理，以对OSS的有效辅助辅助设计，并研究学生与学生的期望和对话方式，并如何与该代理商进行对话，并如何设计这些代理商，并如何设计代理人。为了实现这些目标，该项目采用了多方法方法，包括参与性设计，原型和技术评估。该项目还调查了聊天机器人在帮助学生学习如何为实验室和课堂环境中的开源项目做出贡献的有效性。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子和更广泛影响的评估评估标准来通过评估来支持的。