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

开放源码软件（OSS）是一种经济驱动力，提供了从操作系统内核到复杂的最终用户应用程序的整个开发堆栈中使用的软件系统。它也是一个重要的教育平台。大量年轻开发人员加入开源项目，以提高他们的编程和其他软件工程技能。因此，许多软件工程教育工作者希望将OSS项目作为学生获得真实的世界软件开发问题经验的训练场，这并不奇怪。 这些经验带来了额外的好处，学生有助于与社会和自己的利益相关的项目的发展。成功参与开源项目也增加了学生在职业上取得成功的机会。然而，学生进入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，因为他们通常是在业余时间贡献的志愿者。为了更好地支持学生为开源软件做出贡献，本项目提出设计、开发和评估一个对话代理（聊天机器人）。本项目通过了解学生和教师的需求和期望，调查学生如何用语言表达他们的期望并与代理对话，以及如何设计这样的代理。为了实现这些目标，该项目采用了多种方法，包括参与式设计，原型设计和技术评估。该项目还调查了聊天机器人在帮助学生学习如何在实验室和课堂环境中为开源项目做出贡献方面的有效性。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.