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Newcomers onboarding to Open Source Software (OSS) projects face many challenges. Large Language Models (LLMs), like ChatGPT, have emerged as potential resources for answering questions and providing guidance, with many developers now turning to ChatGPT over traditional Q&A sites like Stack Overflow. Nonetheless, LLMs may carry biases in presenting information, which can be especially impactful for newcomers whose problem-solving styles may not be broadly represented. This raises important questions about the accessibility of AI-driven support for newcomers to OSS projects. This vision paper outlines the potential of adapting AI responses to various problem-solving styles to avoid privileging a particular subgroup. We discuss the potential of AI persona-based prompt engineering as a strategy for interacting with AI. This study invites further research to refine AI-based tools to better support contributions to OSS projects. 

Context: Newcomers joining an unfamiliar software project face numerous barriers; therefore, effective onboarding is essential to help them engage with the team and develop the behaviors, attitudes, and skills needed to excel in their roles. However, onboarding can be a lengthy, costly, and error-prone process. Software solutions can help mitigate these barriers and streamline the process without overloading senior members. Objective: This study aims to identify the state-of-the-art software solutions for onboarding newcomers. Methods: We conducted a systematic literature review (SLR) to answer six research questions. Results: We analyzed 32 studies about software solutions for onboarding newcomers and yielded several key findings: (1) a range of strategies exists, with recommendation systems being the most prevalent; (2) most solutions are web-based; (3) solutions target a variety of onboarding aspects, with a focus on process; (4) many onboarding barriers remain unaddressed by existing solutions; (5) laboratory experiments are the most commonly used method for evaluating these solutions; and (6) diversity and inclusion aspects primarily address experience level. Conclusion: We shed light on current technological support and identify research opportunities to develop more inclusive software solutions for onboarding. These insights may also guide practitioners in refining existing platforms and onboarding programs to promote smoother integration of newcomers into software projects. 

Participation in Open Source Software (OSS) projects offers real software development experience for students and other newcomers seeking to develop their skills. However, onboarding to an OSS project brings various challenges, including finding a suitable task among various open issues. Selecting an appropriate starter task requires newcomers to identify the skills needed to solve a project issue and avoiding tasks too far from their skill set. However, little is known about how effective newcomers are in identifying the skills needed to resolve an issue. We asked 154 undergrad students to evaluate issues from OSS projects and infer the skills needed to contribute. Students reported a total of 94 skills, which we classified into 10 categories. We compared the students' answers to those collected from 6 professional developers. In general, students misidentified and missed several skills (f-measure=0.37). Students had results closer to professional developers for skills related to database, operating infrastructure, programming concepts, and programming language, and they had worse results in identifying skills related to debugging and program comprehension. Our results can help educators who seek to use OSS as part of their courses and OSS communities that want to label newcomer-friendly issues to facilitate onboarding of new contributors.