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In this paper we investigate the influence interfaces and feedback have on human-robot trust levels when operating in a shared physical space. The task we use is specifying a “no-go” region for a robot in an indoor environment. We evaluate three styles of interface (physical, AR, and map-based) and four feedback mechanisms (no feedback, robot drives around the space, an AR “fence”, and the region marked on the map). Our evaluation looks at both usability and trust. Specifically, if the participant trusts that the robot “knows” where the no-go region is and their confidence in the robot's ability to avoid that region. We use both self-reported and indirect measures of trust and usability. Our key findings are: 1) interfaces and feedback do influence levels of trust; 2) the participants largely preferred a mixed interface-feedback pair, where the modality for the interface differed from the feedback. 

Abstract Mentoring is a well-known way to help newcomers to Open Source Software (OSS) projects overcome initial contribution barriers. Through mentoring, newcomers learn to acquire essential technical, social, and organizational skills. Despite the importance of OSS mentors, they are understudied in the literature. Understanding who OSS project mentors are, the challenges they face, and the strategies they use can help OSS projects better support mentors’ work. In this paper, we employ a two-stage study to comprehensively investigate mentors in OSS. First, we identify the characteristics of mentors in the Apache Software Foundation, a large OSS community, using an online survey. We found that less experienced volunteer contributors are less likely to take on the mentorship role. Second, through interviews with OSS mentors (n=18), we identify the challenges that mentors face and how they mitigate them. In total, we identified 25 general mentorship challenges and 7 sub-categories of challenges regarding task recommendation. We also identified 13 strategies to overcome the challenges related to task recommendation. Our results provide insights for OSS communities, formal mentorship programs, and tool builders who design automated support for task assignment and internship. 

Software developers who want to start contributing to an Open Source Software (OSS) project often struggle to find appropriate first tasks. The voluntary, self-organizing distribution of decentralized labor and the distinct nature of some OSS projects intensifies this challenge. Mentors, who work closely with newcomers, develop strategies to recommend tasks. However, to date neither the challenges mentors face in recommending tasks nor their strategies have been formally documented or studied. In this paper, we interviewed mentors of well-established OSS projects (n=10) and qualitatively analyzed their answers to identify both challenges and strategies related to recommending tasks for newcomers. Then, we employed a survey (n=30) to map the strategies to challenges and collect additional strategies. Our study identified 7 challenges and 13 strategies related to task recommendation. Strategies such as “tagging the issues based on difficulty,” “adding documentation,” “assigning a small task first and then challenge the newcomers with bigger tasks,” and “dividing tasks into smaller pieces” were frequently mentioned as ways to overcome multiple challenges. Our results provide insights for mentors about the strategies OSS communities can use to guide their mentors and for tool builders who design automated support for task assignment.