[Context] Interviewing stakeholders is the most popular requirements elicitation technique among multiple methods. The success of an interview depends on the collaboration of the interviewee which can be fostered through the interviewer's preparedness and communication skills. Mastering these skills requires experience and practicing interviews. [Problem] Practical training is resource-heavy as it calls for the time and effort of a stakeholder for each student which may not be feasible for a large number of students. [Method] To address this scalability problem, this paper proposes RoboREIT, an interactive Robotic tutor for Requirements Elicitation Interview Training. The humanoid robotic component of RoboREIT responds to the questions of the interviewer, which the interviewer chooses from a set of predefined alternatives for a particular scenario. After the interview session, RoboREIT provides contextual feedback to the interviewer on their performance and allows the student to inspect their mistakes. RoboREIT is extensible with various scenarios. [Results] We performed an exploratory user study to evaluate RoboREIT and demonstrate its applicability in requirements elicitation interview training. The quantitative and qualitative analyses of the users' responses reveal the appreciation of RoboREIT and provide further suggestions about how to improve it. [Contribution] Our study is the first in the literature that utilizes a social robot in requirements elicitation interview education. RoboREIT's innovative design incorporates replaying faulty interview stages and allows the student to learn from mistakes by a second time practicing. All participants praised the feedback component, which is not present in the state-of-the-art, for being helpful in identifying the mistakes. A favorable response rate of 81% for the system's usefulness indicates the positive perception of the participants.
翻译:【背景:】在多种方法中,面试利益相关者是最受欢迎的需求获取技术。面试的成功取决于被面试者的合作精神,这可以通过面试官的准备和沟通技巧来促进。掌握这些技能需要经验和面试实践。【问题:】实际培训需要利益相关者和每个学生的时间和精力,这可能对大量学生不可行。【方法:】为了解决这个可扩展性问题,本文提出 RoboREIT,一种用于需求获取面试培训的交互式机器人教师。RoboREIT 的人形机器人组件回答面试官的问题,面试官可以从特定场景的一组预定义的替代方案中选择。在面试结束后,RoboREIT 会提供有关面试官表现的上下文反馈,并允许学生检查自己的错误。RoboREIT 可与不同的方案扩展。【结果:】我们进行了一项探索性用户研究,对 RoboREIT 进行了评估,并展示了它在需求获取面试培训中的适用性。对用户反应的定量和定性分析表明,用户对 RoboREIT 的赞赏,并提供了进一步的建议以改进它。【贡献:】我们的研究是文献中首次使用社交机器人进行需求获取面试教育。RoboREIT 的创新设计包括重放有误的面试阶段,并允许学生通过第二次实践从错误中学习。所有参与者都赞扬了反馈组件的帮助性,而这种组件在现有技术中不存在。81% 的系统有用性的良好反应率表明参与者持有积极态度。