Data Driven Classroom Interviews (DDCIs) are an interviewing technique that is facilitated by recent technological developments in the learning analytics community. DDCIs are short, targeted interviews that allow researchers to contextualize students' interactions with a digital learning environment (e.g., intelligent tutoring systems or educational games) while minimizing the amount of time that the researcher interrupts that learning experience, and focusing researcher time on the events they most want to focus on DDCIs are facilitated by a research tool called the Quick Red Fox (QRF)--an open-source server-client Android app that optimizes researcher time by directing interviewers to users that have just displayed an interesting behavior (previously defined by the research team). QRF integrates with existing student modeling technologies (e.g., behavior-sensing, affect-sensing, detection of self-regulated learning) to alert researchers to key moments in a learner's experience. This manual documents the tech while providing training on the processes involved in developing triggers and interview techniques; it also suggests methods of analyses.

翻译：数据驱动课堂访谈是一种由学习分析领域近期技术发展所促成的访谈技术。DDCI是简短、有针对性的访谈，使研究者能够在学生与数字学习环境（如智能辅导系统或教育游戏）互动时进行情境化分析，同时最小化研究者中断学习体验的时间，并将研究精力集中于最关注的事件上。DDCI由名为“快速红狐”的研究工具支持——这是一款开源服务器-客户端Android应用程序，通过引导访谈者接触刚表现出有趣行为（由研究团队预先定义）的用户来优化研究者时间。QRF与现有学生建模技术（如行为感知、情感感知、自主学习检测）集成，以提醒研究者关注学习者体验中的关键时刻。本手册在记录该技术的同时，提供了关于开发触发机制和访谈技巧的流程培训，并提出了分析方法建议。