Date
Publisher
arXiv
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.
Study at a glance
- Question: How can an app help researchers conduct brief, targeted interviews with students during digital learning?
- Setting and data: Not stated in the abstract
- Method: Technical manual and methodology guide
Why it matters
Researchers need to contextualize students' interactions with digital learning environments without interrupting their learning. This requires targeted interviewing methods that focus directly on key moments and behaviors during learning experiences.
Key findings
- In digital learning environments like educational games, the Quick Red Fox app directs interviewers to students displaying specific behaviors, minimizing learning interruptions.
- The app integrates with tools that detect student behaviors, emotions, and self-regulated learning to alert interviewers to key learning moments.
- Targeted, data-driven classroom interviews help observers contextualize student experiences with learning software while focusing on designated events.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Why use AI?
Study design
