Data Driven Classroom Interviews (DDCIs) are short, qualitative interviews designed to help us contextualize student actions within an online learning system. DDCIs are conducted using an Android application called Quick Red Fox (QRF), which pings a researcher in the classroom when an automated model detects a construct, behavior, or event of interest within the learning system you are studying.  The researcher can then conduct an immediate interview, while the student is experiencing that event, leveraging the benefits of a think-aloud protocol while scaffolding the student's metacognition about the learning event, so that we minimize the cognitive load of trying to report on the learning event while continuing with the learning activity. This also allows us to direct our research questions to that we get beyond the observations, ideas, or feelings that are immediately salient to the student. 

There are several advantages to this method:

• DDCIs can be conducted in authentic classroom environments

• QRF can pinpoint subtle and rare interactions that even a teacher in a classroom might not notice

• If students are struggling, we can talk to them before they have resolved that struggle (which may influence their memory of the interaction)

• DDCIs allows the researcher to carry the burden of steer the students' talk toward important topics related to the research questions (vs. other methods, where the burden is on the student)

This tutorial is targeted towards participants who are working with digital learning environments that are capable of processing students’ data in real time.  We are very receptive to inviting participants who are still in the very early planning stages of doing so. 

As this research is truly multi-disciplinary, organizers are dedicated to making this an inclusive opportunity. Established research teams are very welcome, and those looking to form new research partnerships are also highly encouraged.