Quick Red Fox: Optimizing Classroom Interviews with SRL & Affect Detection

Learning Analytics Learning Network

LALN - Quick Red Fox: Optimizing Classroom Interviews with SRL and Affect Detection

Qualitative classroom interviewing and observation is typically highly time-consuming, and these methods can be difficult to use to study phenomena that only occur intermittently, such as key self-regulated learning behaviors or shifts in affect. In this presentation, we discuss our approach for optimizing classroom interviews and observations, to focus researcher time on critical events.Specifically, we introduce the free, open-source Quick Red Fox app. Quick Red Fox receives alerts from a learning system when an event of interest occurs, driven by automated detectors that recognize key self-regulated learning behaviors or shifts in affect, from student interaction behavior. The app prioritizes the events currently occurring in the classroom, and notifies a researcher as to where their time is best spent. Quick Red Fox then scaffolds the researcher in collecting interview data and later in synchronizing it back to student interaction data.In this session, we will provide a tutorial on how we used Quick Red Fox for research within the Betty’s Brain learning platform, discussing how we linked the app to the platform, selected and prioritized detectors and sequences of behavior identified by detectors, the interview protocol we developed around the app, and how we synchronized and analyzed the data to conduct basic research on self-regulated learning, affect, and student attitudes. We conclude with a discussion of research findings obtained with the app thus far.Attendees of this session will learn about this new type of mixed-methods research — using learning analytics to optimize qualitative research — and how they may be able to use Quick Red Fox or similar methods in their own research.Organizers: Jaclyn Ocumpaugh, Stephen Hutt, Ryan S. Baker – University of Pennsylvania; Anabil Munshi, Gautam Biswas – Vanderbilt University, Luc Paquette – University of Illinois at Urbana-ChampaignTarget audience: AnyoneTarget level: IntroductoryDelivery date and time: August 16 2021, 4:00pm US ET/3:00pm US CT

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Quick Red Fox: Optimizing Classroom Interviews with SRL & Affect Detection

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Quick Red Fox: Optimizing Classroom Interviews with SRL & Affect Detection

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