Building Equitable Classrooms Using EQUIP to Track Student Participation Patterns

Streaming Media

Location

Logan, UT

Start Date

9-14-2024 12:00 AM

Description

The more students participate in class, the more they learn, and student participation is key to students' identity development (Nasir & de Royston, 2013; Webb et al., 2019). Yet, students' opportunities to participate in classroom varies and inequities in classroom participation is well documented, especially along racial lines (McAfee, 2014; Reinholz et al., 2020; Shah et al., 2020). New AI- and technology-based tools, like EQUIP (Equity QUantified In Participation), can be used to track student participation patterns (Reinholz et al., 2022). EQUIP is a free, open source, and customizable web app that can be used by instructors to code face-to-face and virtual lessons in ways that automatically generate data so that instructors can see who is participating in class and how. In this first part of this session, we will examine extant research on in(equitable) student participation opportunities in higher education classrooms. In the second part, we will explore, step-by-step, how to use EQUIP to measure and track student participation patterns in classrooms. Finally, we will co-discuss and co-analyze examples of EQUIP data analytics output and how that information can be used to create more equitable (and inclusive) classroom practices and spaces.

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Sep 14th, 12:00 AM

Building Equitable Classrooms Using EQUIP to Track Student Participation Patterns

Logan, UT

The more students participate in class, the more they learn, and student participation is key to students' identity development (Nasir & de Royston, 2013; Webb et al., 2019). Yet, students' opportunities to participate in classroom varies and inequities in classroom participation is well documented, especially along racial lines (McAfee, 2014; Reinholz et al., 2020; Shah et al., 2020). New AI- and technology-based tools, like EQUIP (Equity QUantified In Participation), can be used to track student participation patterns (Reinholz et al., 2022). EQUIP is a free, open source, and customizable web app that can be used by instructors to code face-to-face and virtual lessons in ways that automatically generate data so that instructors can see who is participating in class and how. In this first part of this session, we will examine extant research on in(equitable) student participation opportunities in higher education classrooms. In the second part, we will explore, step-by-step, how to use EQUIP to measure and track student participation patterns in classrooms. Finally, we will co-discuss and co-analyze examples of EQUIP data analytics output and how that information can be used to create more equitable (and inclusive) classroom practices and spaces.