In-the-moment Learning of Organic Chemistry During Interactive Lectures Through the Lens of Practical Epistemology Analysis

Abstract

Although many studies have used interviews to explore how students' reason about organic chemistry problems, less is known about how students learn in-the-moment in natural settings, such as during discussions in active learning settings. In this chapter, we draw on practical epistemology analysis (PEA) to define in-the-moment learning as the noticing of gaps, i.e., students' needs to make something intelligible to be able to progress in an activity, and the filling of these gaps with relations, i.e., connections between what is in question and prior conceptual knowledge or familiar skills. Through analyzing video recordings of students in an interactive general chemistry lecture working on organic chemistry content in groups facilitated by learning assistants, we demonstrate the power of PEA as a tool to make student learning during collaborative group discussion visible. By doing so we aim to provide a lens for practitioners who teach organic chemistry to notice how students' in-the-moment learning progresses and how their facilitation relates to that progression and for researchers to make this progression as it occurs in the moment accessible for their own investigation.

Making in‐the‐moment learning visible: A framework to identify and compare various ways of learning through continuity and discourse change

“…To analyze the data, we used PEA to capture how the conversation progressed by reducing the encounter to what gaps were opened, what relations were established to fill these gaps, and who contributed to the conversation through noticing or filling gaps (Walsh et al, 2022; Wickman & Östman, 2002). We started this process by reading each transcript alongside the video.…”

“…These analyses show that we can distinguish different ways in-the-moment learning progresses, as well as different objects of in-the-moment learning. In addition to the three mechanisms we presented here (revisiting, exploring, and learning of norms), we also found two other common mechanisms for learning in our data set that were conceptual in nature: elaborating, in which learning was driven by the need to make sense of each other's ideas (characterized by high continuity-within and -across, and high DC-within); and stepwise, in which learning was driven by identifying and filling needs before moving onto the next gap (characterized by low continuity-across and DC-across, and high DC-within), similar to the subsequent gap pattern presented in Walsh et al, 2022. Additionally, these mechanisms commonly coexisted within a single encounter.…”

“…This study is part of a larger one that seeks to understand the facilitation practices of learning assistants (e.g., Carlos et al, 2023;Walsh et al, 2022). The learning assistant (LA) model is a near-peer active learning model where more advanced undergraduate students, or LAs, assist in courses to support student engagement and increase the number of facilitators with whom students have contact (Barrasso & Spilios, 2021;Otero et al, 2006Otero et al, , 2010.…”