Shifting Dynamics Between Students' Epistemological Framing and Encounters With Uncertainty

• In Event: 69.019 - Examining Uncertainty as a Construct for Promoting Meaningful Scientific Engagement

Abstract

We explore the shifting dynamics of students’ encounters with uncertainty (or lack of it) as they explore a computational model and the epistemological framings that emerge during this activity. Epistemological framing (Bing & Redish, 2009; Colleague & Author, 2010) provides a lens to examine how students interpreted and negotiated their roles as learners. We argue that experiences of uncertainty can result in a productive framing, and that shifts in framing can influence students’ degree of engagement with discrepancies and anomalies in the computer model.

The data come from a design-based research study for hybrid labs that integrates physical experiments with computational models in introductory undergraduate biology labs. We draw on data from Camtasia videos of a group of students exploring a computational model by manipulating parameters to investigate long-term fitness of two bacterial strains.

In the first phase of analysis, we identified moments that marked a salient shift in students’ epistemological framing of their work. We identified these moments by attending to students’ behaviors including utterances and tone of voice (Colleague & Author, 2009). In a second pass, we identified moments of uncertainty (marked by expressions of confusion or surprise) as well as moments where uncertainty was resolved (either through group negotiation or instructor intervention).

We present an analysis of two contrasting moments. In the first, students encountered uncertainty in the form of an unexpected trend in simulation output. In the second, uncertainty was unexpectedly resolved by the teaching assistant. We analyzed these moments to examine the interplay between students’ experience of uncertainty (or lack of it), epistemological framing, and the consequences for subsequent activity in the computational modeling environment.

We found that encountering uncertainty while exploring the model cued an epistemological framing of model exploring. These moments were marked by a sense of surprise (“Oh, that’s weird”) at noticing an unexpected trend in the model or joy in learning that their exploration could be self-guided (“Oh cool!”). Following these moments, students brainstormed multiple ways to create specific outcomes in the model, they generated explanations for observations, and they challenged each other’s ideas. On the other hand, when uncertainty was unexpectedly resolved by a TA who, provided an explanation for a puzzling pattern and then proposed a specific approach to model exploration, students shifted into an epistemological framing of getting the worksheet done. Indicators of this framing were their affect becoming flat and disinterested, turning to their worksheet, seeking only one way to create specific outcomes in the model, and quickly moving on the next question once a solution was found.

Based on these findings, we claim that students’ experiences of uncertainty while exploring a computational model can result in productive epistemological framings, but that those framings can be unstable and sensitive to external cues such as interactions with instructors. Our work highlights the potential generativity of rich computational contexts where students can freely manipulate parameters but also reflects the tensions that arise when instructors try to reduce the confusion and uncertainty that emerges during students’ self-guided exploration.

Authors

• Aditi Wagh, Tufts University

• Julia Svoboda Gouvea, Tufts University