Taxonomy of Student Uncertainty in Scientific Argumentation

• In Event: 63.064 - Measuring the Impact of Emotions in Informal Learning Environments

Abstract

Objectives. Incorporating uncertainty as part of scientific argumentation means acknowledging that there may be incomplete or potentially limited information from which scientists draw conclusions. In the geosciences, scientists routinely must make inferences about the Earth based on observations of the present and testing those observations against hypotheses about Earth history and processes that are not observable. This paper describes how secondary school students incorporate uncertainty while formulating evidence-based scientific arguments.

Research context. Students’ written scientific argumentation occurred during a curriculum module addressing freshwater availability and sustainability topics. The water module included eight scientific argumentation tasks following the uncertainty-infused scientific argumentation framework (Lee et al., 2014). In these tasks, students made claims about groundwater systems, explain claims based on simulation model results or scientists’ data, rate uncertainty, and elaborate sources of uncertainty.

Theoretical framework. Uncertainty is part of everyday life because we humans act without full knowledge, information, or understanding of any encountered stimulus (Kahneman & Tversky, 1982). People often attribute uncertainty to internal or external sources. Internal attribution uses personal judgments, theories, or experiences irrespective of external criteria. External attribution relies on either frequencies of occurrence across multiple similar cases or causal propensities found in an exemplar. Since geosystems are complex, there exists epistemic uncertainty due to fundamental limitations in investigators’ theoretical and methodological abilities to understand how nature works. Ontic uncertainty also exists because “the physical world has an element of irreducible elusiveness” (Ben-Haim, 2014, p. 165).

Data sources and analysis. We analyzed data collected from 542 middle and high school students taught by nine teachers across six states. The schools represented a mix of urban, rural, and suburban settings. Among the students, 49% were male; 56% were White; 84% spoke English as their first language; and 66% used computers regularly for learning. We first used an emergent coding approach to students’ uncertainty attribution responses. From this, we identified thirteen distinctive categories and then merged them into five higher categories.

Results. The first level represents no information. At the second level, students express personal uncertainty attribution statements. The third level encompasses students’ nominal use of data without citing any specific details. The fourth level concerns scientific descriptions of theoretical basis or empirical findings associated with the investigation. At the fifth and highest level, students cite theoretical, empirical, measurement-related, and analytical limitations.

Significance. As uncertainty plays a critical role in science enterprise, it is imperative to foster similar skills in the process of educating students about the nature of science. Many 21st century issues, such as climate change, energy use, and sustainability, rely on being able to interpret and draw conclusions from models and incomplete data, where there is a large degree of uncertainty and possibly no clear answers. For classroom assessment, we have developed a science task format that incorporates uncertainty as a qualifier of their argument and a taxonomy to reliably distinguish students’ uncertainty attribution responses.

Authors

• Hee-Sun Lee, The Concord Consortium

• Amy R. Pallant, Concord Consortium