Supporting evidence-based reasoning in science education : an examination of pedagogical and technological approaches
Keywords: Education.

Science education reforms have been pushing for evidentiary reasoning to become a central part of classroom instruction (Quinn, Schweingruber, & Keller, 2012). Yet, how to design approaches that engage students in evidentiary reasoning in disciplinary meaningful ways is still not well understood (McNeill & Berland, 2017). The challenge is to create opportunities for students to grapple with essential decisions of evidentiary reasoning while providing the necessary supports for students to do so "productively". A central characteristic of productive engagement is the level of precision in reasoning; imprecise reasoning can lead to wrong interpretations and conclusions, and is prone to biases (Chinn & Malho- tra, 2002a). I have addressed this issue with a set of online and classroom studies. The studies build on a line of work that points to the potential of explicit juxtaposition of alternative explanations to improve precision in evidentiary reasoning (Lombardi, Bailey, Bickel, & Burrell, 2018). In the first part of the dissertation, I present a series of online studies with adult learners that examine how the impact of alternative explanations on evidentiary reasoning depends on the explanatory distance between alternative explanations. I define the explanatory distance between explanations based on the similarity of proposed mechanisms, and based on the extent to which the provided data relates to each explanation. The studies show that the explicit juxtaposition of alternative explanations increases precision in evidentiary reasoning when the explanations are "close" to each other; the juxtaposition biases evidentiary reasoning when the explanations are "far" from each other. "Close" alternative explanations help a. identify and interpret evidentiarily relevant data patterns (Studies 1 & 2), b. correctly evaluate the plausibility of explanations (Studies 1& 2), and c. notice mechanistically relevant data features (Study 3). However, Study 3 also showed that the extent to which close alternative explanations can support evidentiary reasoning is limited in the context of "full" evidentiary reasoning. Additional support is needed to help people generate the evidentiary basis from raw data, in particular when their disciplinary knowledge is limited. The second part of the dissertation was dedicated to development and implementation of a new web-based technology for enabling and supporting evidentiary reasoning in K-12 life science classrooms. I designed the technology based on the core idea to create computer simulations of the models to be evaluated, and to project the simulated data into the same representational space as the real data (in line with the Bifocal Modeling framework of Blikstein (2014)). In the final study, I implemented the technology in a week-long inquiry unit for 7th grade life science classrooms. The purpose of the study was threefold: 1. To examine to what extent the technology-based approach could get student to successfully engage in evidentiary reasoning; 2. To examine whether different types of evaluation activities using the technology influence the precision and consistency in evidentiary reasoning; 3. To what extent the explicit juxtaposition of close alternative models fosters mechanistic understanding.