Variation is an important concept that underlies experimental design and data analysis. Incomplete understanding of variation can preclude students from designing experiments that adequately manage organismal and experimental variation, and from accurately conducting and interpreting statistical analyses of data. Because of the lack of assessment instruments that measure students’ ideas about variation in the context of biological investigations, we developed the Biological Variation in Experimental Design and Analysis (BioVEDA) assessment. Psychometric analyses indicate that BioVEDA assessment scores are reliable/precise. We provide evidence that the BioVEDA instrument can be used to evaluate students’ understanding of biological variation in the context of experimental design and analysis relative to other students and to their prior scores.

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Teaching assistants (TAs) often lead courses using curricula they did not design. Therefore, examining how curriculum and professional development (PD) interact to influence TAs’ teaching practices is critical. This study describes the effects of a curriculum and PD intervention in two contexts: when TAs are teaching curriculum that is explicitly linked to PD, and when teaching curriculum that is not linked to PD. The Intervention curriculum featured structured opportunities for reform-oriented teaching practices. The Intervention PD was situated in the context of these specific curriculum activities and modelled the desired teaching practices. TAs that participated in the intervention implemented more student-centered teaching practices than TAs that did not participate in the intervention, even when teaching curriculum that was not designed to be student-centered and was not linked to PD. A linear model of TAs’ teaching practices that included PD type, task cognitive demand and curriculum type indicates that cognitive demand has the largest relationship with teaching practices, followed by PD type. These results have implications for policy. They suggest that investment in curriculum-linked TA PD can be effective even when teaching curricula that is not linked to PD. Additionally, investment in development of higher-cognitive-demand tasks may be an effective strategy to support implementation of student-centered practices.

Biologists consider variability during biological investigations. A robust quantitative understanding of variability is particularly important during data analysis, where statistics are used to quantify variation and draw conclusions about phenomena while accounting for variation.

A model of variation in experimental design and analysis is presented. Using a quasi-experimental design, this research shows that a curriculum that uses a model-based approach to variation in experimental design and analysis improves student understanding when compared with peers who receive more traditional siloed instruction on these topics.