Search

When conducting biological investigations, experts constantly integrate their conceptual and quantitative understanding of variation with the design and analysis of the investigation. This process is difficult for students, because curricula often treat these concepts as separate components. This study describes the effect of a curricular intervention aimed at improving students' conceptual and quantitative understanding of variation in the context of experimental design and analysis. A model-based intervention curriculum consisting of five short modules was implemented in an introductory biology laboratory course. All students received the regular laboratory curriculum, and half of the students also received the Intervention curriculum. Students' understanding of variation was assessed using a published 16-question multiple-choice instrument designed and validated by the research team. Students were assessed before and after the intervention was implemented, and normalized gain scores were calculated. Students who received the intervention showed significantly higher normalized gains than students who did not receive the intervention. This effect was not influenced by students' gender or exposure to prior statistics courses and persisted into and through the following semester's laboratory course. These results provide support for the use of model-based approaches to improve students' understanding of biological variation in experimental design and analysis.

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

When conducting biological investigations, experts constantly integrate their conceptual and quantitative understanding of variation with the design and analysis of the investigation. This process is difficult for students, because curricula often treat these concepts as separate components. This study describes the effect of a curricular intervention aimed at improving students' conceptual and quantitative understanding of variation in the context of experimental design and analysis. A model-based intervention curriculum consisting of five short modules was implemented in an introductory biology laboratory course. All students received the regular laboratory curriculum, and half of the students also received the Intervention curriculum. Students' understanding of variation was assessed using a published 16-question multiple-choice instrument designed and validated by the research team. Students were assessed before and after the intervention was implemented, and normalized gain scores were calculated. Students who received the intervention showed significantly higher normalized gains than students who did not receive the intervention. This effect was not influenced by students' gender or exposure to prior statistics courses and persisted into and through the following semester's laboratory course. These results provide support for the use of model-based approaches to improve students' understanding of biological variation in experimental design and analysis.

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. Many students struggle to correctly apply a quantitative understanding of variation to statistically analyze data. We present quantitative and qualitative analyses of introductory biology students' responses on two pairs of multiple-choice questions querying two concepts related to the quantitative analysis of variation. More students correctly identify a mathematical expression of variation than correctly interpret it. Many students correctly interpret a nonsignificant p -value in the context of a very small sample size, but fewer students do so in the context of a large sample size. These results imply that many students have an incomplete quantitative understanding of variation. These findings suggest that instruction focusing on conceptual understanding, not procedural problem solving, may elevate students' quantitative understanding of variation., (Copyright © 2021 Hicks et al.)