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Abstract Detail

Teaching Section

Weeks, Andrea [1].

Training the next generation of biodiversity scientists to write and analyze data at George Mason University, botany included!.

The Biology Program at George Mason University revised its core undergraduate curriculum in 2011 to achieve two ends: to update the essential set of concepts and skills each student receives in line with the recommendations from the AAAS (2009; Vision and Change in Undergraduate Biology Education: A Call to Action) and to transition students more quickly to upper-division courses directly related to their specific interests. The Program identified evolution as a central concept for the new curriculum and the ability to analyze, interpret and communicate scientific data as the skill most in need of strengthening among our majors. As a consequence, the Program created two large enrollment, five credit majors' courses (>200 student/semester) that incorporate weekly small group recitation sections (<30 students each) to achieve these new programmatic goals. Recitation sections of both courses, Ecology and Evolution (BIOL308) and Biodiversity (BIOL310), incorporate extensive writing assignments and statistical analyses of student-generated experimental data to help build our biology majors' competencies in these areas. Several new botany-based teaching experiments were developed for these courses. The goal of this presentation is to share the logistics of managing these recitation activities across a hyper-diverse student population, our progress in meeting our goals for student learning, and the practical details of the botany-based writing assignments and teaching experiments used in laboratory and recitation.

Broader Impacts:

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1 - George Mason University, Undergraduate Biology Program and Department of Environmental Science and Policy, 4400 University Drive, Fairfax, VA, 22030, USA

data analysis
statistical tests

Presentation Type: Oral Paper:Papers for Sections
Session: 39
Location: Delaware A/Hyatt
Date: Tuesday, July 10th, 2012
Time: 1:30 PM
Number: 39001
Abstract ID:896

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