Integrating the Three Dimensions of the NGSS into Curricula Using Published Biology Data

The Framework for K-12 Science Education and the Next Generation Science Standards (NGSS) delineate a vision for science education that integrates Disciplinary Core Ideas, Science Practices and Crosscutting Concepts. To address a lack of aligned curricula and assessments addressing all three dimensions, we developed and tested curriculum materials and assessment items for high school evolution instruction. Lesson development was guided by a research-based theory of change which posits that students will better understand evolution when instruction: (1) integrates core ideas about heredity, (2) allows students to use mathematics, data analysis, and evidence-based argumentation with skill-level-appropriate data from published research studies, and (3) leverages interactive, multimedia learning experiences for data collection and analysis. The six prototype high school lessons on natural selection integrate the following dimensions of the Framework and NGSS: (1) Life Science Disciplinary Core Ideas: Heredity and Biological Evolution (2) Science Practices: Analyzing and Interpreting Data, Using Mathematics and Computational Thinking, and Engaging in Argument from Evidence and (3) Crosscutting Concepts: Patterns, and Cause and Effect. Lessons were pilot tested using a treatment-only pre/post test design, with a nation-wide sample of 461 students in 20 biology classes, taught by 7 teachers. The instruments included a 15-item test (administered pre and post) and a post-enactment teacher survey. Paired t-test and chi-square analyses were conducted with matched student test scores to assess learning gains and misconception prevalence. Students (n=308) showed significant learning gains from pre-test (mean=52.92±1.20%) to post-test (mean=61.58±1.41%, t= 8.544, p<0.001). Learning gains were observed in data analysis (t=6.359, p<0.001), knowledge of natural selection theory (t=5.027, p<0.001), and genetics and heritability (t=5.711, p<0.001). We observed a decrease in the selection of distractors associated with intentional trait development (χ2=7.425, p=.007) and misinterpreting distributions as depicting changes over time (χ2=6.536, p=.007). We conclude that our approach holds preliminary promise for decreasing misconceptions and increasing students’ understanding of natural selection and graphs. Teachers reported that the lessons were innovative, easy to enact, and contained appropriate math, language and science content; all of the teachers reported that they would use the materials again.