The Connected Biology project is a collaborative effort between Michigan State University and the Concord Consortium. We’re developing and researching a connected set of technology-enhanced three-dimensional lessons for high school biology that are aligned with NGSS performance expectations.
Our goal is to research how technology-based materials designed to foster interlinked, three-dimensional learning of high school genetics and evolution increase sophistication of student understanding of core ideas, crosscutting concepts, and science practices over time.
We are interested in how materials designed to support three-dimensional learning can support growing complexity in student understanding of the linked ideas of evolution, traits, and underlying molecular mechanisms through the practices of analyzing and interpreting data, constructing scientific explanations, and the crosscutting concepts of patterns and cause and effect.
We hypothesize that thoughtfully integrating the practices of science with a limited number of disciplinary core ideas and crosscutting concepts will support students’ development of a network of connected biological concepts that students can use to make sense of phenomena. This approach stands as a contrast and antidote to many approaches in biology education, which often treat topics as disconnected, resulting in learning of isolated facts over deep connections. We’re creating and researching an example of instructional materials for high school biology designed to foster students’ ability to construct scientific explanations of the relationships between molecules, cells, organisms, and populations and support them in analyzing and interpreting data to explain a variety of phenomena and their underlying causes.
We’re developing and studying the design of a multi-level simulation to support students in making connections across genetic and evolutionary phenomena and researching student learning when using this set of coherent biology materials.
- Reichsman, F. (2018). Connecting genetics and evolution with 3D learning. @Concord, 22(1), 12-13.