In this project, the investigators design and explore the use of agent based models in advancing high school students' understanding of evolutionary biology while promoting their computational thinking skills. Using the NetLogo programming environment, the students and teachers focus on the relationship of evolutionary change at the level of the organism (micro-evolution) with evolution at the population level (macro-evolution). This is one of the basic concepts in evolution that seems most difficult for students to grasp. The use of NetLogo is well-suited toward this end given that it can depict how changes at the individual level relate to shifts in the population of the organism as a whole.
The research examines the impact of using such methods on student outcomes including learning and student interest. The learning environment is designed to examine students working either alone or in pairs at laptop computers or as a group on a table top computer. Design research is used to explore the relative effects of these approaches. Inner city students in grades 9 through 11 are the study population.
This research is important because if learning technologies and modeling evolution as a computational problem can help overcome a critical sticking point in students' understanding in this area, which is core to the biology curriculum, then student learning of evolution can be improved. If the approach used by the investigators is effective, then it demonstrates that significant changes in the productivity of student learning can be achieved by the use of learning technology. In addition, the project expects to contribute to the theory and practice of learning using instructional technologies, agent based models, and computational models. Because inner city students are involved in the study, the findings should be particularly beneficial to this group.
