As computing has become integral to the practice of science, technology, engineering and mathematics (STEM), the STEM+Computing program seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking and computing activities within STEM teaching and learning in early childhood education through high school (preK-12).
Science education research and standards documents emphasize the need for engaging students in the practices of scientists. Yet still little is known about how to engage students in one of the most central practices of science, theory building. The project will investigate how 8th grade students can engage in scientific theory building, including computatinal thinking, and how theory building can be integrated into their science curriculum. There are many ways scientists approach building theory. In some cases, they begin with data and abstract a relationship in order to more precisely describe it in terms of a mathematical model (i.e., aggregate pattern approach). In other cases, they posit the mechanism for a phenomenon, beginning with assumptions about a system (e.g., its elements and their interactions) and build a computational model that, when run, produces outcomes that can be explored (i.e., individual mechanism approach). No educational research studies have yet sought to characterize the commonalities and differences of the two approaches. The project will investigate the learning opportunities of each approach to theory building and use these results to create curricular units that integrate the two approaches. The project will contribute to the educational research base and disseminate project research findings for use by science teachers, curriculum developers, and instructional coaches.
The research aims to understand the character of 1) the theories the students produce; 2) the processes by which they produce their theories; and 3) the characteristics of student learning that result. These questions are addressed through lab-based studies that introduce students to phenomena by guiding them to either articulate the aggregate-level pattern seen in data or develop agent-based computational models that represent the mechanism behind the pattern. Findings will inform the design of curricular units that will be tested through design-based research in the third year. These findings will illuminate how the two approaches can be integrated to help students learn about both scientific phenomena and theory-building processes. The research will also extend insight into how the production of different representations affords different learning pathways. Products of the study will inform the development of curricular materials and software. The research will be of practical value by informing general principles for designing and conducting theory-building instruction. The software produced will extend the widely used NetLogo and NetTango platforms to facilitate building theoretical computational models.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
