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IES Grant

Title: Systems and Cycles: Using Structure-Behavior-Function Thinking as a Conceptual Tool for Understanding Complex Natural Systems in Middle School Science
Center: NCER Year: 2009
Principal Investigator: Hmelo-Silver, Cindy Awardee: Rutgers University
Program: Science, Technology, Engineering, and Mathematics (STEM) Education      [Program Details]
Award Period: 3 years Award Amount: $1,630,450
Type: Development and Innovation Award Number: R305A090210
Description:

Co-Principal Investigator(s): Rebecca Jordan, Ashok Goel, and Spencer Rugaber

Purpose: Complex systems are an important part of the world that we live in and, as such, are recognized as a key concept in national and local science standards. One promising approach for promoting student understanding of complex systems is Structure-Behavior-Function thinking. A Structure-Behavior-Function model of a system explicitly represents the configuration of components and connections (structure), the visible output (functions), and the internal causal processes (behaviors) of the system. The main goal of this study is to design and develop three middle school science curriculum units using Structure-Behavior-Function thinking as a conceptual tool for promoting students' understanding of ecosystems. The project team will also test the feasibility and usability of the model.

Project Activities: The researchers will develop three middle school science curriculum units on ecosystems (aquarium, local, and distal aquatic systems) covering 6-8 weeks of instruction. For each of the three units, the researchers will develop a suite of student tools, including hypermedia, computer simulations, and a Structure-Behavior-Function modeling environment. The curriculum units and tools will be iteratively developed, tested, and refined over the three-year project period.

Products: The products of this project will be three fully developed middle school science curriculum units focusing on ecosystems and their associated tools (hypermedia, computer simulations, and a Structure-Behavior-Function modeling environment). Additional products will include published reports.

Structured Abstract

Setting: The setting for this study includes suburban middle schools in New Jersey.

Population: Two to three suburban middle schools with diverse student populations will participate in the study. In each school, one to two science teachers with three to five classes per teacher (approximately 350 students) will participate.

Intervention: The researchers will develop three middle school science curriculum units on ecosystems covering 6–8 weeks of instruction. Specifically, the units will focus on aquariums, then local aquatic systems, and finally, distal aquatic systems. For each of the three units, the researchers will develop a suite of tools, including a Structure-Behavior-Function modeling environment, designed to help students understand the relationship between different levels of the ecosystem. The Structure-Behavior-Function modeling environment will allow students to access other software tools, including hypermedia and NetLogo computer simulations, and provide a notebook for students to record their observations from work with the software tools, as well as information gathered during physical data collection. The researchers will develop function-oriented hypermedia to give students some basic understanding of the ecosystems and to use as a reference. To make behaviors visible, the researchers will develop NetLogo computer simulations to model behaviors at both the micro- and macro-levels of the ecosystem.

Research Design and Methods: A design research approach will be used to develop the initial curriculum units and tools. An advisory board will review the materials for content and pedagogy and provide feedback for adapting and revising the curriculum units and tools. The researchers will implement the curriculum units and tools in classrooms and examine learning outcomes and processes from each trial to refine the theoretical approach, curriculum, and tools. Pilot testing and revisions of the curriculum units will occur, followed by a final test of the full set of materials in schools. Data will be collected on students' use of the hypermedia, computer simulations, Structure-Behavior-Function modeling tools, pre-test and post-test data, student engagement, and the artifacts students create. In addition, classroom observations will be conducted to study fidelity and variability in implementation.

Control Condition: There is no control condition.

Key Measures: Student artifacts, including completed worksheets and models, will be collected to examine how students conceive of the different ecosystems, how they are able to use Structure-Behavior-Function modeling as a tool for analyzing new ecosystems, and the sophistication of the models that they create. Researcher-developed pre- and post-tests will assess students' understanding of systems as well as their ability to solve "what-if" problems that ask students to describe the causes and consequences of disturbances of the system. The pre- and post-test measures will be adapted from prior measures examining mental models. Fidelity of implementation will be measured through videotaped classroom observations, questionnaires, student engagement measures, and log data analysis.

Data Analytic Strategy: The researchers will conduct fine-grained analyses of the videotaped classroom observation data and log file data to determine the usability and feasibility of the curriculum and tools. Statistical tests will be conducted to look for change over time in student worksheets and models, pre- and post-tests, and questionnaire data.

Publications

Book chapter

Hmelo-Silver, C.E., Jordan, R., and Sinha, S. (2013). Seeing to Understand: Using Visualizations to Understand Learning in Technology-Rich Learning Environments. In R. Luckin, J. Underwood, N. Winters, P. Goodyear, B. Grabowski, and S. Puntambekar (Eds.), Handbook of Design in Educational Technology . New York: Routledge Handbooks Online.

Journal article, monograph, or newsletter

Hmelo-Silver, C.E., Eberbach, C., and Jordan, R. (2014). Technology-Supported Inquiry for Learning about Aquatic Ecosystems. EURASIA Journal of Mathematics, Science & Technology Education, 10 (5): 405–413.

Hmelo-Silver, C.E., Jordan, R., Eberbach, C., and Sinha, S. (2017). Systems Learning with a Conceptual Representation: A Quasi-Experimental Study. Instructional Science, 45 (1): 53–72.

Jordan, R. C., Sorensen, A.E., and Hmelo-Silver, C. (2014). A Conceptual Representation to Support Ecological Systems Learning. Natural Sciences Education. Natural Sciences Education, 43 : 141–146.

Jordan, R.C., Brooks, W.R., Hmelo-Silver, C., Eberbach, C., and Sinha,S. (2014). Balancing Broad Ideas with Context: An Evaluation of Student Accuracy in Describing Ecosystem Processes after a System-Level Intervention. Journal of Biological Education, 48 (2): 57–62.

Sinha, S., Gray, S., Hmelo-Silver, C.E., Jordan, R., Eberbach, C., Goel, A., and Rugaber, S. (2013). Conceptual Representations for Transfer: A Case Study Tracing Back and Looking Forward. Frontline Learning Research, 1 (1): 3–23.

Sinha, S., Rogat, T.K., Adams-Wiggins, K.R., and Hmelo-Silver, C.E. (2015). Collaborative Group Engagement in a Computer-Supported Inquiry Learning Environment. International Journal of Computer-Supported Collaborative Learning, 10 (3): 273–307.

Vattam, S.S., Goel, A.K., Rugaber, S., Hmelo-Silver, C.E., Jordan, R., Gray, S., and Sinha, S. (2011). Understanding Complex Natural Systems by Articulating Structure-Behavior-Function Models. Educational Technology and Society, 14 (1): 66–81.

Proceeding

Eberbach, C., Hmelo-Silver, C.E., Jordan, R., and Sinha, S. (2012). Multiple Trajectories for Understanding Ecosystems. In Proceedings of the 10th International Conference of the Learning Sciences 2012 (pp. 411–418). Sydney, Australia: International Society of Learning Sciences.

Honwad, S., Hmelo-Silver, C.E., Jordan, R., Sinha, S., Eberbach, C., Goel, A., and Rugaber, S. (2011). Learning About Ecosystems in a Computer Supported Collaborative Learning Environment. In Proceedings of the CSCL2011 Connecting Research to Policy and Practice (pp. 982–983). Hong Kong, China: International Society for the Learning Sciences.

Sinha, S., Adams, K. Rogat, T.K., and Hmelo-Silver, C.E. (2012). The Role of Technologies in Facilitating Collaborative Engagement. In Proceedings of the 10th International Conference of the Learning Sciences, Volume II (pp. 489–490). Sydney, Australia: International Society of the Learning Sciences.


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