Empirical Research Emerging Research Strand: A Unified Cross-domain Approach to Studying Learner Understanding of Emergence

Project: Research project

Project Details


Empirical Research Emerging Research Strand: A Unified Cross-domain Approach to Studying Learner Understanding of Emergence Empirical Research, Emerging Research Strand: A Unified, Cross-domain Approach to Studying Learner Understanding of Emergence Emergent phenomena play a central role in every scientific discipline, and the implications of this are important not just for scientists. Many phenomena of importance to Americans involve emergent phenomena, such as global climate change, urban planning, and epidemics. Emergence introduces concepts that challenge us to look for new ways to understand, explain, and shape the world, concepts so counterintuitive and outside our expectations that extensive training is required to master them (e.g., Resnick, 1994; Slotta & Chi, 2006). This proposal, submitted to the Emergent Research strand under the Empirical Research category, describes a project to develop a domain-general protocol for examining understanding of and diagnosing misconceptions about emergent phenomena. Currently, there is no integrated, empirically based theory of how learners represent emergent systems, nor is there a common set of tools and methods for assessing learner understanding. Some progress has been made, but the considerable challenges associated with simulating and displaying complex systems have taken up a significant portion of the research effort, (e.g., Resnick 1994; Wilensky, 1999; Klopfer & Begel, 2008). We could advance our understanding in this area more rapidly and efficiently if we had a domain-general theoretical frame to apply across contexts. Researchers would be able to model and assess learner knowledge in a way that would connect findings across domains, and examine learner understanding of emergence as a phenomenon independent of context. Reaching this goal will require focusing on core psychological representations and processes rather than specific behaviors, and developing common tools and methods for uncovering learner representations and misconceptions. The result would be an inventory template that could be adapted to specific phenomena or used to assess understanding of emergence as an abstract phenomenon. Guided by hypotheses that draw upon prior research into learning about complexity and emergence, as well as other relevant work in development, social psychology, and cognitive science, we will present simulations of emergent phenomena to participants. Working from verbal data elicited through structured interviews, we will develop item templates that can be readily adapted to a specific domain whilst preserving the basic concepts related to emergence. These will be used to further test our hypotheses, and to provide other researchers and educators with tools and methods that they can adapt to their area of interest, while maintaining reliability and validity. Intellectual merit. Many important questions about how people come to understand emergent systems require a more standardized, coordinated approach than has been possible so far. Jacobson and Wilensky (2006) point out that we do not yet know whether certain core concepts related to emergence are more challenging than others, or why. We do not have longitudinal data with which to examine developmental and educational trends in learners understanding over time. We lack a good way to compare curricula that teach emergence. To move forward, we need a common assessment instrument that captures the core principles of emergence and allows researchers to study diverse populations in diverse contexts over time with consistency and continuity. Broader impact . This project has the potential to improve science education and science literacy in the United States. Jacobson and Wilensky (2006) argue that we can and should close the gap that complexity research is creating between scientists and those who use science, such as policymakers and citizens. Too, teaching complex systems as part of science curricula may help to strengthen science education in the US, allowing us to streamline yet deepen the science curriculum (Sabelli, 2006), and build bridges between increasingly specialized and fragmented scientific disciplines (Goldstone,
Effective start/end date8/15/097/31/14


  • National Science Foundation (NSF): $674,180.00


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