The recent next generation science standards in the United States have emphasized learning about complex systems as a core feature of science learning. Over the past 15 years, a number of educational tools and theories have been investigated to help students learn about complex systems; but surprisingly, little research has been devoted to identifying the supports that teachers need to teach about complex systems in the classroom. In this paper, we aim to address this gap in the literature. We describe a 2-year professional development study in which we gathered data on teachers' abilities and perceptions regarding the delivery of computer-supported complex systems curricula. We present results across the 2 years of the project and demonstrate the need for particular instructional supports to improve implementation efforts, including providing differentiated opportunities to build expertise and addressing teacher beliefs about whether computational-model construction belongs in the science classroom. Results from students' classroom experiences and learning over the 2 years are offered to further illustrate the impact of these instructional supports.

StarLogo The Next Generation (TNG) enables secondary school students and teachers to model decentralized systems through agent-based programming. TNG's inclusion of a threedimensional graphical environment provides the capacity to create games and simulation models with a first-person perspective. The authors theorize that student learning of complex systems and simulations can be motivated and improved by transforming simulation models of complex systems phenomena (specifically this study examines systems including epidemics and Newtonian motion) into games. Through this transformation students interact with the model in new ways and increase their learning of both specific content knowledge and general processes such as inquiry, problem solving and creative thinking. During this study several methods for connecting the simulations to game dynamics were tried, ranging from student-created games, to altering existing games, to students playing premade games. This article presents the results of research data from two years of curriculum development and piloting in northern Massachusetts science classrooms to demonstrate the successes and challenges of integrating simulations and games. This article also explores the results of these interventions in terms of ease of implementation, student motivation and student learning.Two teams are building models of virtual worlds. They each need to consider the relevant aspects of the world that they want to represent, focusing on what is important for their purposes, and what is superfluous. They also need to consider how they will provide appropriate inputs into their system and understand the output of their models, including whether the feedback that the models provide is clear. Each team needs to cleverly devise algorithms that appropriately represent the actions and behaviors of the inhabitants of their virtual world, and investigate the outcomes that they observe.In many ways the actions of these two teams are indistinguishable. However, as the products progress, the differences become more pronounced -one team is developing and studying a simulation of warming seas designed to help scientists save endangered species; the other is building a jet ski racing game designed to entertain. Both of these products require good initial models of fluid dynamics, tide flow, buoyancy, and many other physical parameters as a starting place. They may both incorporate information about how weather impacts the oceans -either to make the simulation more accurate or to make the game more exciting. The simulation requires important biological parameters to describe the ocean inhabitants, whereas the game requires important physical information to simulate the behavior of the jet ski under different ocean conditions. Of course there are distinct differences between the way the game and the simulation are developed and studied. These differences allow the simulation to be more predictive, and the game to be more engaging. But perhaps they are more similar than distinct.It is thi...

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We present a curriculum and instruction framework for computer-supported teaching and learning about complex systems in high school science classrooms. This work responds to a need in K-12 science education research and practice for the articulation of design features for classroom instruction that can address the Next Generation Science Standards (NGSS) recently launched in the USA. We outline the features of the framework, including curricular relevance, cognitively rich pedagogies, computational tools for teaching and learning, and the development of content expertise, and provide examples of how the framework is translated into practice. We follow this up with evidence from a preliminary study conducted with 10 teachers and 361 students, aimed at understanding the extent to which students learned from the activities. Results demonstrated gains in students' complex systems understanding and biology content knowledge. In interviews, students identified influences of various aspects of the curriculum and instruction framework on their learning.

The purpose of this study was to investigate how computational modeling promotes systems thinking for English Learners (ELs) in fifth-grade science instruction. Individual student interviews were conducted with nine ELs about computational models of landfill bottle systems they had developed as part of a physical science unit. We found evidence of student engagement in four systems thinking practices. Students used data produced by their models to investigate the landfill bottle system as a whole (Practice 1). Students identified agents and their relationships in the system (Practice 2). Students thought in levels, shuttling between the agent and aggregate levels (Practice 3). However, while students could think in levels to develop their models, they struggled to engage in this practice when presented with novel scenarios (e.g., open vs. closed system). Finally, students communicated information about the system using multiple modalities and less-than-perfect English (Practice 4). Overall, these findings suggest that integrating computational modeling into standards-aligned science instruction can provide a rich context for fostering systems thinking among linguistically diverse elementary students.