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Scientists use models and graphs to distinguish among factors that impact a phenomenon (for example, the impact of CO2 accumulation on climate change) and factors that do not impact the phenomenon (for example the role of ozone depletion on climate change). In this paper, we compare two forms of exploration of time series line graphs: plan and typical. In the plan condition, students plan an experiment with a model by graphing the level of a system parameter (e.g., concentration of greenhouse gases) and the predicted response of an outcome variable (e.g., temperature). They then run the model to observe the accuracy of their predictions. In the typical condition, students run the simulation immediately and adjust the parameter level as they see fit. Students produced more informative experiments in the plan condition than the typical condition. Students in the plan condition made inferences by comparing their prediction to the outcome. 

Computational Thinking (CT) can play a central role in fostering students' integrated learning of science and engineering. We adopt this framework to design and develop the Water Runoff Challenge (WRC) curriculum for lower middle school students in the USA. This paper presents (1) the WRC curriculum implemented in an integrated computational modeling and engineering design environment and (2) formative and summative assessments used to evaluate learner’s science, engineering, and CT skills as they progress through the curriculum. We derived a series of performance measures associated with student learning from system log data and the assessments. By applying Path Analysis we found significant relations between measures of science, engineering, and CT learning, indicating that they are mutually supportive of learning across these disciplines. 

We articulate a framework for using computational modeling to coherently integrate the design of science and engineering curricular experiences. We describe how this framework informs the design of the Water Runoff Challenge (WRC), a multi-week curriculum unit and modeling environment that integrates Earth science, engineering, and computational modeling for upper elementary and lower middle school students. In the WRC, students develop conceptual and computational models of surface water runoff, then use simulations incorporating their models to develop, test, and optimize solutions to the runoff problem. We conducted a classroom pilot study where we collected students’ learning artifacts and data logged from their use of the computational environment. We illustrate opportunities students had to integrate science, engineering, and computational thinking during the unit in a pair of contrasting vignettes.