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  1. Free, publicly-accessible full text available January 1, 2023
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  4. de Vries, E. (Ed.)
    We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT.
  5. de Vries, E. (Ed.)
    We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT.
  6. We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT.
  7. 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.
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