Page 170 - Getting the Picture Modeling and Simulation in Secondary Computer Science Education
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Chapter 7
We developed teaching materials to support the research of students’ understanding (M2) and methods of assessment (M4). However, the instructional strategies (M3) themselves were not explored. We suggest to perform research about successful instructional strategies for Computational Science. The teaching materials developed as spin-off of this project and our assessment instrument can form the basis for this research.
Our assessment instrument based on the SOLO taxonomy is in line with the suggestions and needs expressed by CS teachers and provides for holistic assessment of the learning objectives related to Computational Science. We suggest to research the development of similar assessments instruments focusing not only on the computational concepts, but also computational practices and computational perspectives for, on one hand, other learning objectives of computer sciences, and on the other hand, for learning objectives within other disciplines where computational thinking is involved.
In this project, we focused on research of teaching Computational Science from within a CS course. Computational Science aims to provide CS students with tools, techniques and skills to use modeling and simulation when exploring phenomena in various scientific disciplines outside of CS. We suggest to extend this research along three dimensions. First, following our original line of enquiry further and considering that computational models can produce large quantities of data, we suggested a line of inquiry in the wake of another science paradigm shift — from computational approach that models and simulates complex phenomena to the one that focuses on the exploration of data and unifies theory, experiment and simulation (Hey et al., 2009). By engaging in the practices of data science that bring together computational thinking and mathematical thinking, the students developing models and performing simulations with them would be given a further opportunity to engage in doing science by means of more thorough analysis of the data produced by their simulations. Since this type of activity happened only marginally within this project, we suggest further research into this specific issue. Second, extending the scope, we propose a new vantage point — the perspective of computational thinking in context — and suggest to explore students’ understanding, challenges, and difficulties related to the learning of the disciplinary content for which they make models and perform simulations as described in the learning objectives of Computational Science. Third, as an extension of the previous suggestion, we propose to explore pedagogical aspects of






























































































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