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Introduction to Volume 7 Issue 1
Steven I. Gordonpp. 1–1
A brief introduction to this issue of the Journal of Computational Science Education from the editor.
Volume 7 Issue 1 — April 2016
Contents
Cognitive Aspects of Computational Modeling and Simulation in Teaching and Learning
Osman Yasarpp. 2–14
https://doi.org/10.22369/issn.2153-4136/7/1/1BibTeX
@article{jocse-7-1-1,
author={Osman Yasar},
title={Cognitive Aspects of Computational Modeling and Simulation in Teaching and Learning},
journal={The Journal of Computational Science Education},
year=2016,
month=apr,
volume=7,
issue=1,
pages={2--14},
doi={https://doi.org/10.22369/issn.2153-4136/7/1/1}
}
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We discuss cognitive aspects of modeling and simulation in an efficacy study of computational pedagogical content knowledge (CPACK) professional development of K-12 STEM teachers. Evidence includes data from a wide range of educational settings over the past ten years. We present a computational model of the mind based on an iterative cycle of deductive and inductive cognitive processes. The model is aligned with empirical research from cognitive psychology and neuroscience and it opens door to a whole series of future studies on computational thinking.
Introducing Teachers to Modeling Water in Urban Environments
Steven I. Gordon, Jason Cervenec, and Michael Durandpp. 15–20
https://doi.org/10.22369/issn.2153-4136/7/1/2BibTeX
@article{jocse-7-1-2,
author={Steven I. Gordon and Jason Cervenec and Michael Durand},
title={Introducing Teachers to Modeling Water in Urban Environments},
journal={The Journal of Computational Science Education},
year=2016,
month=apr,
volume=7,
issue=1,
pages={15--20},
doi={https://doi.org/10.22369/issn.2153-4136/7/1/2}
}
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Geoscience educators in K-12 have limited experience with the quantitative methods used by professionals as part of their everyday work. Many science teachers at this level have backgrounds in other science fields. Even those with geoscience or environmental science backgrounds have limited experience with applying modeling and simulation tools to introduce realworld activities into their classrooms. This article summarizes a project aimed at introducing K-12 geoscience teachers to project based exercises using urban hydrology models that can be integrated into their classroom teaching. The impact of teacher workshops on teacher's confidence and willingness to utilize computer modeling in their classes is also reported.
Computational Thinking as a Practice of Representation: A Proposed Learning and Assessment Framework
Camilo Vieira, Manoj Penmetcha, Alejandra J. Magana, and Eric Matsonpp. 21–30
https://doi.org/10.22369/issn.2153-4136/7/1/3BibTeX
@article{jocse-7-1-3,
author={Camilo Vieira and Manoj Penmetcha and Alejandra J. Magana and Eric Matson},
title={Computational Thinking as a Practice of Representation: A Proposed Learning and Assessment Framework},
journal={The Journal of Computational Science Education},
year=2016,
month=apr,
volume=7,
issue=1,
pages={21--30},
doi={https://doi.org/10.22369/issn.2153-4136/7/1/3}
}
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This study proposes a research and learning framework for developing and assessing computational thinking under the lens of representational fluency. Representational fluency refers to individuals ability to (a) comprehend the equivalence of different modes of representation and (b) make transformations from one representation to another. Representational fluency was used in this study to guide the design of a robotics lab. This lab experience consisted of a multiple step process in which students were provided with a learning strategy so they could familiarize themselves with representational techniques for algorithm design and the robot programming language. The guiding research question for this exploratory study was: Can we design a learning experience to effectively support individuals computing representational fluency? We employed representational fluency as a framework for the design of computing learning experiences as well as for the investigation of student computational thinking. Findings from the implementation of this framework to the design of robotics tasks suggest that the learning experiences might have helped students increase their computing representational fluency. Moreover, several participants identified that the robotics activities were engaging and that the activities also increased their interest both in algorithm design and robotics. Implications of these findings relate to the use of representational fluency coupled with robotics to integrate computing skills in diverse disciplines.
Revising and Expanding a Blue Waters Curriculum Module as a Parallel Computing Learning Experience
Ruth Catlett and David Tothpp. 31–39
https://doi.org/10.22369/issn.2153-4136/7/1/4BibTeX
@article{jocse-7-1-4,
author={Ruth Catlett and David Toth},
title={Revising and Expanding a Blue Waters Curriculum Module as a Parallel Computing Learning Experience},
journal={The Journal of Computational Science Education},
year=2016,
month=apr,
volume=7,
issue=1,
pages={31--39},
doi={https://doi.org/10.22369/issn.2153-4136/7/1/4}
}
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The party problem is a mathematical problem in the discipline of Ramsey Theory. Because of the problems embarrassingly parallel nature, its extreme computational requirements, and its relative ease of understanding implementation with a nave algorithm, it is well suited to serve as an example problem for teaching parallel computing. Years ago, a curriculum module for Blue Waters was developed using this problem. However, delays in the delivery of Blue Waters resulted in the module being released before Blue Waters was accessible. Therefore, performance data and compilation instructions for Blue Waters were not available. We have revised the module to provide source code for new versions of the programs to demonstrate more parallel computing libraries. We have also added performance data and compilation instructions for the code in the old version of the module and for the new implementations, which take advantage of the capabilities of the Blue Waters supercomputer now that it is available.
Abatement of Computational Issues Associated with Dark Modes in Optical Metamaterials
Matthew LePain and Maxim Durachpp. 39–45
https://doi.org/10.22369/issn.2153-4136/7/1/5BibTeX
@article{jocse-7-1-5,
author={Matthew LePain and Maxim Durach},
title={Abatement of Computational Issues Associated with Dark Modes in Optical Metamaterials},
journal={The Journal of Computational Science Education},
year=2016,
month=apr,
volume=7,
issue=1,
pages={39--45},
doi={https://doi.org/10.22369/issn.2153-4136/7/1/5}
}
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Optical fields in metamaterial nanostructures can be separated into bright modes, whose dispersion is typically described by effective medium parameters, and dark fluctuating fields. Such combination of propagating and evanescent modes poses a serious numerical complication due to poorly conditioned systems of equations for the amplitudes of the modes. We propose a numerical scheme based on a transfer matrix approach, which resolves this issue for a parallel plate metal-dielectric metamaterial, and demonstrate its effectiveness.