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Effective Self Attention Modeling for Aspect Based Sentiment Analysis Read chapter Read first chapter

2019 | OriginalPaper | Chapter

A Learner-Centered Approach to Teaching Computational Modeling, Data Analysis, and Programming

Authors : Devin Silvia, Brian O’Shea, Brian Danielak

Published in: Computational Science – ICCS 2019

Publisher: Springer International Publishing

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Abstract

One of the core missions of Michigan State University’s new Department of Computational Mathematics, Science, and Engineering is to provide education in computational modeling and data science to MSU’s undergraduate and graduate students. In this paper, we describe our creation of CMSE 201, “Introduction to Computational Modeling and Data Analysis,” which is intended to be a standalone course teaching students core concepts in data analysis, data visualization, and computational modeling. More broadly, we discuss the education-research-based rationale behind the “flipped classroom” instructional model that we have chosen to use in CMSE 201, which has also informed the design of other courses taught in the department. We also explain the course’s design principles and implementation.

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previous chapter Redesigning Interactive Educational Modules for Combinatorial Scientific Computing
next chapter Enabling Interdisciplinary Instruction in Computer Science and Humanities
Footnotes
2
Although it is now a requirement in three degree programs and one minor, and a selective or elective course in several other degrees and minors.
 
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Metadata
Title
A Learner-Centered Approach to Teaching Computational Modeling, Data Analysis, and Programming
Authors
Devin Silvia
Brian O’Shea
Brian Danielak
Copyright Year
2019
Book
Computational Science – ICCS 2019

Print ISBN: 978-3-030-22749-4

Electronic ISBN: 978-3-030-22750-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-22750-0_30

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