Agile approach to a CS2-based course using the Jupyter notebook in lab classes

Guerra, Hélia; Gomes, Luís Mendes; Cardoso, Alberto

doi:10.1109/expat.2019.8876536

Cited by 7 publications

(4 citation statements)

References 7 publications

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“…The Rise of "Computational Narratives." Not surprisingly, Jupyter notebooks are used for teaching traditional computer science (Zastre 2019), as well as a number of advanced topics, including high-performance computing (Glick and Mache 2018); Internet of things, cloud computing, and blockchain (Rao and Dave 2019); agile development (Guerra et al 2019); and artificial intelligence (O'Hara et al 2015). Moreover, Jupyter notebooks are commonly used for teaching computer science to non-CS students (Smith 2016, Vial andNegoita 2018).…”

Section: Jupyter Notebooksmentioning

confidence: 99%

Interactive Computing for Accelerated Learning in Computation and Data Science

Alderson

2022

INFORMS Transactions on Education

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This article describes the motivation and design for introductory coursework in computation aimed at midcareer professionals who desire to work in data science and analytics but who have little or no background in programming. In particular, we describe how we use modern interactive computing platforms to accelerate the learning of our students both in and out of the classroom. We emphasize the importance of organizing the interaction with course material so that students learn not only to “think computationally” but also to “do computationally.” We provide details of existing courses in computation offered at the Naval Postgraduate School, and we describe their ongoing evolution in response to increased demand from members of the civilian and military workforce.

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Section: Jupyter Notebooksmentioning

confidence: 99%

Interactive Computing for Accelerated Learning in Computation and Data Science

Alderson

2022

INFORMS Transactions on Education

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“…In the field of higher education, applying the Jupyternotebook, the most related study was developed by Guerra et al [10]. The authors show how the Jupyternotebook tool can be used in a computer course.…”

Section: State-of-the-artmentioning

confidence: 99%

Digital signal processing course on Jupyter–Python Notebook for electronics undergraduates

Zúñiga-López

Avilés‐Cruz

2020

Comp Applic In Engineering

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The Jupyter–Python Notebook open source is currently used world‐wide as a programming environment for courses and labs. This paper describes an application of a set of Python computer programs implemented in the form of Jupyter notebooks to learn the course of digital signal processing and also seeks to contribute to the development of innovative teaching methodologies. A set of user‐friendly Jupyter notebooks workflows allows teachers–students to teach and learn theoretical concepts, description of problems, computer code, and simulation results with a graphical output. The proposed environment allows teachers/students to code their simulations in Python or Octave simulating languages. Additionally, a new approach involves student‐centered learning to teach theoretical and lab concepts.

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“…Jupyter notebooks are a convenient way to interweave code, text, and images in an interactive format. [18][19][20][21] Class communication is managed using Slack®, a collaboration platform with both general channels (similar to a group discussion board) for class-wide conversation and private messaging for student-student and student-instructor discussions. Students are also provided access to weekly office hours when in-person communication is preferred.…”

Section: Travismentioning

confidence: 99%