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Revolutionizing Education: How Python is Essential Beyond Computer Science

Liffey B
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30 minutes


Python has had a transformational effect on countless fields so far, but its permeation can be accelerated through the integration of Python into non-computing coursework. Currently, Python’s presence within secondary and post-secondary schools varies greatly between different institutions, but the continuity in the lack of interdisciplinary coursework is a key limiting factor in the widespread growth of computing education. This is due to a variety of factors, including stereotypes and policy issues, but the bottom line is that Python being restricted to only computing classes restricts career opportunities and misrepresents the professional world. With support from a case-study of college-level physics students exposed to scientific programming, we propose novel methods of integrating Python into traditional coursework during this talk. The overarching mission of this discussion is to demonstrate how Python literacy in non-computing coursework can ultimately help in streamlining processes and accelerating progress in various industries. Attendees will have the opportunity to hear about the exciting prospect of expanding Python beyond the confines of computer science, and will have an exclusive look at a case-study that offers insight into student benefits of integrated coursework: as concerned stakeholders, it is ultimately well-informed Python community members who must unite to make a positive impact on the education system.

TalkEducation, Teaching & Further Training


Introduction and Motivation:

The goal of many within the Python community has been to increase the reach of computer science education in classrooms and institutions around the world. Various studies have pointed out the problem-solving and planning abilities forged by computer science coursework (Salehi et al., 2020; Arfé et al., 2020), and other research has investigated the social stigma (McCartney et al., 2017) and instructor bottlenecks (Raman et al., 2015) that inhibit accessibility to computer science courses. In recent years, significant steps have been taken towards increasing computer science education. However, most of these efforts are largely focused on the introduction of standalone computer science courses rather than integrated coursework.

In this talk, we explore the seldom-discussed idea of integrating programming into traditional, non-computing fields such as mathematics, social studies, and science. Interdisciplinary coursework is not a new concept in education: students in an English class are expected to be able to understand, produce, and analyze data visualizations, and mathematics students learn to communicate their work formally in language (Lynch, 2020). However, the current belief in the education realm is that computer science is only for a small sect of highly capable students expressing a deep career interest in the field, a clear misconception that has been debunked by studies (Patitsas et al., 2019) and the experiences of countless professionals applying computational resources in traditionally non-computing industries. As a result of such factors, computer science education is fundamentally isolated from the core curriculum, which is to the detriment of learners and the fields that they pursue.

In support of the discussion, we unveil the results of surveys given to physics students enrolled in college-level coursework. In this case-study, students of varied backgrounds in computing are given a lecture on chaotic dynamical systems, and are then shown Python-implemented Runge-Kutta numerical integration methods and simulations to solve and visualize the systems. The insights provided by these students provide great perspective on benefits, reception, and nuances in integrating Python into core classes. Overwhelmingly, many indicated that they believed that the Python demonstrations aided in their understanding of the material. For the attendee, this exclusive look at a case-study will help develop a well-informed perspective on the role of Python beyond just computer science.

We conclude the presentation with recommendations for integrated Python coursework, calling for global policymakers and Python community members to step forward and do their part as stakeholders. We pinpoint why Python is the best choice, touching on factors such as its readable syntax, high volume of functional open-source libraries, ever-growing industry demand. The versatility afforded by such elements makes learners of all backgrounds better equipped for solving the challenging problems they will face in their careers. Community members in attendance will gain essential knowledge regarding the issue of Python integration, making them better equipped to argue on behalf of the educational community.

For students, seeing how complex differential equations can be numerically approached and solved by computers, understanding how new solar systems are discovered by crunching vast astronomical data, and witnessing a computer rapidly sequence a lengthy DNA chain forges an instant, permanent connection that fosters career interests and prepares students for an increasingly computerized professional world. We seek to advocate for every student to have this opportunity.

The key takeaway for talk attendees will be a fresh perspective on the issue of Python’s absence beyond the confines of computer science coursework, as well as methods for mitigation and steps that they can take. Changing education with programming is a long-term investment that will unequivocally accelerate student preparedness and capabilities, but it begins with the focused efforts of an informed public rallying in support of progress.

Schedule and Format:

5 minutes: The problem of computer science in education and why we should focus on increasing Python’s role in non-computing classes

10 minutes: Presenting research: a case study on introducing scientific Python to physics students

5 minutes: Why Python is the best option and the role and impact on the Python community

5 minutes: Proposals for Solutions to the Problem

5 minutes: Question and Answer Session

The speaker

Srivatsa Kundurthy

Srivatsa Kundurthy is a student based in the Greater New York City Area. As a Python practitioner, his projects include Open Source Intelligence tools for extracting public data and Python notebooks for explaining and simulating chaotic dynamical systems. His work in machine learning includes studying computer vision for problems in ecology and researching neural networks for predicting states of chaotic dynamical systems. Additionally, he is working with the LAION Research Group to develop and strengthen the world’s largest image-text dataset. Apart from Machine Learning Research, Srivatsa is greatly interested in technology policy and community-related issues, particularly those extending to the accessibility of programming education. On the side, Srivatsa enjoys science communication and stargazing.

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