T25 Connecting High School and Undergraduate Students to the Geosciences through Multidisciplinary Approaches to Geologic Issues (Posters)

Sunday, 9 October 2022
9:00 AM - 1:00 PM
Exhibit Hall F

THE NASA STEM PROGRAM ALLOWS STUDENTS TO APPLY PYTHON-BASED PROGRAMMING LANGUAGE TO IMPROVE DATA COLLECTION, ANALYSIS, AND ORGANIZATION OF GEOLOGICAL DATA

Paper number: T25-12
Program: Technical Sessions
Time: 9:00 AM – 1:00 PM

Authors

Abstract

The York College-hosted NASA STEM Program presents an introduction to computer programming with an emphasis on learning Python, building high school students’ foundation of coding, developing and improving computational thinking and problem-solving skills. This program assumes no previous programming experience. With the knowledge of programming, it can be used in a variety of applications. Python is able to act as a tool to improve data collection, analysis, organization, and many more based on the user's input on geological data. Students are exposed to a limitless amount of combinations of commands, making it possible to achieve almost any assignment from a beginner level to an advanced level with critical thinking and systematic logical reasoning. Throughout this program, it is clear that students have been improving their problem-solving skills through daily lectures, labs and lecture activities that are followed by visual representations. From a survey, many students wrote they gained a better understanding of the concept and practice through explanations and examples. The utilization of this programming language is essential as they can be incorporated into real life in a diverse field. Python is becoming an effective digital tool for geoscientists and geophysicists considering its capability to quickly load, analyze, plot and generate professional style geological report based on a plethora of geological data. Using snippets, one can manipulate arrays and field data (numpy); spatial data in three dimensions, and assess geological properties. Visualization of field and laboratory-based physical and chemical data, GIS and Remote Sensing, and Machine Learning (ML) are interconnected and can empower geoscience students to predict and estimate physical and chemical attributes controlling geologic processes by employing complex algorithms. Nowadays tremendous growth associated with cutting edge technology, data management from different geological parameters warrant the use of machines to identify trends, establish correlation and eventually devise a viable classification scheme for both exploration and research purposes.

Geological Society of America Abstracts with Programs. Vol. 54, No. 6

doi: 10.1130/abs/2022AM-379851

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