TRAINING DESIGN FOR DISTANCE RUNNING; HOW TO APPLY STATISTICS, DESIGN OF EXPERIMENTS, AND DATA SCIENCE FOR ACTIVE LEARNING IN UNIVERSITY STUDENTS

DS 131: Proceedings of the International Conference on Engineering and Product Design Education (E&PDE 2024)

Year: 2024
Editor: Grierson, Hilary; Bohemia, Erik; Buck, Lyndon
Author: Gonzalez Almaguer, Carlos Alberto; Saavedra Gastelum, Veronica; Zubieta Ramírez, Claudia; Sanchez Gallardo, Aranza; Frias Reid, Natalia
Series: E&PDE
Institution: Tecnologico de Monterrey
Page(s): 348 - 353
DOI number: 10.35199/EPDE.2024.59
ISBN: 978-1-912254-200
ISSN: 3005-4753

Abstract

In recent years, long-distance races have boomed all over the world. Mexico is no exception, but just as the enthusiasm for races over 5k has increased, the rate of sudden heart attacks is due to not having personalised and adequate training. The following paper describes how, based on design and engineering techniques, young students at the Tecnologico de Monterrey are trained to increase their performance as athletes. Statistical methods that allow the design of focused training to improve their times, but without affecting your physical and mental health. The introduction of data science, as well as the design of experiments, allows customizing each training session according to information from each athlete, such as heart rate, VO2max, weight, blood pressure, and the level of red and white blood cells, as well as running technique factors such as stride length, arm stroke technique, and stride. This allows students to actively learn about the application of statistical engineering, which will later allow them to transfer said knowledge to their professional field, making analogies between sport and a disciplinary competition. The results of more than 5 editions of the 5k and 10k race of the annual race of the Tecnologico de Monterrey Campus Querétaro were analyzed. Also, the information from some students who recorded their data through recording devices was processed in databases to calculate descriptive statistics and correlate the designed workouts with individual efforts.

Keywords: Distance Training, Data Science, Statistics, Educational Innovation, Higher Education

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