TRAINING DESIGN FOR DISTANCE RUNNING; HOW TO APPLY STATISTICS, DESIGN OF EXPERIMENTS, AND DATA SCIENCE FOR ACTIVE LEARNING IN UNIVERSITY STUDENTS Academic Article in Scopus uri icon

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 has also increased. This 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 have trained to increase their performance as athletes. Statistical methods allow the design of focused training to improve their time without affecting their physical and mental health. The introduction of data science, as well as the design of experiments, allows customising each training session according to information from each athlete, such as heart rate, VO2 Max, 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 five editions of the 5k and 10k race of the annual race of the Tecnologico de Monterrey Campus Querétaro are analysed, as well as of students who record daily data through recording devices which were processed in databases to calculate descriptive statistics and correlate efforts with the designed workouts. © 2024 Proceedings of the 26th International Conference on Engineering and Product Design Education: Rise of the Machines: Design Education in the Generative AI Era, E and PDE 2024. All rights reserved.

publication date

  • January 1, 2024