Impact of Gamification on Teaching Time Series with Machine Learning Models: A Practical Approach

Coronado R.J.C.; Baca V.H.R.; Tello B.M.; Camino A.F.S. · Proceedings of the 2024 IEEE 4th International Conference on Advanced Learning Technologies for Education and Research, ICALTER 2024 (2024) · DOI: 10.1109/icalter65499.2024.10819239

Resumen

This study evaluates the impact of gamification in teaching time series using machine learning in the Time Series Analysis course. Students are divided into two groups: the control group (section K), which follows a traditional method, and the treatment group (section L), which participates in gamified activities, such as simulations and competitions to solve real problems using ARIMA and LSTM models. Through performance metrics and satisfaction surveys, the study measures the effectiveness of gamification in understanding complex models and motivating students. Preliminary results suggest that the gamified group shows better performance and greater engagement in learning time series. This practical approach indicates that gamification not only improves academic performance but also encourages active participation, being an effective method for learning advanced statistical techniques. Recommendations are proposed to integrate these methods into other technical courses.

Instituciones: Universidad Nacional de Ingeniería