Impact of Gamification on Teaching Time Series with Machine Learning Models: A Practical Approach
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.
Authors
- Rafael Caparó (ORCID: https://orcid.org/0000-0003-1743-2435)
- Alberto Francisco Sánchez Camino (ORCID: https://orcid.org/0009-0004-0482-6464)
- Víctor Horacio Rodriguez Baca (ORCID: https://orcid.org/0000-0002-1191-8349)
- Bartolomé Macavilca Tello (ORCID: https://orcid.org/0009-0002-0062-2742)
Institutions
- National University of Engineering (PE)
Publication Details
- Published
- 2024-12-10
- DOI
- https://doi.org/10.1109/icalter65499.2024.10819239
- Primary Topic
- Educational Games and Gamification
- Type
- article
- Field-Weighted Citation Impact
- 0.00