Gamified recreational exercise focused on Markov Chains

The gamified recreational exercise focused on Markov Chains is an innovative methodology that combines learning with play to facilitate the understanding of statistical and mathematical concepts. Markov Chains are models that describe systems that transition between different states, where the probability of moving to a future state depends only on the current state and not on previous ones. By integrating game elements, such as challenges, rewards and competition, we seek to motivate students to actively engage in the learning process. This approach makes learning more engaging and gives participants a hands-on experience of how Markov Chains work in real situations. Exercises may include simulations, board games, or digital applications that represent scenarios where students must make decisions based on probabilities. Through gamification, teamwork and problem solving are encouraged, essential skills in today's world. The gamified recreational exercise is a favorable tool for teaching Markov Chains, it makes learning more dynamic and effective.

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Publication Details

Journal
Gamification and Augmented Reality.
Published
2024-09-08
DOI
https://doi.org/10.56294/gr2024.72
Primary Topic
Educational Games and Gamification
Type
article
Field-Weighted Citation Impact
0.00
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article

Gamified recreational exercise focused on Markov Chains

Margarita María Castellanos Flórez, Luisa Fernanda Moreno-Galvis Luis F., Paula Andrea Duarte Amado
Gamification and Augmented Reality.
Educational Games and Gamification
article

Gamified recreational exercise focused on Markov Chains

Margarita María Castellanos Flórez, Luisa Fernanda Moreno-Galvis Luis F., Paula Andrea Duarte Amado
article en

Abstract

The gamified recreational exercise focused on Markov Chains is an innovative methodology that combines learning with play to facilitate the understanding of statistical and mathematical concepts. Markov Chains are models that describe systems that transition between different states, where the probability of moving to a future state depends only on the current state and not on previous ones. By integrating game elements, such as challenges, rewards and competition, we seek to motivate students to actively engage in the learning process. This approach makes learning more engaging and gives participants a hands-on experience of how Markov Chains work in real situations. Exercises may include simulations, board games, or digital applications that represent scenarios where students must make decisions based on probabilities. Through gamification, teamwork and problem solving are encouraged, essential skills in today's world. The gamified recreational exercise is a favorable tool for teaching Markov Chains, it makes learning more dynamic and effective.

Gamification and Augmented Reality.Vol. 2
Universidad Industrial de Santander (CO)
Quality Education
Openalex Percentile: Top 81%
Educational Games and Gamification
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