Gamifying the classroom for the acquisition of skills associated with Machine Learning: a two-year case study

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Áreas de investigación:
  • Sin categoría
Año:
2022
Tipo de publicación:
Artículo en conferencia
Autores:
Volumen:
532
Título del libro:
Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022), 13th International Conference on EUropean Transnational Education (ICEUTE 2022)
Serie:
Lecture Notes in Networks and Systems
Páginas:
224-235
Organización:
Universidad de Salamanca (Salamanca, España)
Mes:
5th - 7th September
ISBN:
978-3-031-18409-3
Abstract:
Machine learning (ML) is the field of science that combines knowledge from artificial intelligence, statistics and mathematics intending to give computers the ability to learn from data without being explicitly programmed to do so. It falls under the umbrella of Data Science and is usually developed by Computer Engineers becoming what is known as Data Scientists. Developing the necessary competences in this field is not a trivial task, and applying innovative methodologies such as gamification can smooth the initial learning curve. In this context, communities offering platforms for open competitions such as Kaggle can be used as a motivating element. The main objective of this work is to gamify the classroom with the idea of providing students with valuable hands-on experience by means of addressing a real problem, as well as the possibility to cooperate and compete simultaneously to acquire ML competences. The innovative teaching experience carried out during two years meant a great motivation, an improvement of the learning capacity and a continuous recycling of knowledge to which Computer Engineers are faced to.
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