Show simple item record

Gamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Study

dc.contributor.authorDurán Rosal, Antonio Manuel
dc.contributor.authorGuijo Rubio, David
dc.contributor.authorVargas, Víctor M.
dc.contributor.authorGómez Orellana, Antonio
dc.contributor.authorGutiérrez, Pedro Antonio
dc.contributor.authorFernández, Juan Carlos
dc.date.accessioned2023-12-18T07:37:08Z
dc.date.available2023-12-18T07:37:08Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/20.500.12412/4821
dc.description.abstractMachine 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.es
dc.language.isoenges
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleGamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Studyes
dc.typeconferenceObjectes
dc.identifier.conferenceObjectInternational Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022)es
dc.identifier.doi10.1007/978-3-031-18409-3_22
dc.rights.accessRightsopenAccesses
dc.subject.keywordGamifying the classroomes
dc.subject.keywordSkills associatedes
dc.subject.keywordMachine learninges
dc.subject.keywordCase studyes


Files in this item

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivatives 4.0 Internacional
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 Internacional