| dc.contributor.author | Durán Rosal, Antonio Manuel | |
| dc.contributor.author | Guijo Rubio, David | |
| dc.contributor.author | Vargas, Víctor M. | |
| dc.contributor.author | Gómez Orellana, Antonio | |
| dc.contributor.author | Gutiérrez, Pedro Antonio | |
| dc.contributor.author | Fernández, Juan Carlos | |
| dc.date.accessioned | 2023-12-18T07:37:08Z | |
| dc.date.available | 2023-12-18T07:37:08Z | |
| dc.date.issued | 2023 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.12412/4821 | |
| dc.description.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. | es |
| dc.language.iso | eng | es |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
| dc.title | Gamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Study | es |
| dc.type | conferenceObject | es |
| dc.identifier.conferenceObject | International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) | es |
| dc.identifier.doi | 10.1007/978-3-031-18409-3_22 | |
| dc.rights.accessRights | openAccess | es |
| dc.subject.keyword | Gamifying the classroom | es |
| dc.subject.keyword | Skills associated | es |
| dc.subject.keyword | Machine learning | es |
| dc.subject.keyword | Case study | es |