Methodology for the design of a student pattern recognition tool to facilitate the teaching - Learning process through knowledge data discovery (big data)

Imagine a platform in which the teacher can access to identify patterns in the learning styles of students attached to their course, and in turn this will allow you to know which pedagogical techniques to use in the teaching process - learning to increase the probability of success in your classroom...

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Autores:
Viloria Silva, Amelec Jesus
Lis Gutierrez, Jenny Paola
Gaitan, Mercedes
Moreno Gomez, Gloria Cecilia
Kamatkar, Sadhana J.
Meza, Abel Ramiro
Tipo de recurso:
http://purl.org/coar/resource_type/c_f744
Fecha de publicación:
2018
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/1784
Acceso en línea:
https://hdl.handle.net/11323/1784
https://doi.org/10.1007/978-3-319-93803-5_63
https://repositorio.cuc.edu.co/
Palabra clave:
Identification of patterns
Knowledge Data Discovery and Development
Teaching-learning process
Rights
openAccess
License
Atribución – No comercial – Compartir igual
Description
Summary:Imagine a platform in which the teacher can access to identify patterns in the learning styles of students attached to their course, and in turn this will allow you to know which pedagogical techniques to use in the teaching process - learning to increase the probability of success in your classroom?. What if this tool could be used by students to identify the teacher that best suits their learning style?. Yes, was the tool able to improve its prediction regarding academic performance as time passes? It is obvious that this would require specialized software in the handling of large data. This research-development aims to answer these questions, proposing a design methodology of a student pattern recognition tool to facilitate the teaching-learning process through Knowledge Data Discovery (Big Data). After an extensive document review and validation of experts in various areas of knowledge, the methodology obtained was structured in four phases: identification of patterns, analysis of the teaching-learning process, Knowledge Data Discovery and Development, implementation and validation of software.