Improve the performance of students in the mathematics learning through Bayesian model
Abstract:
This paper shows the use of data mining techniques and math tools software as a supplementary educational resource in the understanding of mathematics. The performance process of mathematics in the first and third level of Computer Science and Electronics has used these data mining techniques and math tools as part of a formation process. Mathematics is fundamental in the formation process of educating the future professionals. Students from experimental groups used together with the teacher the Wolfram Mathematica software. The Bayesian model showed the prediction of the approval rate of the students. Part of the experience in this research was also getting the perception from students through a survey. As a result, we determined the need of this math package as a supplementary educational resource, which supports the capacity of calculus, and the interpretation of the non-trivial problems.
Año de publicación:
2017
Keywords:
- Bayesian model
- Wolfram software
- Data Mining
- Education
Fuente:
scopus
googleTipo de documento:
Conference Object
Estado:
Acceso restringido
Áreas de conocimiento:
- Inferencia bayesiana
- Aprendizaje automático
Áreas temáticas de Dewey:
- Matemáticas
- Escuelas y sus actividades; educación especial
- Educación
Objetivos de Desarrollo Sostenible:
- ODS 4: Educación de calidad
- ODS 17: Alianzas para lograr los objetivos
- ODS 9: Industria, innovación e infraestructura