Predicting High School Students' Academic Performance: A Comparative Study of Supervised Machine Learning Techniques-Reference-Cited by-同舟云学术

Predicting High School Students' Academic Performance: A Comparative Study of Supervised Machine Learning Techniques

Published:2021-12-15 Issue: Volume: Page:
ISSN:
Container-title:2021 Machine Learning-Driven Digital Technologies for Educational Innovation Workshop
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Author:

Sanchez-Pozo Nadia N.¹,Mejia-Ordonez Juan S.¹,Chamorro Diana C.²,Mayorca-Torres Dagoberto³,Peluffo-Ordonez Diego H.⁴

Affiliation:

1. SDAS Research Group,Machine learning Research Program,Ben Guerir,Morocco

2. Universidad Técnica de Machala,Carrera de Ingeniería Química, Faculted de Ciencias Químicas y de la Salud,Machala,Ecuador

3. Universidad Mariana,Programa de Mecatrónica, Facultad de Ingeniería,Pasto,Colombia

4. Mohamed VI Polytechnique University,Modeling, Simulation, and Data Analysis (MSDA) Research Program,Ben Guerir,Morocco

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9733403/9733747/09733756.pdf?arnumber=9733756

Reference20 articles.

1. Using Machine Learning Algorithms to Predict People’s Intention to Use Mobile Learning Platforms During the COVID-19 Pandemic: Machine Learning Approach

2. Student personality prediction using Machine learning algorithms;tawde;Levant,2021

3. Classification of Graduates Student on Entrance Selection Public Higher Education Through Report Card Grade Path Using Support Vector Machine Method

4. Estudio comparativo de técnicas de minería de datos para develar patrones de desempeño académico en enseñanza media;chamorro-sangoquiza;Revista Ibérica de Sistemas e Tecnologias de Informação,2020

5. Predicting academic success in higher education: literature review and best practices

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