Open AccessDevelopment of machine learning implementation in engineering education: A literature review
Author(s) -
Firdamdam Sasmita,
Budi Mulyanti
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/830/3/032061
Subject(s) - context (archaeology) , engineering education , computer science , science and engineering , mathematics education , artificial intelligence , engineering management , engineering ethics , engineering , psychology , paleontology , biology
This study has aims to determine the development of implementing machine learning in several engineering majors. The used method was a literature study, and secondary data was used from reputable international journals and published in 2015 to 2019 from each publisher, which is IEEEXplore, Springer Link, Science Direct, ERIC, and Google Scholar. The author was summarized and analysed articles obtained based on the year of publication and the context of the article. Results show that machine learning has been widely applied in engineering education through fourteen contexts, one of which is Prediction Student Academic Performance, which has continuous development from 2013 to 2019. And the total number of engineering majors that are implementing machine learning was 13 majors. This research was expected to be an illustration, reference, and consideration for technicians in engineering education to give more attention and can be applied in schools, universities, and other engineering institutions in Indonesia country.