Predicting first-year computer science students drop-out with machine learning methods: A case study
author
Maksimova, Natalja
Pentel, Avar
Dunajeva, Olga
statement of authorship
Natalja Maksimova, Avar Pentel, Olga Dunajeva
source
Educating Engineers for Future Industrial Revolutions : Proceedings of the 23rd International Conference on Interactive Collaborative Learning (ICL2020). Volume 2
location of publication
Cham
publisher
Springer International Publishing
year of publication
2021
pages
p. 719-726
series
Advances in Intelligent Systems and Computing ; 1329
conference name, date
ICL2020 – 23rd International Conference on Interactive Collaborative Learning, 23–25 September 2020, Virtual Conference
conference location
Tallinn, Estonia
url
https://doi.org/10.1007/978-3-030-68201-9_70
subject term
õppimine
kõrgkoolid
õppekorraldus
õpiraskused
Scopus
Conference proceedings at Scopus
Article at Scopus
WOS
Article at WOS
kvartiil
Q4
category (general)
Computer science
en
Arvutiteadus
et
Engineering
en
Tehnika
et
category (sub)
Computer science. General computer science
en
Arvutiteadus. Üldine arvutiteadus
et
Engineering. Control and systems engineering
en
Tehnika. Juhtimis- ja süsteemitehnika
et
name of the institution
Tallinna Tehnikaülikool. Virumaa Kolledž
keyword
students’ dropout
machine learning
prediction
ISSN
2194-5357
ISBN
978-3-030-68200-2
notes
Includes bibliogr
scientific publication
teaduspublikatsioon
classifier
3.1
TTÜ department
Virumaa kolledž
language
inglise