Naslov
Applying advanced linear models in the task of predicting student success

Autori
Glavaš, Marko ; Brkić Bakarić, Marija ; Matetić, Maja

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) / Biljanović, Petar - Opatija : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2018, 820-824

Skup
41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2018)

Mjesto i datum
Opatija, Hrvatska, 21.05.2018. - 25.05.2018

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Linear model, regularization, prediction of student success, lasso regression, ridge regression

Sažetak
The paper presents a comparative analysis of different linear models based on the Moodle data related to the course Programming 2 at the Department of Informatics, University of Rijeka. The task is to predict student final course success based on student activity represented by the initial set of features. We experiment with several methods with the aim to reduce the feature set in order to extract the most representative features thus increasing prediction accuracy. The interpretation of the obtained predictive models is given.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti

POVEZANOST RADA