Naslov
Improving University Operations with Data Mining: Predicting Student Performance

Autori
Dragičević, Mladen ; Pejić Bach, Mirjana ; Šimičević, Vanja

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

Izvornik
World Academy of Science, Engineering and Technology, International Science Index / - Firenza : München : World Academy of Science, Engineering and Technology (WASET), 2014, 556-571

Skup
ICMTA 2014: International Conference on Management Technology and Applications

Mjesto i datum
Venecija, Italija, 14.04.2014. - 15.04.2014

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Data mining ; knowledge discovery in databases ; prediction models ; student success

Sažetak
The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija, Informacijske i komunikacijske znanosti

Napomena
International Conference on Management Technology and Applications (ICMTA 2014) : proceedings

POVEZANOST RADA