Naslov
CRISP-DM process model in educational setting

Autori
Oreški, Dijana ; Pihir, Igor ; Konecki, Mario

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

Izvornik
Economic and Social Development, 20th International Scientific Conference on Economic and Social Development, Book of Proceedings / Li Yongqiang, Anica Hunjet, Ante Roncevic - Prag : VADEA ; City of Prague ; Sveučilište Sjever ; Faculty of Management University of Warsaw, 2017, 19-28

Skup
20th International Scientific Conference on Economic and Social Development

Mjesto i datum
Prag, Češka Republika, 27.04.2017. - 28.04.2017

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
academic success, data mining, decision tree, process model

Sažetak
Data mining techniques are being used in areas of prediction and classification, replacing traditional statistical approaches. Their application spans a wide variety of fields and education is one of them. This paper carries out a comprehensive methodology based on the CRISP DM process for data mining in order to gain insights into academic performance prediction. Paper explores to what extent socio-demographic variables, previous education, motivation and learning style can help in identifying successful students. Based on the decision tree method, profile of the typical successful information technology student is identified. Based on the research results it can be concluded that the academic performance is significantly influenced by previous education.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA