Napredna pretraga

Pregled bibliografske jedinice broj: 1021203

Predicting students' success using Neural Networks


Bilal Zorić, Alisa
Predicting students' success using Neural Networks // Proceedings of the ENTRENOVA -ENTerprise REsearch InNOVAtion Conference / Milković, Marin ; Seljan, Sanja ; Pejić Bach, Mirjana ; Peković, Sanja ; Perovic, Djurdjica (ur.).
Zagreb: Udruga za promicanje inovacija i istraživanja u ekonomiji ''IRENET'', 2019. str. 58-66 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


Naslov
Predicting students' success using Neural Networks

Autori
Bilal Zorić, Alisa

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

Izvornik
Proceedings of the ENTRENOVA -ENTerprise REsearch InNOVAtion Conference / Milković, Marin ; Seljan, Sanja ; Pejić Bach, Mirjana ; Peković, Sanja ; Perovic, Djurdjica - Zagreb : Udruga za promicanje inovacija i istraživanja u ekonomiji ''IRENET'', 2019, 58-66

Skup
ENTerprise REsearch InNOVAtion Conference - ENTRENOVA

Mjesto i datum
Rovinj, Hrvatska, 12.-14.9.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Neural networks, educational data mining, student success

Sažetak
Fast technological changes and constant growth of knowledge in many areas have led to an increasing importance of different approach to education. Efficient education is the foundation of modern society and it has the most important role in preparing students for a very flexible labour market. Education is key for development and progress. The goal of this paper is to present a model for predicting students’ success using Neural networks. The model is based on students’ enrolment data that consisted of demographic and economic data and information about previous education. Students’ efficacy is measured by grade point average in college, and students are divided into two groups: with grade point average below and above 3.5. This model can help educators to prepare students who are classified below average with additional classes to overcome the more difficult courses and, thus, reduce the percentage of students leaving the college because of insufficient prior knowledge.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti, Interdisciplinarne društvene znanosti



POVEZANOST RADA


Ustanove
Veleučilište s pravom javnosti Baltazar Zaprešić

Autor s matičnim brojem:
Alisa Bilal Zorić, (378063)