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master's thesis
Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja
2018. urn:nbn:hr:200:710902
Rešicki, Tomislav
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Software Engineering
Chair of Visual Computing

Cite this document

Rešicki, T. (2018). Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja (Master's thesis). Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:710902

Rešicki, Tomislav. "Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2018. https://urn.nsk.hr/urn:nbn:hr:200:710902

Rešicki, Tomislav. "Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2018. https://urn.nsk.hr/urn:nbn:hr:200:710902

Rešicki, T. (2018). 'Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 28 January 2021, https://urn.nsk.hr/urn:nbn:hr:200:710902

Rešicki T. Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2018 [cited 2021 January 28] Available at: https://urn.nsk.hr/urn:nbn:hr:200:710902

T. Rešicki, "Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:200:710902

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Metadata
TitlePredviđanje uspjeha studenata na temelju njihova pisanoga izražavanja
Title (english)Predicting students success based on their writings
AuthorTomislav Rešicki
MentorIrena Galić (mentor)
MentorDragana Božić Lenard (mentor)
Committee memberIrena Galić (predsjednik povjerenstva)
Committee memberČaslav Livada (član povjerenstva)
Committee memberHrvoje Leventić (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Software Engineering)
(Chair of Visual Computing)
Osijek
Defense date and country2018-10-01, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Data Processing
Abstract
Zadatak je ovoga diplomskoga rada bio izraditi kod koji će se moći koristiti za profiliranje kandidata i predviđanje njihova uspjeha. Korpus se istraživanja sastojao od 268 eseja studenata Fakulteta elektrotehnike, računarstva i informacijskih tehnologija Osijek. Eseji su napisani na engleskome jeziku, a u njima su se studenti trebali predstaviti kroz svoje hobije i ambicije. Eseji su računalno analizirani programskim alatom LIWC-om, čiji su se rezultati uspoređivali s ocjenama studenata postignutim na kolegijima engleskoga jezika. Rezultati su se koristili za postavljanje graničnih vrijednosti koje su unošene u izrađeni kod. Na temelju podataka analiza, programerski su određivane ocjene za svakog studenta, a uspješnost takvog određivanja ocjena, na temelju jezičnoga izražavanja studenta, bila je 75,37 %. Izrađeni se kod može koristiti za predviđanje uspjeha studenata i njihovo profiliranje.
Abstract (english)
This paper aimed to develop a code which might be used to profile candidates and predict their success rates. This research corpus was based on essays submitted by 268 students studying at the Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. The essays were written in the English language and they were used as a tool for the students' introduction. The corpus was analyzed using a programming tool LIWC whose raw data were compared to the participants' grades acquired at the courses of the English language. The results were used to set margin values input in the developed code. Based on the research data, each student was predicted a course grade which was compared to an actual grade a student acquired. The success rate of such prediction was 75.37%. The developed code can be used for one’s profiling and success prediction.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:710902
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2018-10-17 07:13:04