Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja

Rešicki, Tomislav

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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

APA 6th Edition

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

MLA 8th Edition

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

Chicago 17th Edition

Harvard

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 24 October 2020, https://urn.nsk.hr/urn:nbn:hr:200:710902

Vancouver

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 2020 October 24] Available at: https://urn.nsk.hr/urn:nbn:hr:200:710902

IEEE

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

Cite this item: https://urn.nsk.hr/urn:nbn:hr:200:710902

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Metadata

Title	Predviđanje uspjeha studenata na temelju njihova pisanoga izražavanja
Title (english)	Predicting students success based on their writings
Author	Tomislav Rešicki
Mentor	Irena Galić (mentor)
Mentor	Dragana Božić Lenard (mentor)
Committee member	Irena Galić (predsjednik povjerenstva)
Committee member	Časlav Livada (član povjerenstva)
Committee member	Hrvoje Leventić (član povjerenstva)
Granter	Josip 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 country	2018-10-01, 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)
Language	croatian
URN:NBN	urn:nbn:hr:200:710902
Study programme	Title: 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 resource	Text
File origin	Born digital
Access conditions	Open access
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Created on	2018-10-17 07:13:04