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Prediktori prihvaćanja online učenja među sveučilišnim studentima: analiza temeljena na rudarenju podataka

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Author(s)
Dukić, Darko
Jukić, Dina
Keywords
online učenje, prediktori, prihvaćanje, rudarenje podataka, stabla odlučivanja, sveučilišni studenti
acceptance, data mining, decision trees, online learning, predictors, university students

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URI
http://hdl.handle.net/20.500.12424/789484
Online Access
http://hrcak.srce.hr/146234
http://hrcak.srce.hr/file/215263
Abstract
Razvoj informacijskih i komunikacijskih tehnologija snažno se odražava na cjelokupno obrazovanje. Kao rezultat toga, online učenje zauzima sve važnije mjesto i u nastavnom procesu na visokoškolskim ustanovama. Cilj je ovog rada utvrditi kakav je stav hrvatskih sveučilišnih studenata o online učenju i identificirati najvažnije prediktore njegovog prihvaćanja. Istraživanje je provedeno putem online upitnika, a analiza se temeljila na stablima odlučivanja, jednoj od najpopularnijih metoda rudarenja podataka. Prema rezultatima, većina studenata ima pozitivan stav o online učenju, a razina ICT znanja i vještina izdvaja se kao najznačajniji prediktor prihvaćanja. Za studente koji su svoja ICT znanja i vještine ocijenili s vrlo dobrim sljedeći najbolji prediktor je status, a za one sa slabijim kompetencijama to je spol.
The development of information and communication technologies has a strong impact on the entire education. As a result, online learning occupies an increasingly important place in the teaching process at higher education institutions. The aim of this study is to determine the attitudes of Croatian university students toward online learning and to identify the most important predictors of its acceptance. The survey was conducted via an online questionnaire and the analysis was based on decision trees, one of the most popular data mining methods. According to the results, most students have a positive attitude toward online learning, and the level of ICT knowledge and skills stands out as the most significant predictor of acceptance. For students who rated their ICT knowledge and skills as very good, the next best predictor is the enrolment status, whereas for those with poorer competencies, it is gender.
Date
2015-09-15
Type
text
Identifier
oai:hrcak.srce.hr:146234
http://hrcak.srce.hr/146234
http://hrcak.srce.hr/file/215263
Copyright/License
info:eu-repo/semantics/openAccess
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