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Pregled bibliografske jedinice broj: 779752

Predictors of Online Learning Acceptance among University Students: An Analysis Based on Data Mining


Dukić, Darko; Jukić, Dina
Predictors of Online Learning Acceptance among University Students: An Analysis Based on Data Mining // Tehnički glasnik - Technical Journal, 9 (2015), 3; 279-284 (podatak o recenziji nije dostupan, prethodno priopcenje, znanstveni)


Naslov
Predictors of Online Learning Acceptance among University Students: An Analysis Based on Data Mining

Autori
Dukić, Darko ; Jukić, Dina

Izvornik
Tehnički glasnik - Technical Journal (1846-6168) 9 (2015), 3; 279-284

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, prethodno priopcenje, znanstveni

Ključne riječi
Acceptance ; data mining ; decision trees ; online learning ; predictors ; university students

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek,
Sveučilište u Osijeku - Odjel za fiziku

Autor s matičnim brojem:
Dina Jukić, (357135)
Darko Dukić, (260093)

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)


Uključenost u ostale bibliografske baze podataka:


  • Academic Search Complete
  • CiteFactor
  • Hrčak