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Pregled bibliografske jedinice broj: 925126

Machine learning methods in predicting the student academic motivation


Đurđević Babić, Ivana
Machine learning methods in predicting the student academic motivation // Croatian operational research review, 8 (2017), 2; 443-461 doi:10.17535/crorr.2017.0028 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 925126 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Machine learning methods in predicting the student academic motivation

Autori
Đurđević Babić, Ivana

Izvornik
Croatian operational research review (1848-0225) 8 (2017), 2; 443-461

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
academic motivation, machine learning, neural networks, decision tree, support vector machine

Sažetak
Academic motivation is closely related to academic performance. For educators, it is equally important to detect early students with a lack of academic motivation as it is to detect those with a high level of academic motivation. In endeavouring to develop a classification model for predicting student academic motivation based on their behaviour in learning management system (LMS) courses, this paper intends to establish links between the predicted student academic motivation and their behaviour in the LMS course. Students from all years at the Faculty of Education in Osijek participated in this research. Three machine learning classifiers (neural networks, decision trees, and support vector machines) were used. To establish whether a significant difference in the performance of models exists, a t-test of the difference in proportions was used. Although, all classifiers were successful, the neural network model was shown to be the most successful in detecting the student academic motivation based on their behaviour in LMS course.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti



POVEZANOST RADA


Ustanove:
Fakultet za odgojne i obrazovne znanosti, Osijek

Profili:

Avatar Url Ivana Đurđević Babić (autor)

Citiraj ovu publikaciju

Đurđević Babić, Ivana
Machine learning methods in predicting the student academic motivation // Croatian operational research review, 8 (2017), 2; 443-461 doi:10.17535/crorr.2017.0028 (međunarodna recenzija, članak, znanstveni)
Đurđević Babić, I. (2017) Machine learning methods in predicting the student academic motivation. Croatian operational research review, 8 (2), 443-461 doi:10.17535/crorr.2017.0028.
@article{article, author = {\DJur\djevi\'{c} Babi\'{c}, I.}, year = {2017}, pages = {443-461}, DOI = {10.17535/crorr.2017.0028}, keywords = {academic motivation, machine learning, neural networks, decision tree, support vector machine}, journal = {Croatian operational research review}, doi = {10.17535/crorr.2017.0028}, volume = {8}, number = {2}, issn = {1848-0225}, title = {Machine learning methods in predicting the student academic motivation}, keyword = {academic motivation, machine learning, neural networks, decision tree, support vector machine} }
@article{article, author = {\DJur\djevi\'{c} Babi\'{c}, I.}, year = {2017}, pages = {443-461}, DOI = {10.17535/crorr.2017.0028}, keywords = {academic motivation, machine learning, neural networks, decision tree, support vector machine}, journal = {Croatian operational research review}, doi = {10.17535/crorr.2017.0028}, volume = {8}, number = {2}, issn = {1848-0225}, title = {Machine learning methods in predicting the student academic motivation}, keyword = {academic motivation, machine learning, neural networks, decision tree, support vector machine} }

Časopis indeksira:


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


Uključenost u ostale bibliografske baze podataka:


  • MathSciNet
  • Zentrallblatt für Mathematik/Mathematical Abstracts
  • CompactMath
  • Current Index to Statistics
  • Current Mathematical Publications
  • DOAJ
  • EBSCO host
  • Genamics Journal Seek database
  • HRČAK
  • ProQuest


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