Pregled bibliografske jedinice broj: 766757
Discovering patterns of student behaviour in e- learning environment
Discovering patterns of student behaviour in e- learning environment // Higher Goals in Mathematics Education / Kolar-Begović, Zdenka ; Kolar-Šuper, Ružica ; Đurđević Babić, Ivana (ur.).
Zagreb: Element ; Fakultet za odgojne i obrazovne znanosti Sveučilišta Josipa Jurja Strossmayera u Osijeku ; Odjel za matematiku Sveučilišta Josipa Jurja Strossmayera u Osijeku, 2015. str. 94-111
CROSBI ID: 766757 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Discovering patterns of student behaviour in e- learning environment
Autori
Zekić Sušac, Marijana ; Đurđević Babić, Ivana
Vrsta, podvrsta i kategorija rada
Poglavlja u knjigama, znanstveni
Knjiga
Higher Goals in Mathematics Education
Urednik/ci
Kolar-Begović, Zdenka ; Kolar-Šuper, Ružica ; Đurđević Babić, Ivana
Izdavač
Element ; Fakultet za odgojne i obrazovne znanosti Sveučilišta Josipa Jurja Strossmayera u Osijeku ; Odjel za matematiku Sveučilišta Josipa Jurja Strossmayera u Osijeku
Grad
Zagreb
Godina
2015
Raspon stranica
94-111
ISBN
978-953-197-586-5
Ključne riječi
student behaviour, e-learning, data mining, classification trees, support vector machines
Sažetak
The benefits of e-learning have been widely recognized in today’s education. However, behaviour of students attending a course through an e-learning platform and its connection to students’ satisfaction with a course is still not investigated enough. This paper analyses a course log data in e-learning environment in addition to some students’ descriptive variables at University of Osijek, and aims to discover patterns in students’ behaviour that could enable to create profiles of satisfied and unsatisfied students. The final purpose is to reveal knowledge about student behaviour that will assist academic teachers in increasing the level of their students’ satisfaction. The methodology used in the research includes several data mining methods, such as statistical tests of dependence, and support vector machines. The results show that satisfied students put more effort in frequent viewing of all course materials, they are more active in uploading assignments, and have more previously earned ECTS points than unsatisfied students. The extracted characteristics could be used to improve student satisfaction with the course by stimulating those activities. In order to generalize results, the research is to be extended to include more e-courses on different levels of academic education.
Izvorni jezik
Engleski
Znanstvena područja
Informacijske i komunikacijske znanosti
Napomena
Indeksirano u bazi podataka ERIC.
POVEZANOST RADA
Ustanove:
Ekonomski fakultet, Osijek,
Fakultet za odgojne i obrazovne znanosti, Osijek
