Original scientific paper

https://doi.org/10.17559/TV-20191019165025

Predicting Students' Outcomes in Blended Learning: An Empirical Investigation in the Higher Education Context

Damijana Keržič* orcid.org/0000-0003-4505-7134 ; University of Ljubljana, Faculty of Public Administration, Gosarjeva ulica 5, SI-1000 Ljubljana
Nina Tomaževič ; University of Ljubljana, Faculty of Public Administration, Gosarjeva ulica 5, SI-1000 Ljubljana
Aleksander Aristovnik orcid.org/0000-0003-1345-9649 ; University of Ljubljana, Faculty of Public Administration, Gosarjeva ulica 5, SI-1000 Ljubljana
Lan Umek orcid.org/0000-0003-2730-2597 ; University of Ljubljana, Faculty of Public Administration, Gosarjeva ulica 5, SI-1000 Ljubljana

Abstract

The main goal of this research was to clarify which aspects of blended learning increase a student's knowledge level measured by the course final grade. The questionnaire-based survey was used for gathering students' attitudes towards some aspects of blended learning. A principal component analysis and hierarchical clustering of variables were applied to extract the components that describe dimensions of blended learning and represent the explanatory variables in a multiple regression model with student's final grade as a dependent variable. Using a Two-Step cluster analysis to reveal natural groupings based on the answers in the questionnaire, two clusters were formed having a statistically significant difference between the means of final grades. The research revealed that the organization of a course and the study material supporting face-to-face teaching are essential features with an impact on student's final success. The study also showed that the aspects of traditional face-to-face teaching are more strongly linked to higher grades than the aspects of e-courses.

Keywords

blended learning; education data mining; higher education; performance; satisfaction

Hrčak ID:

251515

URI

https://hrcak.srce.hr/251515

Publication date:

5.2.2021.

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