Identifying Factors of Students’ Failure in Blended Courses by Analyzing Students’ Engagement Data
Department of Accounting and Finance, University of West Attica, 12243 Egaleo, Greece
*
Author to whom correspondence should be addressed.
Educ. Sci. 2020, 10(9), 242; https://doi.org/10.3390/educsci10090242
Received: 29 July 2020
/
Revised: 2 September 2020
/
Accepted: 8 September 2020
/
Published: 10 September 2020
Our modern era has brought about radical changes in the way courses are delivered and various teaching methods are being introduced to answer the purpose of meeting the modern learning challenges. On that account, the conventional way of teaching is giving place to a teaching method which combines conventional instructional strategies with contemporary learning trends. Thereby, a new course type has emerged, the blended course in the context of which online teaching and conventional instruction are efficiently mixed. This paper demonstrates a way to identify factors affecting students’ critical performance in blended courses through a binary logistics regression analysis on students’ engagement data. The binary logistics regression analysis has led to a risk model which identifies and prioritizes these factors in proportion to their contribution to the risk occurrence. The risk model is demonstrated in the context of two specific blended courses sharing the same learning design. Additionally, the outcome of the study has proved that factors related to the e-learning part have critically affected the students’ performance in the respective blended courses.
View Full-Text
Keywords:
risk model; risk factors; students’ achievement; engagement; blended courses
▼
Show Figures
Figure 1
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
MDPI and ACS Style
Georgakopoulos, I.; Chalikias, M.; Zakopoulos, V.; Kossieri, E. Identifying Factors of Students’ Failure in Blended Courses by Analyzing Students’ Engagement Data. Educ. Sci. 2020, 10, 242. https://doi.org/10.3390/educsci10090242
AMA Style
Georgakopoulos I, Chalikias M, Zakopoulos V, Kossieri E. Identifying Factors of Students’ Failure in Blended Courses by Analyzing Students’ Engagement Data. Education Sciences. 2020; 10(9):242. https://doi.org/10.3390/educsci10090242
Chicago/Turabian StyleGeorgakopoulos, Ioannis, Miltiadis Chalikias, Vassilis Zakopoulos, and Evangelia Kossieri. 2020. "Identifying Factors of Students’ Failure in Blended Courses by Analyzing Students’ Engagement Data" Education Sciences 10, no. 9: 242. https://doi.org/10.3390/educsci10090242
Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.
