Search
Program Calendar
Browse By Day
Browse By Time
Browse By Person
Browse By Room
Browse By Group
Browse By Session Type
Browse By Research Area
Search Tips
AECT 2014 Convention Page
Personal Schedule
Sign In
X (Twitter)
A variety of studies to predict students’ performance have been conducted since the educational data tracked from LMS are increasingly utilized to analyze their learning behaviors. However, such a prediction is still challenging in blended learning environments due to the large proportion of residuals occurred by off-line behaviors that are not explained by student’s online activity. In this study, we analyzed two different blended classes (discussion-based vs. lecture-based) by using a mix of regression and random forest approach.
Jeong Hyun Kim, Ewha Womans University
Yeonjeong Park, Ewha Womans University
Jongwoo Song, Ewha Womans University
Il-Hyun Jo, Ewha Womans University