T39 KSET- Analyzing weekly traces of online behavioral data: Exploratory Study to find critical time for prediction

• In Event: Roundtable Session 2
  In Roundtable Session: KSET - Roundtable 2

Short Description

This study analyzed 194 college students’ online behaviors in weekly-base to find the critical time to predict their learning achievements. The data-exploration tracked from LMS contributed to developing an elaborated prediction model, with which instructors are able to provide timely and more proper interventions to students. Multiple regression analysis conducted repeatedly to compare the predictability among the fifteen weekly models present a possibility for developing an adaptive prediction system in the context of online learning.

Authors

• Jeong Hyun Kim, Ewha Womans University

• Hyeyun Lee, Ewha W. University

• Min Sun Kim, Ewha Womans University

• Yeonjeong Park, Ewha Womans University

• Il-Hyun Jo, Ewha Womans University