2010 Conference Archive
“Dr. _____, Should I Take This Course Online?”
Copyright
This work is archived and distributed under the repository's Standard Copyright and Reuse License (opens in new tab). End users may copy, store, and distribute this work without restriction. For all other uses, permission must be obtained from the copyright owners or their authorized agents.
Abstract
By the time many college students take their first online course, they have taken as many as 150 regular classroom courses. Whereas students know what to expect in a traditional classroom course and they can, usually after the first day of class, forecast how they will perform in the course, evaluating an online course is much more difficult. We often see students fail our online course in one semester and then earn an A or B the next semester in the traditional classroom section. Thus students should, and often do, ask the question: “should I take your online section of this course?” The purpose of this session is to introduce and discuss an empirical based prediction “advisement” model that we have developed and tested. Our model, which goes beyond conventional measures of student competence and demographics, allows students to predict their grade in an online course before they even register.
Location
Room 1908
Publication Type and Release Option
Event
Recommended Citation
Fendler, Richard; Shrikhande, Milind; and Ruff, Craig, "“Dr. _____, Should I Take This Course Online?” " (2010). SoTL Commons Conference. 42.
https://digitalcommons.georgiasouthern.edu/sotlcommons/SoTL/2010/42
“Dr. _____, Should I Take This Course Online?”
Room 1908
By the time many college students take their first online course, they have taken as many as 150 regular classroom courses. Whereas students know what to expect in a traditional classroom course and they can, usually after the first day of class, forecast how they will perform in the course, evaluating an online course is much more difficult. We often see students fail our online course in one semester and then earn an A or B the next semester in the traditional classroom section. Thus students should, and often do, ask the question: “should I take your online section of this course?” The purpose of this session is to introduce and discuss an empirical based prediction “advisement” model that we have developed and tested. Our model, which goes beyond conventional measures of student competence and demographics, allows students to predict their grade in an online course before they even register.
