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- All Subjects: Online Education
- Creators: Bekki, Jennifer
Description
Customized online education is a means of educating a large amount of users in a way that will change their behavior at a low incremental cost to the one providing the information. This thesis will examine several aspects of online education, but primarily focus on the presentation of the materials. It will examine how this is done through a consulting project I worked on in conjunction with the New Venture Group for Parenting Arizona. Parenting Arizona is a non-profit organization based in Arizona that offers classes for parents who are seeking better ways to manage their family responsibilities. The purpose of the consulting project was to take the instructional materials used in in-person group classes and modify it to be effectively used for instruction in an online environment. Parenting Arizona foresaw a number of benefits from this modification and migration of instructional materials for the web; first among these was the ability of people in remote areas or in situations that did not allow them to attend an on-ground class to gain access to instructional material. In addition, the broader availability of the material that would come from its presence on the web would expand the influence of good parenting instructions to a greater audience both inside and outside the State of Arizona, aiding even more families.
ContributorsAnderson, Kyle (Author) / Brooks, Dan (Thesis director) / Forss, Brennan (Committee member) / Rosen, Julie (Committee member) / Barrett, The Honors College (Contributor)
Created2012-05
Description
This study investigated the ability to relate a test taker’s non-verbal cues during online assessments to probable cheating incidents. Specifically, this study focused on the role of time delay, head pose and affective state for detection of cheating incidences in a lab-based online testing session. The analysis of a test taker’s non-verbal cues indicated that time delay, the variation of a student’s head pose relative to the computer screen and confusion had significantly statistical relation to cheating behaviors. Additionally, time delay, head pose relative to the computer screen, confusion, and the interaction term of confusion and time delay were predictors in a support vector machine of cheating prediction with an average accuracy of 70.7%. The current algorithm could automatically flag suspicious student behavior for proctors in large scale online courses during remotely administered exams.
ContributorsChuang, Chia-Yuan (Author) / Femiani, John C. (Thesis advisor) / Craig, Scotty D. (Thesis advisor) / Bekki, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015