The investigators seek to explore the extent to which the quantity and quality of student participation in course discussion boards (a.k.a. online asynchronous discussions (OAD)) is associated with retention in or dropping out from undergraduate computer science and industrial engineering majors. This study represents a planning and pilot study using data from discussion board enhanced STEM courses at the University of Southern California. The ultimate goal of the investigators' intended future research will be to produce knowledge usable in making more effective use of this learning technology.
The methods include computational analysis of the discussion text, a survey questionnaire, and information gathered from the registrar's office. Machine learning/natural process learning techniques will be used to process the data. The investigators will use generalized linear modeling and Multivariate Analysis of Covariance techniques in their analysis. Additionally, the investigators seek to determine differences in participation by demographic characteristics and language/technical backgrounds.
Discussion boards are now commonplace in undergraduate STEM learning environments, yet a solid base of research on their use and on user behaviors does not exist. This research is intended to begin to fill that gap. And, given many instructional reforms depend upon them, it is vital that we understand these factors better in order to improve instruction and learning.
