|
Activity Number:
|
209
|
|
Type:
|
Contributed
|
|
Date/Time:
|
Monday, July 30, 2007 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Survey Research Methods
|
| Abstract - #308237 |
|
Title:
|
Response and Nonresponse Pattern Analysis in Survey Research
|
|
Author(s):
|
Chong Ho Yu*+ and Samuel DiGangi and Sandra Andrews and Angel Jannasch-Pennell
|
|
Companies:
|
Arizona State University and Arizona State University and Arizona State University and Arizona State University
|
|
Address:
|
3S89 Computing Commons, Tempe, AZ, 85287,
|
|
Keywords:
|
survey ; data mining ; classification tree
|
|
Abstract:
|
In a southwestern university, a survey regarding use of instructional technology was sent to all students via email. Respondents in survey research were self-selected and thus parametric procedures might not be properly applied. While it is important to analyze the data collected from the respondents, it is equally important to examine the profile of non-respondents in order to understand the potential bias of the survey results. To address this issue, the demographic information of the entire population was extracted from the data warehouse for response pattern analysis using sata visualization and data mining techniques. It was found that contrary to prior research, gender and race were not significant predictors to survey responses. Rather, science and engineering students tended to respond to this type of technology-related survey.
|
