Scaling up: Taking the Academic Pathways of People Learning Engineering Survey (APPLES) National. Research Brief

The Academic Pathways of People Learning Engineering Survey (APPLES) was deployed for a second time in spring 2008 to undergraduate engineering students at 21 US universities. The goal of the second deployment of APPLES was to corroborate and extend findings from the Academic Pathways Study (APS; 20...

Full description

Saved in:
Bibliographic Details
Published inCenter for the Advancement of Engineering Education
Main Authors Donaldson, Krista M, Chen, Helen L, Toye, George, Clark, Mia, Sheppard, Sheri D
Format Report
LanguageEnglish
Published Center for the Advancement of Engineering Education 01.12.2008
Subjects
Academic Persistence
Correlation
Educational Research
Engineering Education
Evaluation Methods
Performance Factors
Student Surveys
Undergraduate Students
United States
United States
Online AccessGet full text

Cover

More Information
Summary:The Academic Pathways of People Learning Engineering Survey (APPLES) was deployed for a second time in spring 2008 to undergraduate engineering students at 21 US universities. The goal of the second deployment of APPLES was to corroborate and extend findings from the Academic Pathways Study (APS; 2003-2007) and the first deployment of APPLES (spring 2007) on factors that correlate with persistence in engineering on a national scale. The APPLES2 set of deployments, which surveyed over 4,200 students, was among the largest and broadest cross-sectional surveys focusing on undergraduate education ever undertaken. The total response for the survey was 4,266 subjects from the 21 institutions after data cleaning. The average survey response rate relative to the undergraduate engineering populations at the participating institutions was 14 percent. Eighty-five percent of the APPLES participants claimed the $4 incentive, although only 76 percent of the incentive claimants followed through to collect the incentive. Eight out of the 21 institutions met all their strata targets. The most commonly missed targets were non-persisters and ethnic minority students. There were two cases of attempted large-scale fraud. Fraud was defined as a large number of ineligible submissions during one institution's survey deployment. Using a combination of IP tracking and timing data, the team was able to identify these submissions for removal from the data set.