Exploring the Engineering Student Experience: Findings from the Academic Pathways of People Learning Engineering Survey (APPLES). TR-10-01

• Published in: Center for the Advancement of Engineering Education
• Main Authors: Sheppard, Sheri, Gilmartin, Shannon, Chen, Helen L, Donaldson, Krista, Lichtenstein, Gary, Eris, Ozgur, Lande, Micah, Toye, George
• Format: Report
• Language: English
• Published: Center for the Advancement of Engineering Education 01.09.2010
• Subjects: Aspiration; College Freshmen; College Seniors; Disproportionate Representation; Education Work Relationship; Engineering Education; Family Characteristics; Gender Differences; Knowledge Level; Longitudinal Studies; Majors (Students); Minority Group Students; Participant Characteristics; Self Esteem; Socioeconomic Status; Student Characteristics; Student Experience; Student Motivation; Student Surveys; Undergraduate Students

This report is based on data from the Academic Pathways of People Learning Engineering Survey (APPLES), administered to engineering students at 21 U.S. engineering colleges and schools in the spring of 2008. The first comprehensive set of analyses completed on the APPLES dataset presented here looks at how engineering students experience their education, how they gain knowledge of what engineering is, and what their post-graduation plans are. The APPLES instrument is one of the research tools developed and used by the National Science Foundation-funded Academic Pathways Study (APS)1. The APPLES study represented the major cross-sectional survey component of the APS. Other components included a four-year longitudinal study of 160 engineering students at four institutions, and interviews of over 90 practicing engineers in a range of professional settings. Taken together, these components were designed to expand our understanding of the undergraduate engineering experience and the transition from school to the workplace. The APS research questions focus on four primary areas that investigate what engineering graduates need to succeed in an increasingly complex world: (1) Skills and Knowledge: How do students' engineering skills and knowledge develop and/or change over time?; (2) Identity: How do students come to identify themselves as engineers? How does student appreciation, confidence, and commitment to engineering change as they navigate their education? How does this in turn impact how these students make decisions about further participation in engineering after graduation?; (3) Education: What elements of students' engineering educations contribute to changes observed in the questions related to skills, knowledge, and identity? What do students find difficult and how do they deal with the difficulties they face?; and (4) Workplace: How do students and early career engineers conceive of their engineering future? What skills do early career engineers need as they enter the workplace? Where did they obtain these skills? Are there any missing skills? This report presents the first set of analyses conducted on the APPLES dataset. The first section of the report (Chapters 1-3) is an overview of the APPLES instrument along with demographics of the overall cross-sectional population surveyed. In Chapter 1, the APPLES instrument is described, including definitions of the variables which form the basis of the rest of the report. Chapter 2 specifies the selection of the 21 schools where APPLES was deployed and the demographics of the 4,266 students who completed the survey. Then in Chapter 3, the organization of the remainder of the report and its focus on the comparisons between first-year and senior engineering majors are outlined. Appended are: (1) The Academic Pathways of People Learning Engineering Survey (APPLES) Instrument; (2) Descriptions of the Major Declaration Process and Institutional Selectivity Characteristics; (3) Definitions of APPLES Engineering Majors and Other Majors; (4) Means and Standard Deviations of Core Constructs; (5) Simple Correlation Coefficients: First-Year Students; (6) Calculating APPLES Multi-Item Variables; and (7) Methodological Notes for Regressions. Individual chapters contain footnotes. (Contains 11 figures and 99 tables.)