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ERIC Number: ED550433
Record Type: Non-Journal
Publication Date: 2012
Pages: 267
Abstractor: As Provided
Reference Count: N/A
ISBN: 978-1-2678-2401-1
ISSN: N/A
Educating the Engineers of 2020: An Outcomes-Based Typology of Engineering Undergraduates
Knight, David B.
ProQuest LLC, Ph.D. Dissertation, The Pennsylvania State University
Members of government and industry have called for greater emphasis within U.S. colleges and universities on producing engineers who can enter and advance a more competitive, globally connected workforce. Looking toward this future, engineers will need to exhibit strong analytical skills as in the past, but they also will need to be proficient in a cadre of new abilities to compete. This study examines, in combination, an array of knowledge and skills aligned with the National Academy of Engineering's "engineer of 2020." The study has two major goals. The first is to develop a typology of engineering students based on the learning outcomes associated with the engineer of E2020. The second is to understand the educational experiences that distinguish these groups of students who resemble, more or less, the engineer of 2020. This approach acknowledges that engineering graduates need a complex skill set to succeed in the new global economy; it is the combination of skills associated with the engineer of 2020, not the individual skills in isolation, which will ensure graduates can respond to workforce needs of the future. To date, research on student outcomes has studied learning outcomes independent of one another rather than investigating student learning holistically. The study uses student data from the "Prototype to production: Processes and conditions for preparing the Engineer of 2020" study, sponsored by the National Science Foundation (NSF EEC-0550608). Engineering students from a nationally representative sample of engineering programs in the United States answered a survey that collected information on their pre-college academic preparation and sociodemographic characteristics, their curricular and co-curricular experiences in their engineering programs, and their self-ratings of their engineering-related competencies. Only data on engineering students in their senior year (n = 2,422) were utilized in analyses. Analyses were conducted in multiple phases for each of five engineering disciplines in the data set (biomedical/bioengineering, chemical, civil, electrical, and mechanical engineering). First, cluster analyses produced typologies (or groupings) of engineering seniors (one for each of five engineering disciplines studied and an "all engineering" analysis) based on nine self-reported learning outcomes, including fundamental skills, design skills, contextual awareness, interdisciplinary competence, and professional skills. Second, profiles of pre-college characteristics as well as student experiences in college were developed for each discipline and the five disciplines combined. Using analyses of variance, Chi-square analyses, and multinomial logistic regression, this phase also identified differences in student characteristics and college experiences between clusters of students reporting high proficiencies on the array of outcomes and students in other clusters. This second phase informed the third phase, which produced parsimonious models that used pre-college characteristics and student experience variables to predict cluster membership. As a whole, the findings demonstrate that analyses that include the full array of E2020 learning outcomes produce meaningful typologies that distinguish between groupings of students in different engineering fields. Findings demonstrate that a subset of students--the engineers of 2020--report high skills and abilities on the full array of learning outcomes. These are the graduates sought by both the federal government and industry who most closely resemble the engineers of 2020. In addition, distinctive curricular and co-curricular experiences distinguish this E2020 group of students in each engineering discipline from other groupings of students in that same discipline. These findings have valuable implications for practice because they identify an array of discipline-specific, in- and out-of-class learning experiences that appear to promote the development of this multi-dimensional set of outcomes. Overall, however, greater curricular emphases on broad and systems perspectives in the engineering curriculum most consistently set apart the students who report high proficiencies on the E2020 outcomes. The findings also indicate that strategies for improving undergraduate engineering outcomes should be tailored by engineering discipline. The study contributes to both practice and research by developing a technique that can be used to create an outcomes-based typology that can be applied to any set of learning outcomes. Graphical representations of results consolidate large quantities of information into an easily accessible format so that findings can guide both practitioners and policymakers who seek to improve this multi-dimensional set of undergraduate engineering learning outcomes. Future directions for research, including operationalizing organizational contexts influencing E2020 learning outcomes as well as anticipated career trajectories of students across the typology, are also discussed. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A