Transcript Examining the Tracks that Cause Derailment: Institutional
Bryce E. Hughes, Juan C. Garibay, Sylvia Hurtado, & Kevin Eagan UCLA American Educational Research Association San Francisco, CA May 1, 2013 1
National Academy of Engineering (2011) report
Lifelong Learning Imperative in Engineering
Wave of retirements “U.S. has one of the lowest rates of graduation of bachelor level engineers in the world: only 4.5% of our university graduates are engineers” (p. ix).
Tremendous infrastructural and environmental challenges Despite its national import, much is still unknown about the factors that influence engineering completion 2
Student characteristics and precollege experiences Self-efficacy Academic preparation Knowledge of and exposure to engineering (from parents and others) Aspirations and commitment to an engineering career Classroom experiences Teacher-centered practices: Lectures, grading on a curve, individual-based work Student-centered pedagogy: Active learning strategies, collaborative work, design- and problem-based learning 3
Practices and Programs in Engineering (ASEE, 2012) : Internships and cooperative experiences Research opportunities Retention programs for URMs Financial assistance Institutional Contexts (For STEM students) Size, selectivity, private, and Minority-Serving Institutions Peer normative context Previous research models on engineering student success have yet to account for these contexts 4
To identify institutional contexts that contribute to engineering degree completion within five years of college entry.
Identify contexts that “derail” engineering aspirants from the engineering track and improve the use of “evidence-based” approaches 5
• • • • Longitudinal Data on Engineering Aspirants Data Sources: • • • 2004 Freshman Survey Completion data from National Student Clearinghouse 2007 & 2010 HERI Faculty Survey • • STEM Best Practices Survey – administered to STEM deans and department chairs at our participating campuses IPEDS Sample: 15,913 first-time, full-time engineering aspirants across 270 institutions Analysis: Multinomial HGLM (HLM software) 6
Dependent Variable (measured five years after college entry): Engineering completion compared to: Bachelor’s completion in non-engineering field No bachelor’s degree completion-includes students still enrolled (major not known) 7
Independent variables Background characteristics Pre-college preparation and experiences Aspirations and expectations Intended major Aggregate peer effects Institutional characteristics Faculty contextual measures Best practices in STEM 8
Dependent Variable
Completed engineering degree in five years Completed degree in other field Did not complete
Demographics
Sex: Female American Indian Asian/Pacific Islander Black Latino/a Other race White 35.2% 24.6% 40.1% 16.88% 1.63% 13.93% 8.91% 7.13% 1.52% 66.88% 9
Institutional context
Control: Private Undergraduate FTE % STEM faculty engaging undergrads in research Avg. STEM faculty score on student-centered pedagogy
Student-level variables
Parent employed as engineer Sex: Female Aeronautical/astronautical engineering (ref: mechanical) Chemical engineering Computer engineering Electrical/electronics engineering Industrial engineering Other engineering
+ + + +
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Institutional Context
Control: Private Undergraduate FTE % STEM faculty engaging undergrads in research Selectivity Avg. STEM faculty score on student-centered pedagogy
Student-level variables
Sex: Female Parent employed as engineer American Indian, Latino/a (ref: White) Doctoral degree aspiration Civil engineering Aeronautical/astronautical engineering (ref: mechanical) Computer engineering + + + + + + + 11
Hispanic-Serving Institution Black students (ref: White) Black students at HBCUs Civil engineering (ref: mechanical) Other engineering
Non-engineering
+
No completion
+ + n.s.
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Institutional context matters Driven by mission, affects college’s level of resources Minority-serving institutions continue to meet a crucial need Faculty efforts can aggregate into cultural influences on student outcomes Disaggregating by engineering field informs how differences in culture and coursework affect student outcomes Students may also “go pro” early in some fields 13
Individual colleges are uniquely positioned to graduate engineers Understanding this position better informs practice and policy Future research should address the influence of context for community college and transfer students Parsing out micro-, meso-, and macrolevel institutional influences provides a more complete picture of an institution’s degree productivity Degree completion is influenced by institutional mission as well as department-level differences 14
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Faculty/Co-PIs: Sylvia Hurtado Mitchell Chang Kevin Eagan Postdoctoral Scholars: Josephine Gasiewski Graduate Research Assistants: Tanya Figueroa Gina Garcia Juan Garibay Bryce Hughes Administrative Staff: Dominique Harrison Papers and reports are available for download from project website: http://heri.ucla.edu/nih Project e-mail: [email protected]
This study was made possible by the support of the National Institute of General Medical Sciences, NIH Grant Numbers 1 R01 GMO71968-01 and R01 GMO71968-05, the National Science Foundation, NSF Grant Number 0757076, and the American Recovery and Reinvestment Act of 2009 through the National Institute of General Medical Sciences, NIH Grant 1RC1GM090776-01. This independent research and the views expressed here do not indicate endorsement by the sponsors. 16