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Investigation of Belonging for Engineering and Science Undergraduates by Year in School

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2012 ASEE Annual Conference & Exposition


San Antonio, Texas

Publication Date

June 10, 2012

Start Date

June 10, 2012

End Date

June 13, 2012



Conference Session

Identity and Culture

Tagged Division

Educational Research and Methods

Page Count


Page Numbers

25.858.1 - 25.858.11



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Paper Authors


Tamara Floyd Smith Tuskegee University

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Tamara Floyd Smith, P.E., is Associate Professor of chemical engineering and 3M Scholar at Tuskegee University.

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Denise Wilson University of Washington

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Denise Wilson is an Associate Professor at the University of Washington in the Department of Electrical Engineering and holds degrees in mechanical and electrical engineering, as well as education (learning sciences). Her technical research focuses on sensors and sensor systems, while her research in engineering education emphasizes affective outcomes which influence academic achievement and persistence in engineering.

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Diane Carlson Jones Ph.D. University of Washington

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Melani Plett Seattle Pacific University


Rebecca A. Bates Minnesota State University, Mankato

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Rebecca A. Bates received the Ph.D. degree in electrical engineering from the University of Washington in 2004. She also received the M.T.S. degree from Harvard Divinity School in 1993. She is currently an Associate Professor in the Computer Science Department and Integrated Engineering program at Minnesota State University, Mankato. She is a 2011-12 AAAS Science & Technology Policy Fellow at the National Science Foundation.

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Nanette M Veilleux Simmons College

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Investigation of Belonging for Engineering and Science Undergraduates by Year in School The articulation and demonstration of student learning outcomes are essential elements ofundergraduate education. For STEM education, in particular, efforts to improve student learningoutcomes have concentrated on (1) faculty professional development to become better teachers,(2) increasing student exposure to the practice of science and engineering through corporateinternships and research experiences and (3) incorporation of the latest technology to assiststudents. However, it is important to realize that STEM student outcomes which, over the courseof the undergraduate degree, represent all levels of Bloom’s taxonomy are overlaid with thestudent life experience represented by Maslow’s hierarchy of needs. Thus, if a student has notsuccessfully advanced beyond belonging, the third level of Maslow’s hierarchy, it may becomethe bottleneck in the goal to improve learning outcomes. Recognizing the importance of student belonging in STEM, researchers at multipleinstitutions began a multi-year study of belonging among engineering and computer sciencestudents. The main goal of this larger study is to test the linkage between STEM students’ senseof belonging while in school and their engagement in their studies across different types ofinstitutions. For this study, belonging is separated into four types: class belonging, majorbelonging, university belonging and psychological sense of community. One potential outcomeof the larger study is a list of interventions or best practices to ensure that students have achieveda sense of belonging at their respective institutions. In this paper, the focus is on similarities anddifferences in self reported belonging for STEM undergraduates by classification (year inschool). The following hypothesis was tested: belonging will increase monotonically withstudent classification. From spring 2010 through spring 2011, a combined total of more than 900 studentscompleted surveys at a Research 1 institution located in the Northwest, a Historically BlackCollege/University (HBCU), a women’s college in the Northeast, a small private faith-basedinstitution in the Northwest, and a large teaching institution in the Midwest. The four types ofbelonging, or scales, were included in the survey assessing individual characteristics andacademic experiences. The students responded to three or four items for each scale using a Likertscale ranging from “1” (Strongly Disagree) to “5” (Strongly Agree). In the analysis for this study, responses were summed for each scale so that higher scoresindicated greater belonging. The internal reliability coefficients for each scale were strong(alphas ranged from .80 to .88). One-way Analyses of Variance (ANOVAs) for each schoolcompared mean levels of the 4 types of belonging across school classifications. Significanteffects (p<.05) to determine the significantdifferences between specific classification levels. Belonging scores across all institutions rangedfrom 14.08 to 17.45 out of 20.00 for four item scales and 9.49 to 12.68 out of 15.00 for the threeitem scale (psychological sense of community). The results of the analysis indicate that,although statistically significant differences in belonging were observed based on studentclassification at individual institutions, the differences did not support the monotonic increase byclassification hypothesized at all schools for all types of belonging. The authors attempt toexplain these observations based on cohort effects, institutional nuances and other factors.

Smith, T. F., & Wilson, D., & Jones, D. C., & Plett, M., & Bates, R. A., & Veilleux, N. M. (2012, June), Investigation of Belonging for Engineering and Science Undergraduates by Year in School Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. 10.18260/1-2--21615

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