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Title: Student perceptions of and learning in makerspaces embedded in their undergraduate engineering preparation programs.
Building upon our two years of research on the use of makerspaces in undergraduate engineering programs, we engaged in a large-scale data collection from students enrolled in undergraduate engineering preparation programs with affiliated makerspaces established for a minimum of three years. Using web searches, and other sources of information (e.g. references from other researchers or faculty members), we have identified 28 institutions that met our criteria. Working with a third party, we gathered over 574 responses from undergraduate engineering students with makerspace experiences spread across the 28 institutions. To gather our data, we created and validated an online survey with a combination of quantitative and qualitative items. We constructed a survey with subscales aligned with motivation to learn, growth mindset, learning goal orientation, knowledge of engineering as a profession, and belongingness and inclusion, as associated with work within makerspaces. We found significant positive correlations among the variables, positive levels of motivation, growth mindset, knowledge of engineering as a profession, and belongingness. We found differences in levels for gender, engineering majors, and student class standing. We discuss the implications for our findings in the context of undergraduate engineering student learning in makerspaces.  more » « less
Award ID(s):
1664271
NSF-PAR ID:
10197129
Author(s) / Creator(s):
; ; ; ; ; ;
Date Published:
Journal Name:
Zone 1 Conference of the American Society for Engineering Education
Volume:
30699
ISSN:
2332-368X
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  4. Abstract Background

    Noncognitive and affective (NCA) factors (e.g., belonging, engineering identity, motivation, mindset, personality, etc.) are important to undergraduate student success. However, few studies have considered how these factors coexist and act in concert.

    Purpose/Hypothesis

    We hypothesize that students cluster into several distinct collections of NCA factors and that identifying and considering the factors together may inform student support programs and engineering education.

    Design/Method

    We measured 28 NCA factors using a survey instrument with strong validity evidence. We gathered responses from 2339 engineering undergraduates at 17 U.S. institutions and used Gaussian mixture modeling (GMM) to group respondents into clusters.

    Results

    We found four distinct profiles of students in our data and a set of unclustered students with the NCA factor patterns varying substantially by cluster. Correlations of cluster membership to self‐reported incoming academic performance measures were not strong, suggesting that students' NCA factors rather than traditionally used cognitive measures may better distinguish among students in engineering programs.

    Conclusions

    GMM is a powerful technique for person‐centered clustering of high‐dimensional datasets. The four distinct clusters of students discovered in this research illustrate the diversity of engineering students' NCA profiles. The NCA factor patterns within the clusters provide new insights on how these factors may function together and provide opportunities to intervene on multiple factors simultaneously, potentially resulting in more comprehensive and effective interventions. This research leads to future work on both student success modeling and student affairs–academic partnerships to understand and promote holistic student success.

     
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