IDEAS home Printed from https://ideas.repec.org/a/spr/reihed/v65y2024i5d10.1007_s11162-023-09772-5.html
   My bibliography  Save this article

Role Models in Action Through YouTube Videos for Engineering Community College Students

Author

Listed:
  • Hye Rin Lee

    (University of Delaware
    University of California,)

  • Teomara Rutherford

    (University of Delaware)

  • Paul Hanselman

    (University of California,)

  • Fernando Rodriguez

    (University of California,)

  • Kevin F. Ramirez

    (University of California,)

  • Jacquelynne S. Eccles

    (University of California,)

Abstract

Community colleges provide broad access to a college degree due to their less expensive tuition, greater course time offerings, and more open admission policies compared to four-year universities as reported (Juszkiewicz, 2015). These institutions have great potential to diversify who chooses STEM, such as engineering. Such diverse representation is important, because students from different backgrounds can contribute new perspectives that foster creative and innovative approaches to solving problems. However, approximately 40% of the students who enter community college in the U.S. leave before graduation (Xu & Jaggars, 2011). Harnessing the power of social media to reduce attrition, we tested a pilot intervention in which community college students in engineering courses completed a reflection exercise after watching YouTube videos of former engineering students from similar backgrounds who successfully transferred to a four-year college. Quasi-experimental analyses (N = 537) show that students in the intervention received higher engineering course grades and had greater odds of enrolling in an engineering course in the subsequent term compared to those who were not in the intervention. Additionally, we find support for the hypothesis that the intervention has larger benefits for women. Results suggest that hearing from other students about their engineering experience can be a useful tool for improving community college students’ choices and performance.

Suggested Citation

  • Hye Rin Lee & Teomara Rutherford & Paul Hanselman & Fernando Rodriguez & Kevin F. Ramirez & Jacquelynne S. Eccles, 2024. "Role Models in Action Through YouTube Videos for Engineering Community College Students," Research in Higher Education, Springer;Association for Institutional Research, vol. 65(5), pages 1007-1039, August.
    • Handle: RePEc:spr:reihed:v:65:y:2024:i:5:d:10.1007_s11162-023-09772-5
    DOI: 10.1007/s11162-023-09772-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11162-023-09772-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11162-023-09772-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. David S. Yeager & Paul Hanselman & Gregory M. Walton & Jared S. Murray & Robert Crosnoe & Chandra Muller & Elizabeth Tipton & Barbara Schneider & Chris S. Hulleman & Cintia P. Hinojosa & David Paunesk, 2019. "A national experiment reveals where a growth mindset improves achievement," Nature, Nature, vol. 573(7774), pages 364-369, September.
    2. Mehmet Kara & Kemal Baytemir & Fatma Inceman-Kara, 2021. "Duration of daily smartphone usage as an antecedent of nomophobia: exploring multiple mediation of loneliness and anxiety," Behaviour and Information Technology, Taylor & Francis Journals, vol. 40(1), pages 85-98, January.
    3. van Buuren, Stef & Groothuis-Oudshoorn, Karin, 2011. "mice: Multivariate Imputation by Chained Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 45(i03).
    4. Kenny, Lawrence W, et al, 1979. "Returns to College Education: An Investigation of Self-Selection Bias Based on the Project Talent Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 20(3), pages 775-789, October.
    5. Bailey, Thomas & Jeong, Dong Wook & Cho, Sung-Woo, 2010. "Referral, enrollment, and completion in developmental education sequences in community colleges," Economics of Education Review, Elsevier, vol. 29(2), pages 255-270, April.
    6. Catherine Porter & Danila Serra, 2020. "Gender Differences in the Choice of Major: The Importance of Female Role Models," American Economic Journal: Applied Economics, American Economic Association, vol. 12(3), pages 226-254, July.
    7. Thomas G. Greene & C. Nathan Marti & Kay McClenney, 2008. "The Effort—Outcome Gap: Differences for African American and Hispanic Community College Students in Student Engagement and Academic Achievement," The Journal of Higher Education, Taylor & Francis Journals, vol. 79(5), pages 513-539, September.
    8. Ho, Daniel E. & Imai, Kosuke & King, Gary & Stuart, Elizabeth A., 2007. "Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference," Political Analysis, Cambridge University Press, vol. 15(3), pages 199-236, July.
    9. Hagy, Alison P. & Staniec, J. Farley Ordovensky, 2002. "Immigrant status, race, and institutional choice in higher education," Economics of Education Review, Elsevier, vol. 21(4), pages 381-392, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kerstin Grosch & Simone Haeckl & Martin G. Kocher, 2022. "Closing the Gender STEM Gap - A Large-Scale Randomized-Controlled Trial in Elementary Schools," CESifo Working Paper Series 9907, CESifo.
    2. Grosch, Kerstin & Häckl, Simone & Kocher, Martin G., 2022. "Closing the gender STEM gap: A large-scale randomized-controlled trial in elementary schools," Department of Economics Working Paper Series 329, WU Vienna University of Economics and Business.
    3. Heyna, Philipp, 2024. "Can TikTok Drive Support for Populist Radical Right Parties? Causal Evidence From Germany," OSF Preprints yju9n, Center for Open Science.
    4. Silvan Has & Jake Anders & Nikki Shure, 2020. "Monetary and time investments in children's education: how do they differ in workless households?," CEPEO Working Paper Series 20-10, UCL Centre for Education Policy and Equalising Opportunities, revised Apr 2020.
    5. Heyna, Philipp, 2024. "Can TikTok Drive Support for the Far-Right? Causal Evidence From Germany," OSF Preprints yju9n_v2, Center for Open Science.
    6. Heyna, Philipp, 2024. "Can TikTok Drive Support for the Far-Right? Causal Evidence From Germany," OSF Preprints yju9n_v1, Center for Open Science.
    7. Bo Zhang & Eric J. Tchetgen Tchetgen, 2022. "A semi‐parametric approach to model‐based sensitivity analysis in observational studies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S2), pages 668-691, December.
    8. Liu, Yan & Chen, Xi & Yan, Zhijun, 2019. "Depression in the House: The Effects of Household Air Pollution from Solid Fuel Use in China," IZA Discussion Papers 12654, Institute of Labor Economics (IZA).
    9. Noemi Kreif & Richard Grieve & Rosalba Radice & Zia Sadique & Roland Ramsahai & Jasjeet S. Sekhon, 2012. "Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data," Medical Decision Making, , vol. 32(6), pages 750-763, November.
    10. Noémi Kreif & Richard Grieve & Iván Díaz & David Harrison, 2015. "Evaluation of the Effect of a Continuous Treatment: A Machine Learning Approach with an Application to Treatment for Traumatic Brain Injury," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1213-1228, September.
    11. Do, Manh Hung & Nguyen, Trung Thanh & Grote, Ulrike, 2023. "Land consolidation, rice production, and agricultural transformation: Evidence from household panel data for Vietnam," Economic Analysis and Policy, Elsevier, vol. 77(C), pages 157-173.
    12. Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
    13. Abhilash Bandam & Eedris Busari & Chloi Syranidou & Jochen Linssen & Detlef Stolten, 2022. "Classification of Building Types in Germany: A Data-Driven Modeling Approach," Data, MDPI, vol. 7(4), pages 1-23, April.
    14. Uz Zaman, Qamar & Zhao, Yuhuan & Zaman, Shah & Batool, Kiran & Nasir, Rabiya, 2024. "Reviewing energy efficiency and environmental consciousness in the minerals industry Amidst digital transition: A comprehensive review," Resources Policy, Elsevier, vol. 91(C).
    15. Federico Biagi & Daniele Bondonio & Alberto Martini, 2015. "Counterfactual Impact Evaluation of Enterprise Support Programmes. Evidence from a Decade of Subsidies to Italian Firm," ERSA conference papers ersa15p1619, European Regional Science Association.
    16. Bono, Pierre-Henri & David, Quentin & Desbordes, Rodolphe & Py, Loriane, 2022. "Metro infrastructure and metropolitan attractiveness," Regional Science and Urban Economics, Elsevier, vol. 93(C).
    17. Boonstra Philip S. & Little Roderick J.A. & West Brady T. & Andridge Rebecca R. & Alvarado-Leiton Fernanda, 2021. "A Simulation Study of Diagnostics for Selection Bias," Journal of Official Statistics, Sciendo, vol. 37(3), pages 751-769, September.
    18. Zichen Deng & Maarten Lindeboom, 2021. "Early-life Famine Exposure, Hunger Recall and Later-life Health," Tinbergen Institute Discussion Papers 21-054/V, Tinbergen Institute.
    19. Leah Warfield Smith & Randall Lee Rose & Alex R. Zablah & Heath McCullough & Mohammad “Mike” Saljoughian, 2023. "Examining post-purchase consumer responses to product automation," Journal of the Academy of Marketing Science, Springer, vol. 51(3), pages 530-550, May.
    20. Baron, Opher & Callen, Jeffrey L. & Segal, Dan, 2023. "Does the bullwhip matter economically? A cross-sectional firm-level analysis," International Journal of Production Economics, Elsevier, vol. 259(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:reihed:v:65:y:2024:i:5:d:10.1007_s11162-023-09772-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.