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Major Decision: The Impact of Major Switching on Academic Outcomes in Community Colleges

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Abstract

A third of the 2- and 4-year undergraduates beginning college in 2011–2012 changed their major in the first 3 years of enrollment. Yet, few studies have examined the effects of major switching on student outcomes, particularly in community colleges. Major switching can delay or impede college completion through excess credit accumulation, or it can increase the probability of completion due to a better academic match. Using state administrative data and propensity score matching, we find that major switching increases certificate completion rates but moderately decreases the probability of bachelor’s degree completion in community colleges for students who started with a declared major. We suggest that instead of discouraging major switching, institutions should integrate switching into program planning. Policies like common course-sequencing, cross-discipline introductory courses and flexible application of credits can allow students to revise their interests and goals without losing much time, credits, or tuition dollars.

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Notes

  1. As part of state or national initiatives, about 300 colleges are using the guided pathways model to implement whole-college redesign that emphasizes, among other things, early long-term academic planning among students (Jenkins et al. 2019).

  2. Our data do not include credits earned by students who transferred to private or out-of-state 4-year universities. However, the NSC data suggests that only 5% of our sample transferred to private institutions, so we do not expect the lack of private or out-of-state 4-year data to affect our results.

  3. Our robustness checks include an analysis including the 1000 students who started with undeclared majors, results are discussed in a later section.

  4. A similar strategy was employed by Dadgar and Trimble (2015) and Liu et al. (2015).

  5. To test for the robustness of our definition we also model major switching across four-digit CIP codes. Despite an increase in majors from 22 to 167, the rate of switching only increases from 23 to 27%. The results using this definition are similar to our findings in magnitude and direction (see Table A2).

  6. See Table 1 for details on incidence of switching across majors.

  7. For a robustness check, we run the matching model using 0.2 standard deviations and find similar results. Yet using 0.05 standard deviations gives us a closer match between treated and control observations. We also run the model using a probit instead of a logit regression in the first stage and with the Abadie and Imbens (2011) standard errors that take into account the fact that the propensity scores are estimated in separate steps. The results remain consistent.

  8. Appendix Table A1 presents the post-match balance across treatment and control groups.

  9. The process of propensity score matching was done within each of the ten datasets and the mean of PSM variables from all datasets were used for calculating estimated treatment effects (Cham and West 2016; Hill 2004; Mitra and Reiter 2016).

  10. Literature suggests that poor performance in the first-term can increase major switching; however, these indicators may also be influenced by the initial major choice. We tested across alternate model specifications that sequentially excluded CIP, institutional effects and first-term academic performance variables. Stability of effects across these models suggests that we are matching on a robust set of variables.

  11. We separate AA and AS degrees from AAS because AAS is considered a terminal degree and program credits earned for this degree generally are not transferable to 4-year institutions.

  12. We define excess credits based on the most common degree requirements in the state. These average at 70 credits for associate degrees and 130 credits for bachelor’s degrees according to the state department of higher education website.

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Funding

Funding for this study was provided by the Bill & Melinda Gates Foundation. We are grateful for excellent feedback from Michelle Van Noy, Davis Jenkins, John Fink, and attendees of the 2019 Association for Education Finance Policy Annual Conference. Any errors are those of the authors.

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  1. Community College Research Center, Teachers College Columbia University, New York, USA

    Vivian Liu, Soumya Mishra & Elizabeth M. Kopko

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  1. Vivian Liu
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Correspondence to Soumya Mishra.

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Appendix

Appendix

See Tables 8 and 9.

Table 8 Sample mean and standard difference pre- and post-match
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Table 9 Effect of switching majors—alternate definition of majors
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Liu, V., Mishra, S. & Kopko, E. Major Decision: The Impact of Major Switching on Academic Outcomes in Community Colleges. Res High Educ 62, 498–527 (2021). https://doi.org/10.1007/s11162-020-09608-6

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