Student Swirl at a Single Institution: The Role of Timing and Student Characteristics

Abstract

Back-and-forth enrollment at different institutions-student swirl-and concurrent enrollment at two or more institutions-double-dipping-have become common experiences for students in the United States. However, empirical studies explaining student mobility are rather rare. This study examines how student departures from and returns to a single institution are affected by college attendance elsewhere. The model presented here demonstrates that departure rates are higher for students concurrently attending another college. Return rates, on the other hand, are substantially lower for those students who attend other colleges after departure from the study institution. The effect of multiinstitutional attendance differs by college type, with the effect of 4-year out-of-state institution attendance being most pronounced. The simultaneous analysis of departures and returns provides the study institution with a more accurate and complete picture of student mobility.

Dreams Delayed: Barriers to Degree Completion among Undocumented Community College Students

“…Again, undocumented students are significantly more likely than their peers to stop out (odds ratio: 7.04, p < 0.01), after controlling for other factors. Interestingly, an odds ratio of 0.588 ( p < 0.05) indicates that the children of immigrants are less likely than those from non-immigrant families to withdraw from school, lending support to the ‘second-generation advantage’ or ‘immigrant optimism’ hypothesis (Kao and Tienda 1995; Kasinitz et al 2008). Latinos are about as likely to stop out as other racial/ethnic groups.…”

“…It is possible, for example, that the children of immigrants may benefit from a ‘second-generation advantage’ (Kasinitz et al 2008) that facilitates their degree completion, and therefore may be more likely than their US-born counterparts to maintain continuous enrolment. In other words, they may draw on their families' high expectations for success in the US, or ‘immigrant optimism’ (Kao and Tienda 1995), as well as strengths of both immigrant and US cultures and networks to help ensure their educational success. However, it may also be possible that the children of immigrants stop out at higher rates owing to their tendency to assume more family financial responsibilities than their native-born peers (Fuligni and Pedersen 2002), potentially hampering their ability to focus on their studies (Sy and Romero 2008).…”

The Relationship Between State Policy Levers and Student Mobility

“…In our sample, concurrent institutional enrollment ranged from a low of 3 % in year six to a high of 12 % in year two. Johnson and Muse (2012) found that concurrent enrollment among students attending research intensive (4-year) institutions is relatively infrequent, as low as 1 %. By contrast, Peter and Forrest Cataldi (2005) report that overall about 11 % of students overall (1995-1996 national cohort) enrolled concurrently, with the proportion a bit higher for students who began at public 4-year universities (12.4 %) By contrast, Bahr (2012) found that among community college students in California, about 13 % of students enrolled concurrently during a 7-year period.…”

A Methodology for Determining the Transferability Rate of Courses

“…One metric that has been tracked for over 30 years is transfer rate, or the proportion of students with the intent to transfer who actually transferred within a given timeframe (Astin, 1982;Cohen, 1994;Cohen & Brawer, 1987;Hossler et al, 2012;Johnson & Muse, 2012;McCormick & Carroll, 1997;Roska, 2009). The persistence and subsequent graduation rates of transfer students has been extensively researched (Cohen & Brawer, 1987;Ishitani, 2008); and researchers have also found that some demographic and other student characteristics affect student transfer and subsequent graduation rates (Cohen & Brawer, 1987;Piland, 1995;Wang, 2012).…”