Author(s):Graça Leão Fernandes (presenting), Carlos Farinha Rodrigues

Conference:ECER 2017

Network:02. Vocational Education and Training (VETNET)

Format:Paper

Session Information

02 SES 05 C, VET Dropout and Completion

Paper Session

Time:2017-08-23
13:30-15:00

Room:K5.02

Chair:Petri Nokelainen

Contribution

Dropout in the Transition from Upper Secondary to Higher Education


The current economic situation in the EU and particularly in Portugal makes investment in human capital crucial for fostering any recovery in the economy. Dropout is a heavy economic burden and a loss of human capital investment.

The present Portuguese government has given the fight against dropout priority, in particular that between Upper Secondary and Higher Education.  An analysis of who is dropping out is essential in identifying high-risk students and its main determinants. This helps the clarification of the dropout process and is a first step in designing effective strategies to reduce it.

 

In this paper we want to find answers to questions about the main factors that drive dropout focusing in the transition between Upper Secondary and Higher Education. There is a huge literature about dropout in Secondary and Higher Education but fewer focuses in the transition between the two. Following previous research in the field we look to the impact of individual characteristics, family socio-economic background, and previous school trajectory but will also take in consideration the comparison between the expectations before and after Upper Secondary conclusions.

Portugal is a country with big differences between the more developed seaside and the less developed interior regions. So we analyze the differences in dropout proportion between seaside and   interior regions.

Because dropout rates are much higher among students who have followed vocational training courses than among those who followed scientific or humanistic courses the differences in the characteristics of those two groups will be analyzed too.

There is a huge[1] literature about dropout in Higher Education but less[2] focuses in the transition period. Literature about this topic examines the main determinants that affect access to Higher Education, mainly previous school trajectory and financial aid. Less discussed are ways to get and levels of information about Higher Education institutions and studying challenges they will have to face.

It was found that gender and race [Ingels et al. (2002), Cross & Slater (2002)] are persistent have impact on Higher  Education access. Some studies[3], found that High School track, academic performance and social support are strong predictors of college entry. Family socio economic background is another powerful predictor of dropout[4]. High School students from poor social origins are discouraged from even considering access to Higher Education and have less information about financial aid opportunities. Dropout in the transition is surely driven by affordability but also by the lower expectations less educated parents for their children. Besides they don’t know how to prepare their children for Higher Education challenges. Mismatch between information and expectations regarding degree and college choice turns Secondary to Higher Education transition more difficult[5].


[1] Dropout and Completion in Higher Education in Europe - Europa(2015), Hällsten, Martin (2017).

[2] Goldrick-Rab, S. et al (2007), Araque, F. et al.(2009), Siri, A. et al (2016).

[3] Adelman, C. (2004), Adelman et al. (2003), Nora & Horvath (1990), St. John (1991), St. John & Asker (2003), Thomas (1998).

[4] Cabrera & La Nasa (2001), Cabrera et al. (2003), Flint (1997), Glen (2204), Walpole(2003), Terenzine, P., et al.(2001).

[5] Rosenbaum & Person (2003)


Method

We use data collected from two surveys launched by the Statistics Department of the Education Ministry answered by Upper Secondary students who enrolled in 2013 and conclude the grade in 2015. The two surveys are answered by the same students. The first survey was launched just before the end of Upper Secondary Education and the second one 14 months later.
We merged the two databases into one who has information about 13200 youngsters and more than 1000 variables covering all the characteristics in the several dimensions above mentioned.
We begin to analyze how representative of the population was the sample in our data base. An exploratory data analysis is carried to analyze de main risk factors in the dropout process. For some variables t-tests for the proportion or mean differences between students who dropped out and those who don’t are performed to measure the significance of the effect of those variables. Finally we estimate a probit model that allows the identification of the main risk factors.


Expected Outcomes

We use data collected from two surveys launched by the Statistics Department of the Education Ministry answered by Upper Secondary students who enrolled in 2013 and conclude the grade in 2015. The two surveys are answered by the same students. The first survey was launched just before the end of Upper Secondary Education and the second one 14 months later.
We merged the two databases into one who has information about 13200 youngsters and more than 1000 variables covering all the characteristics in the several dimensions above mentioned.
We begin to analyze how representative of the population was the sample in our data base. An exploratory data analysis is carried to analyze de main risk factors in the dropout process. For some variables t-tests for the proportion or mean differences between students who dropped out and those who don’t are performed to measure the significance of the effect of those variables. Finally we estimate a probit model that allows the identification of the main risk factors.


References

Adelman, C., Daniel, B., Berkovitz, I., Owings, J. (2003), “Postsecondary attainmemt, attendance, curriculum and performance”, Washington, D.C.: NCES.
Adelman, C. (2004), “Principal indicators of student histories in postsecondary education”, Washington, D.C.: NCES.
Araque, Francisco; Roldán , Concepción; Salguero, Alberto (2009), “Factors influencing university drop out rates”, Computers & Education 53 (2009) 563–574.
Cabrera, A.F. & La Nasa, S.M. (2001), “On the path to college: three critical tasks facing america’s disadvantaged”, Research in Higher Education, vol. 42(2), 119-150.
Dropout and Completion in Higher Education in Europe - Europa (2015), ec.europa.eu/.../education.../education/.../dropout.
Flint, T. (1997), “Intergenerational effects of paying for college”, Research in Higher Education, vol. 38(3), 313-344.
Glen, D. (2204), -new book accuses education Dept of research errors that skewed policy making, Chronicle of Higher Education, july 9.
Goldrick-Rab, Sara; Carter, Deborah; Wagner, Rachelle (2007), “What Higher Education Has to Say About Transition to College”, Teachers College Record volume 109, number 10, October, pp.2444-2481.
Hällsten ,Martin (2017), “Is Education a Risky Investment? The Scarring Effect of University Dropout in Sweden”, Euro Sociologic Review (2017) jcw053.DOI: https://doi.org/10.1093/esr/jcw053 .
Ingels, S.J., Curti, T.R., Kaufman, P., Alt, M.N., Chen, X. (2002), “Coming of Age in the 1990’s: The eight-grade class of 1988 12 years later”, Washington, D.C.: NCES.
Nora, A. & Horvath, F. (1990), “Structural pattern differences in course enrollment rates among community college students”, Research in Higher Education, vol. 31(6), 539-554.
Rosenbaum, J.E. & Person, A.E. (2003), “Beyond college for all: Policies and practices to improve transition into college and jobs”, Professional School Counseling, 6(4), 252-260.
Siri, Anna. et al (2016), “Mind the gap between high school and university! A field qualitative survey at the National University of Caaguazú (Paraguay)”, Advances in Medical Education and practice, 7 pp. 301-308.
St. John, E.P. (1991), “What really influences minority attendance? Sequential analysis of the high school and beyond sophomore cohort”, Research in Higher Education, vol. 32(2), 141-158.
Terenzine, P., Cabrera, A.F., Bernal, E.(2001), Swimming against the tide: The poor in American higher education, New York: college Board.
Thomas, R. (1998), Black and Latino college enrollment. Paper presented at the AERA.
Walpole, M. (2003), “Socioeconomic status and college: How SES affects college experiences and outcomes”, Review of Higher Education, vol. 27(1), 45-73.


Author Information

Graça Leão Fernandes (presenting)
CEMAPRE- Lisbon School of Economics and Management - University of Lisbon
LISBOA
Carlos Farinha Rodrigues
CEMAPRE- Lisbon School of Economics and Management - University of Lisbon, Portugal; Lisbon School of Economics and Management - University of Lisbon