Compensation for poor performance through social background in tertiary education choices

ABSTRACT

In this paper, we use longitudinal data to examine the compensation effect when young students decide among different tertiary education options. We begin with an analysis of the transition to higher vocational training programmes or university degree programmes. For those choosing the university option, we then analyse the risk (high or low) of degree programme completion. Longitudinal data enables control variables from years before the decision is made, and variables affecting previous compensation processes, to be introduced into the logistic regression model. The results show that the compensation effect has a weak influence when deciding amongst enrolment options for tertiary education.

KEYWORDS:

• Compensation effect
• compensatory advantage
• risk of completion
• higher vocational training programmes
• transition to tertiary education
• transition to higher education

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 The search for a specific behaviour associated with a particular socioeconomic group may be similar to that required to test the Effectively Maintained Inequality (EMI) hypothesis; however, in our case, it is not expected that an inverted tendency for the two opposed extreme groups will be found, as suggested by (Lucas, 2017; Lucas and Byrne 2017; Vilalta-Bufí 2018).

2 Studying vocational tracks in the tertiary educational level has been possible in Spain since the 1990s.

3 In Spain, the European Higher Education Area (EHEA) Reform, which has been implementing the Bologna Declaration since 2008, has effected the organisation of degree programmes into a minimum of four years of study. Nowadays, in the Catalan university system, there are the following degree programmes: 83.5% four years, 3.5% five years, 11.4% six years, and 1.7% seven years (all of which are dual degree programmes).

4 HE: transition to higher education; Perf: school performance during the years prior to the transition moment; EdBck: family level of education (family educational background); Ctrl: any control variable included in the model.

5 Every subsequent year, we asked for the marks obtained the previous year. ‘Very good student’ is when the student always obtained very good marks (9 or 10 over 10 points); ‘Good student’ is when they obtained middle marks in at least one year (6, 7, or 8 over 10 points); and ‘Student sometimes failing’ is when they failed, just passed, or retook some subjects in at least one year.

6 Hence, if the student fails a subject that cost €200, the fee for the retake is €400 – meaning that the student will end up paying a total of €600. If the student has to take it a third time the fee escalates to €600 – meaning the student ends up paying €1,200 for the three attempts.

7 A University System Observatory (Sacristán and França 2013) study calculates the total cost of degrees in Catalonia after the huge increase of 2012. The study evidences how, due to the specific way of organising the fees, the total cost becomes tightly linked to the difficulty in passing the subjects. This is why we include the low performance rate as an important indicator in our operationalisation of risk.

8 The EMI hypothesis requires that lines cross each other to be confirmed (Vilalta-Bufí 2018); in other words, that the interactive effect is larger than the combined effect of the main and the conditioning variables.

9 Some authors speak about the possibility of applying a linear regression with a dichotomous dependent variable (Bernardi and Cebolla 2014); in our case, if a linear regression (instead of a logistic regression) is applied as an additional robustness check, some of the expected interactions of the model appear to show their statistical significance. See Appendix.

Additional information

Funding

This work was supported by the Ministerio de Ciencia, Innovación y Universidades [reference: CSO2013-44540-P and CSO2016-79945-P]. It’s also part of an international research to compare training and work paths of youth in different cities (www.iscy.org).