The International Observatory on Academic Achievement - Documentary search

File number :
CS-ISC-05e

Bibliographic reference :
Dekkers, H. P. J. M., Bosker, R. J., & Driessen, G. W. J. M. (2000). Complex Inequalities of Educational Opportunities: A Large-Scale Longitudinal Study on the Relation Between Gender, Social Class, Ethnicity, and School Success. Educational Research and Evaluation, 6(1), 59-82.

Abstract :

Study Description
In this Dutch study, the authors try to emphasize the complexity of the educational inequality phenomenon by reviewing the combined effect of various inequality sources including gender, socio-economic status and ethnicity. The effect of these sources is more interactive than additive.

The authors also try to identify the interaction effect of these three variables on academic success indicators, i.e. the educational level attained six years after entering high school on the one hand, and on the other hand, the specialization choices of students in the vocational education path and the science subjects choices of students in the general education path.

This longitudinal study used data from the Dutch National Database – Secondary Education Students Cohort. The sample consisted of 18,391 students (381 schools) who entered high school in 1989. The academic career of these students was reviewed six years later (1995). Collected data was processed by statistical analyses.

Main Findings – Interaction of the Variables Studied
Results have shown the interactive effect of the variables studied. If these variables had a mere additive effect, one would expect that ethnic minority female students of lower socio-economic status would be the least successful students by the end of the study. However, findings have shown that working-class male students of the majority group are those who exhibited the most significant academic delay.

With regard to the variable “educational level attained six years after entering high school”, findings have shown that female students had an advantage over male students although the gender effect varied in function of socio-economic status and ethnicity. As socio-economic status increased, the advantage of female students over male students decreased. Furthermore, findings have shown that ethnic minority female students performed as well as those from the majority group, whereas ethnic minority male students appeared to outperform those of the majority group. Findings have also shown that during high school, female students and students from ethnic minority groups caught up with male students from majority groups, even outperforming them.

Evidence has shown that the variable “specialization choices of students in the vocational education path” was influenced by the gender effect. It was observed that male students opted for technical or agricultural specializations, whereas female students opted for health care specializations. However, there was one exception; female students from higher socio-economic status (whether from a minority group or not) tended to make less traditional choices.

Findings have shown that the variable “science subjects choices of students in the general education path” was once again influenced by the gender effect, as female students chose fewer science subjects than male students. In general, socio-economic status did not appear to be related to preference for science subjects. However, in the case of the male student group of ethnic minority, those from higher socio-economic backgrounds tended to choose more science subjects than those of lower socio-economic backgrounds.

These results have shown significant differences in the analysis of social inequalities and have provided interesting indications on populations that may best benefit from efforts made in order to reduce educational inequalities.

For more information on this subject, see files CS-ISC-10 and CS-ISC-16.

Links :
This journal is also available in electronic format.

Key Words :
Quantitative Analysis, Gender, Socio-economic status, Ethnicity, Academic Success, Educational Level, Vocational Education Path, General Education Path, Science, Dutch National Database, Longitudinal Study, Secondary/High School

Monitored Countries :
Netherlands