Thursday, February 26, 2015

Tracing regional inequalities in the Georgian education system (Part 2)

The first part of this blog post described the regional distribution of 2014 Unified Entrance Exam (UEE) mean scores in Georgia. Here in the second part, we look at applicants’ gender and location (as explained below) in order to understand how mean 2014 UEE scores differ by these variables. This post also considers the role and quality of teachers in these regional disparities.

A location variable was generated for the present analysis, based on the applicants’ municipality of registration. This variable breaks down the applicants into five groups: those coming from the capital, large cities (Kutaisi, Rustavi, Batumi, Poti), municipalities in Western Georgia (including both urban and rural settlements), municipalities in Eastern Georgia (again, including both urban and rural settlements), and ‘other’ (IDPs and foreign-registered applicants). Although it is not possible to differentiate between urban and rural residents of the municipalities using UEE data, in general, municipalities included in the Eastern and Western Georgia groupings mainly consist of  rural populations.

As descriptive analysis presented in the first part of this blog post showed, applicants from Tbilisi and large cities scored the highest. Applicants coming from ethnic minority municipalities and certain mountainous areas of Western Georgia received the lowest scores. In order to check whether regional differences are systematic or random, a statistical technique called Analysis of Variance (ANOVA) was employed. ANOVA checks whether the mean score of the groups under analysis differ from each other and whether a difference is statistically significant. The ANOVA results show that the main effects of gender, F(1, 26311)= 136.43, p<0.001, and location, F(4, 26311)= 396.36, p<0.001 are significant factors in applicants’ exam scores, while the interaction of these two variables is not significant, F(4, 26311)=1.67, p=0.1531. Post-hoc analysis demonstrates that there are no significant differences between the scores of applicants from the municipalities of Western and Eastern Georgia.

As shown in the chart above, in all locations, female applicants had higher mean scores than males. Applicants from Tbilisi – both males and females – were the most successful. Residents of large urban areas performed better than applicants from predominantly rural municipalities. Finally, applicants from the ‘other’ group scored higher than those from predominantly rural municipalities.

Although, in general, female applicants scored better than males, the difference was not vast. Importantly, there are significant regional gaps between applicants, which are clearly revealed by UEE scores. A number of reasons likely contribute to this disparity.

To start, Georgia is characterized by endemic regional inequality, including uneven quality of education in the country. There is an especially large gap between large urban areas and predominantly rural municipalities. The lack of quality education and good teachers in rural areas is obvious from the results of international tests taken by schoolchildren (TIMSS, PISA, PIRLS). Although, in these tests, Georgian pupils, overall, score around or above world averages, the picture is bleaker when looking at the scores by settlement type.

In Georgia, there is generally a lack of good teachers – nationally, over 90% of teachers of certain disciplines failed their certification exams in 2013. Still, the low quality of teachers in rural areas is more pronounced. If we look at the statistics for pupils per certified teachers (i.e. teachers who have passed special exams and hence are considered better performers compared with their peers), we see that this number is highest in ethnic minority municipalities – that is, there are fewer certified teachers with more students. In Marneuli, Ninotsminda and Akhalkalaki municipalities, there are one hundred or more pupils per certified teacher, while in Sachkhere municipality in Imereti the respective number is 25.

As school education, which should be instrumental in preparing pupils for university admission exams, appears to be inadequate, university applicants (and their parents) often hire private tutors rather than attend school in the final (11th and 12th) grades. Considering that private tutors are in many cases active teachers, the availability of quality tutors in rural areas is also lower, while better private tutors are found in the capital and large urban areas. This factor also contributes to regional disparities in UEE scores.

This series of blog posts explored the results of 2014 Unified Entrance Exams, taking into consideration regional and gender factors. Both descriptive and exploratory analysis shows that there are significant disparities between applicants, especially from the geographic point of view. While UEE was an excellent opportunity for many applicants who would not have had the chance to be accepted to a higher educational institution within the previous corrupt admissions system, certain segments of the population still do not enjoy equal opportunities, not because of the UEE per se, but due to the existing endemic problems that the Georgian secondary education system faces. In spite of its impressive success, the improved university admissions system has not tackled Georgia’s deep-rooted educational inequalities.

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