SCHOOL LOCATION AND STUDENT ACHIEVEMENT: RESULTS OF LITHUANIAN MATURITY EXAMINATIONS IN MATHEMATICS
One of the commonly used indicators of educational quality are student achievements in international large-scale student assessment studies and national school leaving examinations (Somerset, 2011, Engel & Rutkowski ,2014). School location is often considered as one of the factors which may have impact on educational quality. Educational research does not provide clear evidence that rural schools are inferior to urban schools (Reeves & Bylund, 2005), so there is a need for more research on urban-rural differences in other school quality factors (Othman & Muijs, 2013).
A decade ago the Ministry of Education and Science (MoES) in a policy paper stated that in rural regions teachers were less qualified, schools were undersupplied with ICT, offered less extra-curricular activities and support services, school infrastructure was less developed and required renovation. In the paper national testing of 8th grade students during the 2003, 2005 and 2007 was explored. Since 2003 the results of students in cities and regional centres remained around same level while the results of students in small towns and villages improved. Differences in quality of urban and rural schools were also indicated in State education strategy for 2013-2022 (MoES, 2014). The aim of our survey was to find out whether implementation of strategic educational goals and other policy measures resulted in diminishing the urban-rural differences in student achievement in Lithuanian schools.
We analyzed the results of five cycles of maturity examinations in mathematics 2013-2018. The data was provided by the Centre of Information Technologies in Education of MoES. Differences in achievements between municipalities and by school location in five groups (Vilnius, large cities, cities, small cities, rural area) were compared. Normality of data distribution was assessed using Shapiro-Wilk test. Wilcoxon test was applied with significance level 0.05.
The results indicate that the median of assessments is statistically significantly smaller in rural area compared to cities. Thus, if we base our decisions on the analysis of medians only, the achievements of students in rural areas are lower than in cities. Though testing whole distribution of achievements, we cannot say that the situation in the countryside is worse than in the cities. For formation of education policy, the analysis based on median/average is insufficient. Analysis of whole distribution of observations is prerequisite.
This research is funded by the European Social Fund according to the activity ‘Improvement of researchers’ qualification by implementing world-class R&D projects’ of Measure No.09.3.3-LMT-K-712. The project No. DOTSUT-39(09.3.3-LMT-K-712-01-0018)/LSS-250000-57.
 Engel, L. C., Rutkowski, D. (2014) Global Influences on National Definitions of Quality Education: Examples from Spain and Italy. Policy Futures in Education, 12(6), 769-783.
 Othman, M., Muijs, D. (2013) Educational quality differences in a middle-income country: the urban-rural gap in Malaysian primary schools. School Effectiveness and School Improvement, 24(1), 1-18.
 Reeves, E. B., Bylund, R. A. (2005) Are rural schools inferior to urban schools? A multilevel analysis of school accountability trends in Kentucky. Rural Sociology, 70(3), 360-386.
 Somerset, A. (2011). Strengthening educational quality in developing countries: the role of national examinations and international assessment systems. Compare, 41(1), 141–144.