Inequalities in Albanian Education: Evidence from Large-Scale Assessment Studies

• Authors: Arjan Shahini

Abstracts

EN

The study analyzes student, school and district level inequalities of Albanian education system as evidenced in two large-scale assessments. Two main datasets were used for this study, PISA 2018 and the Albanian State Matura Exam 2017. Due to the limited availability of data, the study could only consider a small number of dependent variables at the individual, school, and district level. Utilizing a multilevel analysis, the study observes considerable differences among schools and districts in all three PISA domains and the State Matura Exam. The results were inconclusive regarding shortages of resources at the school and district level. Staff shortage was associated with academic performance in the PISA 2018 dataset, but no statistical association could be identified with the lack of school resources. The analysis of the district financial resources did not show any significant relationship between spending and school performance in the Albanian State Matura Exam. Gender disparities were present in both datasets. Socioeconomic factors, which were measured only in the PISA dataset, had an effect on the student’ achievement.

Keywords

EN

PISA; large-scale assessment; Albanian education system; school effectiveness research; Albanian State Matura Exam

• Publisher: Wydawnictwo Adam Marszałek
• Journal: Kultura i Edukacja
• Year: 2021
• Issue: 4(134)
• Pages: 40-70

Dates

published

2021

Contributors

author

Arjan Shahini

• Martin Luther Universität Halle-Wittenberg

References

• Andrews, M., Duncombe, W., & Yinger, J. (2002). Revisiting Economies of Size in American Education: Are We Any Closer to a Consensus? Economics of Education Review, 21(3), 245–262. DOI: 10.1016/S0272-7757(01)00006-1.
• BalkanWeb (2015, June 1). Testi i Gjuhës dhe Letërsisë, maturantët protestë para MAS: Shumë pyetje s’kishin lidhje me tekstin [Language and Literature Test, Students Protest in Front of the Ministry of Education: Many Response Items Were Not Related with the Text]. Gazeta Shqiptare. Retrieved from: https://www.balkanweb.com/site/testi-i-gjuhes-dhe-letersise-maturantet-proteste-para-mas-shume-pyetje-skishin-lidhje-me-tekstin/.
• Bates, D., Mächler, M., Bolker, B., & Walker, S. (2015). Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67(1), 1–48. DOI: 10.18637/jss.v067.i01.
• Borgonovi, F., Ferrara, A., & Maghnouj, S. (2018). The Gender Gap in Educational Outcomes in Norway. OECD Education Working Papers, 183. https://doi.org/10.1787/f8ef1489-en.
• Bosker, R., & Guldemond, H. (1991). Interdependency of Performance Indicators: An Empirical Study in a Categorical School System. In: S.W. Raudenbush, & J. Douglas Willms (Eds.), Schools, Classrooms, and Pupils: International Studies of Schooling from a Multi¬level Perspective (pp. 101–113). San Diego, CA: Academic Press.
• Chapman, C., Muijs, D., Reynolds, D., Sammons, P., & Teddlie, C. (Eds.) (2016). The Routledge International Handbook of Educational Effectiveness and Improvement: Research, Policy, and Practice. New York: Routledge.
• Contini, D., Di Tommaso, M.L., & Mendolia, S. (2017). The Gender Gap in Mathematics Achievement: Evidence from Italian Data. Economics of Education Review, 58, 32–42. DOI: 10.1016/j.econedurev.2017.03.001.
• Della Sala, M.R., Knoeppel, R.C., & Marion, R. (2017). Modeling the Effects of Educational Resources on Student Achievement: Implications for Resource Allocation Policies. Education and Urban Society, 49(2), 180–202. DOI: 10.1177/0013124516643757.
• Figlio, D., Karbownik, K., Roth, J., & Wasserman, M. (2016). School Quality and the Gender Gap in Educational Achievement. American Economic Review, 106(5), 289–295. DOI: 10.1257/aer.p20161074.
• Fitz-Gibbon, C., & Koch, S. (2000). School Effectiveness and Education Indicators. In: C. Teddlie, & D. Reynolds (Eds.), The International Handbook of School Effectiveness Research (pp. 257–282). London: Falmer Press.
• Fowler, W.J., & Walberg, H.J. (1991). School Size, Characteristics, and Outcomes. Educational Evaluation and Policy Analysis, 13(2), 189–202. DOI: 10.3102/01623737013002189.
• Gelman, A., & Hill, J. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge: Cambridge University Press.
• Goldstein, H., & Thomas, S. (1996). Using Examination Results as Indicators of School and College Performance. Journal of the Royal Statistical Society. Series A (Statistics in Society), 159(1), 149–163. DOI: 10.2307/2983475.
• Gortazar, L., Kutner, D., & Inoue, K. (2014). Education Quality and Opportunities for Skills Development in Albania: An Analysis of PISA 2000–2012 Results. Washington, D.C.: World Bank Group. Retrieved from: http://documents.worldbank.org/curated/en/2012/01/20214469/education-quality-opportunities-skills-development-albania-analysis-pisa-2000-2012-results.
• Hanushek, E.A. (1989). The Impact of Differential Expenditures on School Performance. Educational Researcher, 18(4), 45–62. DOI: 10.2307/1176650.
• Hanushek, E.A., & Woessmann, L. (2014). Institutional Structures of the Education System and Student Achievement: A Review of Cross-Country Economic Research. In: R. Strietholt, W. Bos, J.E. Gustafsson, & M. Rosen (Eds.), Educational Policy Evaluation through International Comparative Assessments (pp. 145–175). Munster: Waxman.
• Hox, J.J., Moerbeek, M., & Van de Schoot, R. (2010). Multilevel Analysis: Techniques and Applications (2nd ). New York: Routledge.
• IDRA (2012). Matura Shtetërore: Një Vlerësim i Cilësisë së Sistemit [State Matura: A Quality Assessment of the System]. Tirana: Viti i Botimit. Retrieved from: https://www.idrainsti¬tute.org/files/reports/State%20Matura/Matura%20Shteterore%202012.pdf.
• IEA (2019). IEA International Database (IDB) Analyzer (Version 4.0.35) [Software]. Hamburg, Germany: IEA – International Association for the Evaluation of Education Achievement.
• INSTAT (2018). Arsimi [Education]. Retrieved from: http://databaza.instat.gov.al/pxweb/en/.
• Ireson, J. (2004). Private Tutoring: How Prevalent and Effective Is It? London Review of Education, 2(2), 109–122. DOI: 10.1080/1474846042000229458.
• ISTAT (2018, November 29). Integrazione delle seconde generazioni: Microdati ad uso pubblico. Retrieved from: https://www.istat.it/it/archivio/210741.
• Jacobs, J.E., & Bleeker, M.M. (2004). Girlsʼ and Boysʼ Developing Interests in Math and Science: Do Parents Matter? New Directions for Child and Adolescent Development, 106, 5–21. DOI: 10.1002/cd.113.
• Laukaityte, I., & Wiberg, M. (2017). Using Plausible Values in Secondary Analysis in Large-Scale Assessments. Communications in Statistics – Theory and Methods, 46(22), 11341–11357. DOI: 10.1080/03610926.2016.1267764.
• Lecki, G. (2010). LEMMA (Learning Environment for Multilevel Methods and Applications). Module 5: Introduction to Multilevel Modelling R Practical. Retrieved from: https://www.cmm.bris.ac.uk/lemma/.
• Liu, J., Peng, P., & Luo, L. (2020). The Relation between Family Socioeconomic Status and Academic Achievement in China: A Meta-Analysis. Educational Psychology Review, 32(1), 49–76. DOI: 10.1007/s10648-019-09494-0.
• Lockheed, M.E., Wagemaker, H. (2013). International Large-Scale Assessments: Thermometers, Whips or Useful Policy Tools? Research in Comparative and International Education, 8(3), 296–306. doi:10.2304/rcie.2013.8.3.296
• Lubienski, C.A., & Lubienski, S.T. (2013). The Public School Advantage: Why Public Schools Outperform Private Schools. Chicago: University of Chicago Press.
• Lucas, G., Daniel, K., & Keiko, I. (2014). Education quality and opportunities for skills development in Albania: an analysis of Pisa 2000–2012 results. Retrieved from: http://documents.worldbank.org/curated/en/2012/01/20214469/education-quality-opportunities-skills-development-albania-analysis-pisa-2000-2012-results
• Lüdecke, D. (2018a). sjPlot: Data Visualization for Statistics in Social Science. Retrieved from: https://cran.r-project.org/package=sjPlot.
• Lüdecke, D. (2018b). sjstats: Statistical Functions for Regression Models (Version 0.17.1). Retrieved from: https://CRAN.R-project.org/package=sjstats.
• Lunn, D.J., Thomas, A., Best, N., & Spiegelhalter, D. (2000). WinBUGS-a Bayesian Modelling Framework: Concepts, Structure, and Extensibility. Statistics and Computing, 10(4), 325–337. DOI: 10.1023/A:1008929526011.
• Maghnouj, S., Fordham, E., Guthrie, C., Henderson, K., & Trujillo, D. (2020, May 7). OECD Reviews of Evaluation and Assessment in Education: Albania. Paris: OECD.
• Martins, L., & Veiga, P. (2010). Do Inequalities in Parents’ Education Play an Important Role in PISA Students’ Mathematics Achievement Test Score Disparities? Economics of Education Review, 29(6), 1016–1033. DOI: 10.1016/j.econedurev.2010.05.001.
• Meyer, R.H. (1993). Can Schools Be Held Accountable for Good Performance? A Critique of Common Educational Performance Indicators. In: E.P. Hoffman (Ed.), Essays on the Economics of Education (pp. 75–110). Kalamazoo: WE Upjohn Institute for Employment Research. DOI: 10.17848/9780880995542.ch4.
• Ministry of Education and Science (2011). School Inventory and Education Survey: Final Results. (TA-ALB-10). Government of Albania.
• Ministry of Education (2014a). Dokumenti i strategjisë së zhvillimit të arsimit parauniversitar 2014–2020 [Document Strategy for the Development of Pre-University Education 2014–2020]. Tirana: Ministria e Arsimit dhe Sportit. Retrieved from: http://arsimi.gov.al/wp-content/uploads/2018/08/Strategji_APU_dokumenti_perfundimtar_24_03_2015.pdf.
• Ministry of Education (2014b, February 14). Karta e Performances se Shkolles [School Performance Card].
• National Agency of Examinations (2014). Vlerësim Kombëtar (Për nxënësit e klasës III dhe V) [National Assessment: For Students at the 3rd and 5th Grade]. Retrieved from: http://qsha.gov.al/infos/publikime_raporte/raport_komb_kl3-5.pdf.
• Neely, S.R., & Diebold, J. (2016). Public Expenditures and the Production of Education. Education Policy Analysis Archives, 24(88), 1–22. DOI: 10.14507/epaa.24.2441.
• OECD (2010). PISA 2009 Results: What Makes a School Successful?: Resources, Policies and Practices. Paris: OECD. Retrieved from: https://www.oecd.org/pisa/pisaprod¬ucts/48852721.pdf.
• OECD (2016, December 6). PISA 2015 Results. Paris: OECD.
• OECD (2019a). PISA 2018 Assessment and Analytical Framework. Paris: OECD. DOI: 10.1787/b25efab8-en.
• OECD (2019b). Program for International Student Assessment (PISA): Results from PISA 2018: Albania. Paris: OECD. Retrieved from: https://www.oecd.org/pisa/publications/PISA2018_CN_ALB.pdf.
• OSFA (2013). Matura Shtetërore ne Shqipëri, 2012. Tirana: Fondacioni Shoqëria e Hapur për Shqipërinë.
• Penner, A.M., & Paret, M. (2008). Gender Differences in Mathematics Achievement: Exploring the Early Grades and the Extremes. Social Science Research, 37(1), 239–253. DOI: 10.1016/j.ssresearch.2007.06.012.
• Prenzel, M. (2012). Introduction: Research on PISA, with PISA, and for PISA. In: M. Prenzel, M. Kobarg, K. Schöps, & S. Rönnebeck (Eds.), Research on PISA: Research Outcomes of the PISA Research Conference 2009 (pp. xiii-xxii). Heidelberg: Springer Science & Business Media.
• QSHA (2014). Vlerësim Kombëtar (Për nxënësit e klasës 3 dhe 5) [National Assessment: Students of the 3rd and 5th Grade]. Retrieved from: http://qsha.gov.al/infos/publikime_rap¬orte/raport_komb_kl3-5.pdf.
• QSHA (2017a). Matura Shteterore 2017: Raport Publik mbi Arritjet e Nxenesve [State Matura 2017: Public Report on Studentsʼ Achievements]. Retrieved from: http://qsha.gov.al/infos/publikime_raporte/raporti_msh_2017.pdf.
• QSHA (2017b). Provimet Kombetare te Arsimit Baze 2017. Retrieved from: http://qsha.gov.al/infos/publikime_raporte/raporti_pkab_2017.pdf.
• R Development Core Team (2014). R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing.
• Raudenbush, S.W., Bryk, A., & Congdon, R. (2013). HLM 7.01 for Windows [Hierarchical Linear and Nonlinear Modeling Software]. Skokie, IL: Scientific Software International.
• Raudenbush, S.W., & Willms, J.D. (Eds.) (2014). Schools, Classrooms, and Pupils: International Studies of Schooling from a Multilevel Perspective. San Diego, CA: Academic Press.
• Rizzuto, R., & Wachtel, P. (1980). Further Evidence on the Returns to School Quality. Journal of Human Resources, 15(2), 240–245. DOI: 10.2307/145333.
• Sakellariou, C. (2017). Private or Public School Advantage? Evidence from 40 Countries Using PISA 2012-Mathematics. Applied Economics, 49(29), 2875–2892. DOI: 10.1080/00036846.2016.1248361.
• Sander, W. (1993). Expenditures and Student Achievement in Illinois: New Evidence. Journal of Public Economics, 52(3), 403–416. DOI: 10.1016/0047-2727(93)90043-S.
• Scheerens, J. (2016). Educational Effectiveness and Ineffectiveness: A Critical Review of the Knowledge Base. Dordrecht: Springer.
• Scheerens, J., Hendriks, M., & Luyten, H. (2014). School Size Effects: Review and Conceptual Analysis. In: H. Luyten, M. Hendriks, & J. Scheerens (Eds.), School Size Effects Revisited (pp. 7–40). Dordrecht: Springer.
• Schmidt-Neke, M. (2007). Albania. In: W. Hörner, H. Döbert, B. von Kopp, & W. Mitter (Eds.), The Education Systems of Europe (pp. 11–32). Dordrecht: Springer.
• Serra, D., Barr, A., & Packard, T.G. (2011). Education Outcomes, School Governance and Parentsʼ Demand for Accountability: Evidence from Albania. Policy Research Working Paper, 5643. Washington: World Bank. Retrieved from: https://openknowledge.world-bank.org/bitstream/handle/10986/19879/WPS5643.pdf?sequence=1&isAllowed=y.
• Silm, G., Must, O., Täht, K., & Pedaste, M. (2021). Does Test-Taking Motivation Predict Test Results in a High-Stakes Testing Context? Educational Research and Evaluation, 1–27. DOI: 10.1080/13803611.2021.1949355.
• Sirin, S.R. (2005). Socioeconomic Status and Academic Achievement: A Meta-Analytic Review of Research. Review of Educational Research, 75(3), 417–453. DOI: 10.3102/00346543075003417.
• Somers, M.A., McEwan, P.J., & Willms, J.D. (2004). How Effective Are Private Schools in Latin America? Comparative Education Review, 48(1), 48–69. DOI: 10.1086/379841.
• Strand, S., Malmberg, L., & Hall, J. (2015, January 29). English as an Additional Language (EAL) and educational achievement in England: An analysis of the National Pupil Database. London, Oxford: Education Endowment Foundation, University of Oxford. Retrieved from: https://ore.exeter.ac.uk/repository/bitstream/handle/10871/23323/EAL_and_educational_achievement2.pdf?sequence=1.
• Teddlie, C., Stringfield, S., & Reynolds, D. (2000). Context Issues within School Effectiveness Research. In: C. Teddlie, & D. Reynolds (Eds.), The International Handbook of School Effectiveness Research (pp. 160–185). London: Falmer Press.
• Thomson, S. (2018). Achievement at School and Socioeconomic Background: An Educational Perspective. npj Science of Learning, 3(1), 5. DOI: 10.1038/s41539-018-0022-0.
• UNESCO (2017). Albania: Education Policy Review: Issues and Recommendations. Retrieved from: http://unesdoc.unesco.org/images/0025/002592/259245e.pdf.
• UNESCO (2018). Handbook on Measuring Equity in Education. Montreal, Canada: UNESCO Institute for Statistics. Retrieved from: http://uis.unesco.org/sites/default/files/documents/handbook-measuring-equity-education-2018-en.pdf.
• World Bank (2005, March). Poverty and Education in Albania: Who Benefits from Public Spending. Retrieved from: https://documents1.worldbank.org/curated/en/582031468004830192/pdf/319830AL.pdf.

Identifiers

DOI

10.15804/kie.2021.04.03

Biblioteka Nauki

1931990