The effect of student and school characteristics on TIMSS 2015 science and mathematics achievement: The case of Türkiye
Burçin Coşkun 1 * , Engin Karadağ 2
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1 Trakya University, Faculty of Education, Edirne, Türkiye
2 Akdeniz University, Faculty of Education, Antalya, Türkiye
* Corresponding Author

Abstract

In this study, the effects of some student (e.g., gender, bullying, etc.) and school variables (e.g., emphasis on academic achievement, clarity of teaching, etc.) on the TIMSS 2015 science and mathematics achievement of eighth grade students in Türkiye were examined by controlling for the socioeconomic status of the students at the student and school level. The analyses were performed using the multilevel modelling method and the HLM8 package program. The findings show that school variables account for 34% of the variability in the TIMSS 2015 science achievement of eight grade students, while student variables account for 66%. Similar to this, school variables account for 35% of the variability in these students' mathematics achievement and student variables for 65% of it. The socioeconomic status of the school at the school level and students' confidence in learning the lesson at the student level are the two variables that have the strongest effects on students' achievement in science and mathematics. According to the results, other variables that have a significant effect on students' achievement in both science and mathematics at the school level are the clarity of teaching, the emphasis on academic achievement, and the school bullying level. Furthermore, school discipline problems have an effect on students' mathematics achievement. However, school resources and teacher qualifications do not have a significant effect on student achievement. Home educational resources and bullying among students are two important variables that effect how well students do in science and mathematics. The effect of gender and value learning the lesson on science achievement was significant, whereas the effect on mathematics achievement was not. The effect of like learning lesson on student achievement is significant only for mathematics. 

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References

  • Aksu, G., Güzeller, C. O., & Eser, M. T. (2017). Analysis of maths literacy performances of students with hierarchical linear modeling (HLM): The case of PISA 2012 Turkey. Education and Science, 42(191), 247-266. https://doi.org/10.15390/EB.2017.6956
  • Akyol, G., Sungur, S., & Tekkaya, C. (2010). The contribution of cognitive and metacognitive strategy use to students' science achievement. Educational Research and Evaluation, 16(1), 1-21. https://doi.org/10.1080/13803611003672348
  • Arifoğlu, A. (2019). Investigating of school effects on student achievement: A multilevel analysis of Turkey’s TIMSS 2015 data [Unpublished doctoral dissertation]. Hacettepe University.
  • Atar, H. Y. (2014). Multilevel effects of teacher characteristics on TIMSS 2011 science achievement. Education and Science, 39(172), 121-137.
  • Aydın, M. (2015). The effects of student-level and school-level factors on middle school students’ mathematics achievement [Unpublished doctoral dissertation]. Necmettin Erbakan University.
  • Aypay, A., Erdoğan, M., & Sözer, M. A. (2007). Variation among schools on classroom practices in science based on TIMSS‐1999 in Turkey. Journal of Research in Science Teaching, 44(10), 1417-1435. https://doi.org/10.1002/tea.20202
  • Beaton, A. E. (1996). Science achievement in the middle school years. IEA's third international mathematics and science study (TIMSS). Center for the Study of Testing, Evaluation, and Educational Policy, Boston College.
  • Blömeke, S, Olsen, R. V., & Suhl, U. (2016). Relation of student achievement to the quality of their teachers and instructional quality. In Jan-Eric Gustafsson & Trude Nilsen (Eds), Teacher quality, instructional quality and student outcomes (pp. 21-50). Springer. https://doi.org/10.1007/978-3-319-41252-8_2
  • Burroughs, N., Gardner, J., Lee, Y., Guo, S., Touitou, I., Jansen, K., & Schmidt, W. (2019). Relationships between instructional alignment, time, instructional quality, teacher quality, and student mathematics achievement. In Burrroughs et.al (Eds), Teaching for Excellence and Equity (pp. 63-100). Springer, Cham. https://doi.org/10.1007/978-3-030-16151-4_6
  • Brookover, W. B., Beady, C., Flood, P. K., & Schweitzer, J. H. (1979). School social systems and student achievement: Schools can make a difference. Praeger.
  • Caponera, E., & Losito, B. (2016). Context factors and student achievement in the IEA studies: Evidence from TIMSS. Large-scale Assessments in Education, 4(1), 12-20. https://doi.org/10.1186/s40536-016-0030-6
  • Ceylan, E., & Berberoglu, G. (2007). Factors related with students' science achievement: A modeling study. Education and Science, 32(144), 36-44.
  • Coleman, J. S. (1990). Equality and achievement in education. Routledge.
  • Dulay, S., & Karadağ, E. (2017). The effect of school climate on student achievement. In Karadağ, E. (Ed) The factors effecting student achievement (pp. 199-213). Springer, Cham. https://doi.org/10.1007/978-3-319-56083-0_12
  • Ehrenberg, R. G., Brewer, D. J., Gamoran, A., & Willms, J. D. (2001). Class size and student achievement. Psychological Science in the Public Interest, 2(1), 1-30.
  • Enders, C. K. (2010). Applied missing data analysis. Guilford Press.
  • Enders, C. K., & Tofighi, D. (2007). Centering predictor variables in cross-sectional multilevel models: A new look at an old issue. Psychological Methods, 12(2), 121-131. https://doi.org/10.1037/1082-989x.12.2.121
  • Erberber, E. (2009). Analyzing Turkey’s data from TIMSS 2007 to investigate regional disparities in eighth grade science achievement [Unpublished doctoral dissertation]. East Boston College, USA.
  • Ersan, O., & Rodriguez, M. C. (2020). Socioeconomic status and beyond: A multilevel analysis of TIMSS mathematics achievement given student and school context in Turkey. Large-scale Assessments in Education, 8(1), 1-32. https://doi.org/10.1186/s40536-020-00093-y
  • Fleming, L. C., & Jacobsen, K. H. (2010). Bullying among middle-school students in low and middle income countries. Health Promotion International, 25(1), 73-84. https://doi.org/10.1093/heapro/dap046
  • Garson, G. D. (2019). Multilevel modeling: Applications in STATA®, IBM® SPSS®, SAS®, R, & HLM. SAGE Publications.
  • Gökkaya, F., & Tekinsav-Sütcü, S. (2020). An investigation of the prevalence of peer bullying among middle school students. H. U. Journal of Education, 35(1), 40-54. https://doi.org/10.16986/HUJE.2018042225
  • Goldhaber, D. D., & Brewer, D. J. (1997). Why don't schools and teachers seem to matter? Assessing the impact of unobservables on educational productivity. Journal of Human Resources, 32(3), 505-523. https://doi.org/10.2307/146181
  • Goldhaber, D. D., & Brewer, D. J. (2000). Does teacher certification matter? High school teacher certification status and student achievement. Educational Evaluation and Policy Analysis, 22(2), 129-145. https://doi.org/10.3102/01623737022002129
  • Greenwald, R., Hedges, L. V., & Lain, R. D. (1996). The effects of school resources on student achievement. Review of Educational Research, 66(3), 361-396. https://doi.org/10.2307/1170528
  • Gronmo, L. S., Lindquist, M., Arora, A., & Mullis, I. V. S. (2013). TIMSS 2015 mathematics framework (Chapter 1). In I. V. S. Mullis & M. O. Martin (Eds), TIMSS 2015 Assessment Frameworks (pp. 11-27). http://timssandpirls.bc.edu/timss2015/frameworks.html
  • Gustafsson, J. E., & Nilsen, T. (2016). The impact of school climate and teacher quality on mathematics achievement: A difference-in-differences approach. Teacher Quality, Instructional Quality and Student Outcomes, 2, 81-95. https://doi.org/10.1007/978-3-319-41252-8_4
  • Gustafsson, J. E., Nilsen, T., & Hansen, K. Y. (2018). School characteristics moderating the relation between student socio-economic status and mathematics achievement in grade 8. Evidence from 50 countries in TIMSS 2011. Studies in Educational Evaluation, 57, 16-30. https://doi.org/10.1016/j.stueduc.2016.09.004
  • Hanushek, E. A. (1986). The economics of schooling: Production and efficiency in public schools. Journal of Economic Literature, 24(3), 1141-1177. https://www.jstor.org/stable/2725865
  • Hanushek, E. A. (1997). Assessing the effects of school resources on student performance: An update. Educational Evaluation and Policy Analysis, 19(2), 141-164. https://doi.org/10.2307/1164207
  • Hanushek, E. A., Rivkin, S. G., Rothstein, R., & Podgursky, M. (2004). How to improve the supply of high-quality teachers. Brookings Papers on Education Policy, 7, 7-44. https://www.jstor.org/stable/20067265
  • Harris, D. N., & Sass, T. R. (2011). Teacher training, teacher quality and student achievement. Journal of Public Economics, 95(7-8), 798-812. https://doi.org/10.1016/j.jpubeco.2010.11.009
  • Hedges, L. V., Laine, R. D., & Greenwald, R. (1994). An exchange: Part I: Does money matter? A meta-analysis of studies of the effects of differential school inputs on student outcomes. Educational Researcher, 23(3), 5-14. https://doi.org/10.3102/0013189X023003005
  • Hooper, M., Mullis, I. V. S., & Martin, M. O. (2013). TIMSS 2015 context questionnaire framework (Chapter 3). In Mullis, I.V.S. & Martin, M.O. (Eds), TIMSS 2015 Assessment Frameworks (pp. 61-82). http://timssandpirls.bc.edu/timss2015/frameworks.html
  • Hox, J. J. (2010). Applied multilevel analysis (2nd ed.). Routledge.
  • Hox, J. J., Moerbeek, M., & Van de Schoot, R. (2018). Multilevel analysis: Techniques and applications. New York, NY: Routledge.
  • Jones, L. R., Wheeler, G., & Centurino, V. A. (2013). TIMSS 2015 science framework (Chapter 2). In I. V. S. Mullis & M. O. Martin (Eds), TIMSS 2015 Assessment Frameworks (pp. 29-58). https://timssandpirls.bc.edu/timss2015/frameworks.html
  • Kiray, S. A., Gok, B., & Bozkir, A. S. (2015). Identifying the factors affecting science and mathematics achievement using data mining methods. Journal of Education in Science Environment and Health, 1(1), 28-48. http://doi.org/10.21891/jeseh.41216
  • Lai, S. L., Ye, R., & Chang, K. P. (2008). Bullying in middle schools: An Asian-Pacific regional study. Asia Pacific Education Review, 9(4), 503-515. https://doi.org/10.1007/BF03025666
  • Lamb, S., & Fullarton, S. (2002). Classroom and school factors affecting mathematics achievement: A comparative study of Australia and the United States using TIMSS. Australian Journal of Education, 46(2), 154-171. https://doi.org/10.1177/000494410204600205
  • LaRoche, S., Joncas, M., & Foy, P. (2016). Sample Design in TIMSS 2015. In M. O. Martin, I. V. S. Mullis, & M. Hooper (Eds), Methods and Procedures in TIMSS 2015 (pp. 3.1-3.37). http://timss.bc.edu/publications/timss/2015-methods/chapter-3.html
  • Lay, Y. F., & Chandrasegaran, A. L. (2016). Availability of school resources and TIMSS grade 8 students' science achievement: a comparative study between Malaysia and Singapore. International Journal of Environmental and Science Education, 11(9), 3065-3080.
  • Lay, Y. F., & Ng, K. T. (2019). The predictive effects of school safety on Southeast Asian grade 8 students’ science achievement in TIMSS 2015. Jurnal Pendidikan IPA Indonesia, 8(3), 426-435.
  • Liou, P. Y., & Liu, E. Z. F. (2015). An analysis of the relationships between Taiwanese eighth and fourth graders’ motivational beliefs and science achievement in TIMSS 2011. Asia Pacific Education Review, 16(3), 433-445. https://doi.org/10.1007/s12564-015-9381-x
  • 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. https://doi.org/10.1080/03610926.2016.1267764
  • Ma, X. (2002). Bullying in middle school: Individual and school characteristics of victims and offenders. School Effectiveness and School Improvement, 13(1), 63-89. https://doi.org/10.1076/sesi.13.1.63.3438
  • Martin, M. O., Mullis, I. V. S., Gregory, K. D., Hoyle, C., & Shen, C. (2000). Effective schools in science and mathematics. IEA’s third international mathematics and science study, IEA.
  • Martin, M. O., & Mullis, I. V. (2013). TIMSS and PIRLS 2011: Relationships among Reading, Mathematics, and Science Achievement at the Fourth Grade-Implications for Early Learning. International Association for the Evaluation of Educational Achievement.
  • Martin, M. O., Mullis, I. V. S., Foy, P., & Hooper, M. (2016a). TIMSS 2015 international results in science. http://timssandpirls.bc.edu/timss2015/international-results/
  • Martin, M. O., Foy, P., Mullis, I. V., & O’dwyer, L. M. (2013). Effective schools in reading, mathematics, and science at fourth grade. TIMSS and PIRLS, 109-178. In Martin, M. O., & Mullis, I. V. (Eds). TIMSS and PIRLS 2011: Relationships among Reading, Mathematics, and Science Achievement at the Fourth Grade-Implications for Early Learning. International Association for the Evaluation of Educational Achievement.
  • Martin, M. O., Mullis, I. V. S., Hooper, M., Yin, L., Foy, P., & Palazzo, L. (2016b). Creating and interpreting the TIMSS 2015 context questionnaire scales. In M. O. Martin, I. V. S. Mullis, & M. Hooper (Eds), Methods and procedures in TIMSS 2015 (pp.15.1-15.312). http://timss.bc.edu/publications/timss/2015-methods/chapter-15.html
  • Mohammadpour, E. (2013). A three-level multilevel analysis of Singaporean eighth-graders science achievement. Learning and Individual Differences, 26, 212-220. https://doi.org/10.1016/j.lindif.2012.12.005
  • Mohammadpour, E., & Abdul Ghafar, M. N. (2014). Mathematics achievement as a function of within-and between-school differences. Scandinavian Journal of Educational Research, 58(2), 189-221. https://doi.org/10.1080/00313831.2012.725097
  • Mohammadpour, E., Shekarchizadeh, A., & Kalantarrashidi, S. A. (2015). Multilevel modeling of science achievement in the TIMSS participating countries. The Journal of Educational Research, 108(6), 449-464. https://doi.org/10.1080/00220671.2014.917254
  • Mullis, I. V., & Martin, M. O. (2017). TIMSS 2019 assessment frameworks. International Association for the Evaluation of Educational Achievement. Herengracht 487, Amsterdam, 1017 BT, The Netherlands.
  • Mullis, I. V., Martin, M. O., Foy, P., & Arora, A. (2012). TIMSS 2011 international results in mathematics. International Association for the Evaluation of Educational Achievement.
  • Mullis, I. V. S., Martin, M. O., Foy, P., & Hooper, M. (2016). TIMSS 2015 international results in mathematics. http://timssandpirls.bc.edu/timss2015/international-results/
  • Mullis, I. V., Martin, M. O., Foy, P., Kelly, D. L., & Fishbein, B. (2020). TIMSS 2019 international results in mathematics and science. https://timssandpirls.bc.edu/timss2019/
  • Neuschmidt, O., Barth, J., & Hastedt, D. (2008). Trends in gender differences in mathematics and science (TIMSS 1995–2003). Studies in Educational Evaluation, 34(2), 56-72.
  • Nilsen, T., Gustafsson, J. E., & Blömeke, S. (2016). Conceptual framework and methodology of this report. In Nilsen, T. & Gustafsson, J. E. (Eds), Teacher quality, instructional quality and student outcomes (pp. 1-20). Springer. https://doi.org/10.1007/978-3-319-41252-8_1
  • Nortvedt, G. A., Gustafsson, J. E., & Lehre, A. C. W. (2016). The importance of instructional quality for the relation between achievement in reading and mathematics. In Nilsen, T. & Gustafsson, J. E. (Eds), Teacher quality, instructional quality and student outcomes (pp. 97-113), Springer International Publishing. http://doi.org/10.1007/978-3-319-41252-8_5
  • Nye, B., Konstantopoulos, S., & Hedges, L. V. (2004). How large are teacher effects?. Educational Evaluation and Policy Analysis, 26(3), 237-257. https://doi.org/10.3102/01623737026003237
  • OECD. (2014). Education at a glance 2014: OECD indicators, OECD Publishing. https://doi.org/10.1787/eag-2014-en
  • OECD. (2016). PISA 2015 results (Volume I): Excellence and equity in education, PISA, OECD Publishing. https://www.oecd.org/publications/pisa-2015-results-volume-i-9789264266490-en.htm
  • Olmez, I. B. (2020). Modeling mathematics achievement using hierarchical linear models. Elementary Education Online, 19(2), 944-957. https://doi.org/10.17051/ilkonline.2020.695837
  • Önal, S. İ. (2015). TIMSS 2011 cross country comparisons: Relationship between student-and teacher-level factors and 8th grade students’ science achievement and attitude toward science [Unpublished doctoral dissertation]. Middle East Technical University, Ankara.
  • Paccagnella, O. (2006). Centering or not centering in multilevel models? The role of the group mean and the assessment of group effects. Evaluation Review, 30(1), 66-85. https://doi.org/10.1177/0193841x05275649
  • Ponzo, M. (2013). Does bullying reduce educational achievement? An evaluation using matching estimators. Journal of Policy Modeling, 35(6), 1057-1078. https://doi.org/10.1016/j.jpolmod.2013.06.002
  • Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical linear models: Applications and data analysis methods. London: Sage Publication.
  • Raudenbush, S. W., Bryk, A. S., Cheong, Y. F., Congdon, R. T., & Du Toit, M. (2011). HLM 7: Hierarchical linear and nonlinear modeling. Scientific Software International.
  • Reyes, L. H. (1984). Affective variables and mathematics education. The Elementary School Journal, 84(5), 558-581. https://www.jstor.org/stable/1001237
  • Rumberger, R. W., & Palardy, G. J. (2004). Multilevel models for school effectiveness research. In D. Kaplan (Ed), The Sage handbook of quantitative methodology for the social sciences (pp. 235-258). Sage.
  • Rutkowski L., & Rutkowski D. (2016). The relation between students’ perceptions of instructional quality and bullying victimization. In Nilsen T., & Gustafsson JE. (Eds) Teacher quality, instructional quality and student outcomes. IEA Research for Education (A Series of In-depth Analyses Based on Data of the International Association for the Evaluation of Educational Achievement (IEA), Vol 2. (pp. 115-133). Springer. https://doi.org/10.1007/978-3-319-41252-8_6
  • Rutter, M., & Maughan, B. (2002). School effectiveness findings 1979–2002. Journal of School Psychology, 40(6), 451-475. https://doi.org/10.1016/S0022-4405(02)00124-3
  • Sarı, M. H., Arıkan, S., &Yıldızlı, H. (2017). 8. sınıf matematik akademik başarısını yordayan faktörler-TIMSS 2015. Eğitimde ve Psikolojide Ölçme ve Değerlendirme, 8(3), 246-265. https://doi.org/10.32960/uead.407078
  • Scherer, R., & Gustafsson, J. E. (2015). Student assessment of teaching as a source of information about aspects of teaching quality in multiple subject domains: An application of multilevel bifactor structural equation modeling. Frontiers in Psychology, 6, 1550-1570. https://doi.org/10.3389/fpsyg.2015.01550
  • Schreiber, J. B. (2002). Institutional and student factors and their influence on advanced mathematics achievement. The Journal of Educational Research, 95(5), 274-286. https://doi.org/10.1080/00220670209596601
  • Sirin, S. R. (2005). Socioeconomic status and academic achievement: A meta-analytic review of research. Review of Educational Research, 75(3), 417-453. https://doi.org/10.3102/00346543075003417
  • Snijders, T. A., & Bosker, R. J. (2012). Multilevel analysis: An introduction to basic and advanced multilevel modeling. Sage.
  • Suna, H. E., & Özer, M. (2021). The achievement gap between schools and relationship between achievement and socioeconomic status in Turkey. Journal of Measurement and Evaluation in Education and Psychology, 12(1), 55-71. http://doi.org/10.21031/epod.860431
  • Stanco, G. (2012). Using TIMSS 2007 data to examine STEM school effectiveness in an international context [Unpublished doctoral dissertation]. Boston College, Boston.
  • Stringfield, S., & Teddlie, C. (1988). A time to summarize: The Louisiana school effectiveness study. Educational Leadership, 46(2), 43-49.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.
  • Topçu, M. S., Erbilgin, E., & Arikan, S. (2016). Factors predicting Turkish and Korean students’ science and mathematics achievement in TIMSS 2011. Eurasia Journal of Mathematics, Science and Technology Education, 12(7), 1711-1737. https://doi.org/10.12973/eurasia.2016.1530a
  • Toropova A., Myrberg, E., & Johansson S. (2020). Teacher job satisfaction: the importance of school working conditions and teacher characteristics. Educational Review, 73(1), 71-97. https://doi.org/10.1080/00131911.2019.1705247
  • Tsai, L. T., & Yang, C. C. (2015). Hierarchical effects of school-, classroom-, and student-level factors on the science performance of eighth-grade Taiwanese students. International Journal of Science Education, 37(8), 1166-1181. https://doi.org/10.1080/09500693.2015.1022625
  • Tyack, D., & Cuban, L. (1995). Tinkering toward utopia. Harvard University Press.
  • White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica: Journal of the Econometric Society, 48(4), 817-838. https://doi.org/10.2307/1912934
  • Wößmann, L. (2003). Schooling resources, educational institutions and student performance: the international evidence. Oxford Bulletin of Economics and Statistics, 65(2), 117-170. https://doi.org/10.1111/1468-0084.00045
  • Woessmann, L. (2016). The importance of school systems: Evidence from international differences in student achievement. Journal of Economic Perspectives, 30(3), 3-32. https://www.jstor.org/stable/43855699
  • Wu, M. (2005). The role of plausible values in large-scale surveys. Studies in Educational Evaluation, 31(2-3), 114-128. https://doi.org/10.1016/j.stueduc.2005.05.005
  • Yalcin, S., Demirtasli, R. N., Dibek, M. I., & Yavuz, H. C. (2017). The effect of teacher and student characteristics on TIMSS 2011 mathematics achievement of fourth-and eighth-grade students in Turkey. International Journal of Progressive Education, 13(3), 79-94.
  • Yavuz, H. Ç., Demirtaşlı, R. N., Yalçın, S., & Dibek, M. İ. (2017). Türk öğrencilerin TIMSS 2007 & 2011 matematik başarısında öğrenci ve öğretmen özelliklerinin etkileri. Eğitim ve Bilim, 42(189), 27-47. http://doi.org/10.15390/EB.2017.6885
  • Yildirim, O., & Demir, S. B. (2014). The examination of teacher and student effectiveness at TIMSS 2011 science and math scores using multi-level models. Pakistan Journal of Statistics, 30(6), 1211-1218.
  • Yücel, C., & Karadağ, E. (2016). TIMSS 2015 Türkiye: Patinajdaki eğitim [TIMSS 2015 Turkey: Education in spin]. Eskişehir Osmangazi University Faculty of Education.

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