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Factors Related to the Mathematics Achievement of Resilient and Nonresilient Students with Different Genders in Top Performing Asian Countries

Yıl 2025, Cilt: 33 Sayı: 4, 716 - 725, 11.10.2025
https://doi.org/10.24106/kefdergi.1795686

Öz

Purpose: This study focused on the relationship between student-related factors and students’ mathematics achievement in top performing five Asian countries, including, Singapore, Chinese Taipei, South Korea, Japan, and Hong Kong, in TIMSS 2019 at the eighth-grade level with the specific focus on resilient and nonresilient students with different genders.
Design/Methodology/Approach: The data consisted of the pooled sample of 19,652 students in total. Seven student-related factors indicated by previous researchers were tested across the resilient and nonresilient students in these Asian countries through linear multiple regression technique.
Findings: As a result, valuing of mathematics and liking mathematics were found to have significant positive relationship with resilient students’ mathematics achievement while self-confidence and SES to be significantly related to only resilient male students’ achievement. In addition, for the nonresilient students, valuing mathematics, SES, liking mathematics, and discipline climate of classroom were found to be significantly positively related to achievement for both genders.
Highlights: The study revealed that valuing and liking mathematics consistently contributed to higher mathematics achievement among both resilient and nonresilient students across genders. While self-confidence in mathematics and socioeconomic status (SES) were not significant for resilient female students, they emerged as important predictors for resilient male students as well as for both genders of nonresilient students. Moreover, classroom discipline climate positively influenced the achievement of nonresilient students but showed no effect on resilient students. In contrast, school belonging and experiences of bullying were not significantly related to mathematics achievement in the overall sample.

Kaynakça

  • Abazaoğlu, I., Yatağan, M., Yıldızhan, Y., Arifoğlu, A., & Umurhan, H. (2015). Öğrencilerin Matematik başarısının uluslararası fen ve matematik eğilimleri araştırması sonuçlarına göre değerlendirilmesi [Examination of the students’ mathematics achievement by the trends in international mathematics and science study]. Electronic Turkish Studies, 10(7), 33-49.
  • Agasisti, T., & Longobardi, S. (2014). Inequality in education: Can Italian disadvantaged students close the gap? Journal of Behavioral and Experimental Economics, 52, 8-20.
  • Agasisti, T., Avvisati, F., Borgonovi, F., & Longobardi, S. (2018). Academic resilience: What schools and countries do to help disadvantaged students succeed in PISA. OECD education working papers, 167. OECD Publishing.
  • Akyüz, G., & Pala, N. M. (2010). The effect of student and class characteristics on mathematics literacy and problem solving in PISA 2003. Elementary Education Online, 9(2), 668-678
  • Akyüz, G. (2006). Investigation of the effect of teacher and class characteristics on mathematics achievement in Turkey and European Union countries. Elementary Education Online, 5(2), 75-86.
  • Akyüz, G. (2014). The effects of student and school factors on mathematics achievement in TIMSS 2011. Eğitim ve Bilim, 39(172), 150-162.
  • Alacacı, C., & Erbaş, A. K. (2010). Unpacking the inequality among Turkish schools: Findings from PISA 2006. International Journal of Educational Development, 30(2), 182-192.
  • Allan, J. F., McKenna, J., & Dominey, S. (2014). Degrees of resilience: Profiling psychological resilience and prospective academic achievement in university inductees. British Journal of Guidance & Counselling, 42(1), 9-25.
  • Atar, B. (2011). Application of descriptive and explanatory item response models to TIMSS 2007 Turkey mathematics data. Eğitim ve Bilim, 36(159), 255-269.
  • Avcı, S. (2022). Investigation of the individual characteristics that predict academic resilience. International Journal of Contemporary Educational Research, 9(3), 543-556
  • Bates, D. (2024). Linear mixed-effects models using ‘Eigen’ and S4. R package (version 1.1-35.4). https://cran.r-project.org/web/packages/lme4/lme4.pdf. Accessed 11 June 2024.
  • Demir, I., Kılıç, S., & Deprem, O. (2009). Factors affecting Turkish students’ achievement in mathematics. US-China Education Review, 6(6), 47-53.
  • Demir, I., Kılıç, S., & Ünal, H. (2010). Effects of students’ and schools’ characteristics on mathematics achievement: Findings from PISA 2006. Procedia Social and Behavioral Sciences, 2(2010), 3099-3103.
  • Dinçer, M. A., & Kolasın, G. U. (2009). Türkiye’de öğrenci başarısında eşitsizliğin belirleyicileri [The determination of inequalities in student success in Turkey]. Istanbul, Turkey: Sabanci Universitesi Egitim Girisimi Reformu.
  • Dincer, M. A., & Uysal, G. (2010). The determinants of student achievement in Turkey. International Journal of Educational Development, 30(6), 592-598.
  • Doğan, N., & Barış, F. (2010). Tutum, değer ve özyeterlik değişkenlerinin TIMSS-1999 ve TIMSS-2007 sınavlarında öğrencilerin matematik başarılarını yordama düzeyleri [The prediction of students’ attitudes, values, and self-efficacies variables on their mathematics achievement on TIMSS-1999 and TIMSS-2007]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 1(1), 44-50.
  • Doll, B., Zucker, S., & Brehm, K. (2004). Resilient classrooms: Creating healthy environments for learning. Guilford Publications.
  • DuMont, K. A., Widom, C.S., & Czaja, S.J. (2007). Predictors of resilience in abused and neglected children grown-up: The role of individual and neighborhood characteristics. Child Abuse and Neglect, 31, 255-274.
  • Engin-Demir, C. (2009). Factors influencing the academic achievement of the Turkish urban poor. International Journal of Educational Development, 29(2009), 17-29.
  • Erberber, E., Stephens, M., Mamedova, S., Ferguson, S., & Kroeger, T. (2015). Socioeconomically disadvantaged students who are academically successful: Examining academic resilience cross-nationally. IEA’s Policy Brief Series, 5. Amsterdam
  • Frempong, G., Visser, M., Feza, N., Winnaar, L., & Nuamah, S. (2016). Resilient learners in schools serving poor communities. Electronic Journal of Research in Educational Psychology, 14(2), 352-367.
  • Güven, B., & Çobakçor, B. O. (2013). Factors influencing mathematical problem-solving achievement of seventh grade Turkish students. Learning and Individual Differences, 23(2013), 131-137.
  • Güzel, Ç. I., & Berberoğlu, G. (2005). An analysis of the Programme for International Student Assessment 2000 (PISA 2000) mathematical literacy data for Brazilian, Japanese, and Norwegian students. Studies in Educational Evaluation, 31, 283–314.
  • Hopkins, D. (2005), The practice and theory of school improvement: International handbook of educational change, (Vol. 4), Springer Science and Business Media.
  • Kılıç, S., Çene, E., & Demir, I. (2012). Comparison of learning strategies for mathematics achievement in Turkey with eight countries. Educational Sciences, 12(4), 2594-2598.
  • Kyriakides, L., & Creemers, B. P. (2008). Using a multidimensional approach to measure the impact of classroom-level factors upon student achievement: A study testing the validity of the dynamic model. School Effectiveness and School Improvement, 19(2), 183-205.
  • Kyriakides, L., Creemers, B., Antoniou, P., & Demetriou, D. (2010). A synthesis of studies searching for school factors: Implications for theory and research. British Educational Research Journal, 36(5), 807–830.
  • Lessard, A., Butler-Kisber, L., Fortin, L., & Marcotte, D. (2014). Analysing the discourse of dropouts and resilient students. The Journal of Educational Research, 107(2), 103–110.
  • Li., M.H. (2008). Helping college students cope: Identifying predictors of active coping in different stressful situations. Journal of Psychiatry, Psychology and Mental Health, 2(1), 1-15.
  • Lorah, J. A. (2018). Effect size measures for multilevel models: Definition, interpretation, and TIMSS example. Large-Scale Assessments in Education, 6(1), 8.
  • Ma, X., Jong, C., & Yuan, J. (2013). Exploring reasons for the East Asian success in PISA. In H. D. Meyer & A. Benavot (Eds.), PISA, power, and policy: The emergence of global educational governance, Oxford: Symposium Books.
  • Martin, A. J., & Marsh, H. W. (2006). Academic resilience and its psychological and educational correlates: A construct validity approach. Psychology in the Schools, 43(3), 267–281.
  • Martin, A. J., & Marsh, H. W. (2008). Academic buoyancy: Towards an understanding of students’ everyday academic resilience. Journal of School Psychology, 46, 53–83.
  • Martin, A.J. & Marsh, H. W. (2009). Academic resilience and academic buoyancy: Multidimensional and hierarchical conceptual framing of causes, correlates and cognate constructs. Oxford Review of Education, 35(3), 353–370.
  • Martin, M.O., Foy, P., Mullis, I.V.S., & O’Dwyer, L.M. (2013). Effective schools in reading, mathematics, and science at the fourth grade. In M.O. Martin & I.V.S. Mullis (Eds.), TIMSS and PIRLS 2011: Relationships among reading, mathematics, and science achievement at the fourth grade—Implications for early learning. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
  • Masten, A. S. (2014). Global perspectives on resilience in children and youth. Child Development, 85, 6–20.
  • Maxwell, S., Reynolds, K., Lee, E., Subasic, E., & Bromhead, D. (2017). The impact of school climate and school identification on academic achievement: Multilevel modeling with student and teacher data. Frontiers in Psychology, 8, 1-21.
  • McLafferty M., Mallet J., & McCauley V. (2012). Coping at university: The role of resilience, emotional intelligence, age and gender. Journal of Quantitative Psychological Research, 1, 1–6.
  • Mullis, I. V. S. (2017). Introduction. In Mullis, I. V. S., Martin, M. O. (Eds.). TIMSS 2019 assessment frameworks (pp. 1-10). Chestnut Hill, MA: TIMSS & PIRLS International Study Center at Boston College.
  • Mullis, I. V. S., Martin, M. O., Foy, P., Kelly, D. L., & Fishbein, B. (2020). TIMSS 2019 International Results in Mathematics and Science. Retrieved from Boston College, TIMSS & PIRLS International Study Center. Website: https://timssandpirls.bc.edu/timss2019/international-results/
  • Nilsen, T., Blömeke, S., Hansen, K. Y., & Gustafsson, J. E. (2016). Can schools contribute to enhance equity? The answer may depend on a country’s developmental level. IEA Policy Brief.
  • OECD. (2012). PISA 2012 Results: Excellence through Equity (Volume II): Giving Every Student the Chance to Succeed. Paris: OECD Publishing.
  • OECD. (2018). Equity in education: Breaking down barriers to social mobility. OECD Publishing.
  • Özer, Y., & Anıl, D. (2011). Examining the factors affecting students’ science and mathematics achievement with structural equation modeling. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 41(2011), 313,324.
  • Parker, J. D. A., Hogan, M. J., Eastabrook, J. M., Oke, A., & Wood, L. M. (2006). Emotional intelligence and student retention: Predicting the successful transition from high school to university. Personality and Individual Differences, 41, 1329-1336.
  • R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/.
  • Radisic, J., & Pettersen, A. (2020). Resilient and nonresilient students in Sweden and Norway—Investigating the interplay between their self-beliefs and the school environment. In T. S. Frones, A.
  • Pettersen, J. Radisic, N. Buchholtz (Eds.), Equity, equality and diversity in the Nordic model of education, Cham, Switzerland: Springer.
  • Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. In R. Murnane & G. Duncan (Eds.), Whither opportunity? Rising inequality in schools, and children’s life changes. Russel Sage Foundation Press.
  • Sander, P., & Sanders, L. (2009). Measuring academic behavioural confidence: The ABC scale revisited. Studies in Higher Education, 34(1), 19–35.
  • Sandoval-Hernandez, A., & Cortes, D. (2012). Factors and conditions that promote academic resilience: A cross-country perspective. Paper presented at the annual conference of the Comparative and International Education Society, Puerto Rico.
  • Sandoval-Hernandez, A., & Bialowolski, P. (2016). Factors and conditions promoting academic resilience: A TIMSS-based analysis of five Asian education systems. Asia Pacific Education Review, 17, 511–520.
  • Shin, J., Lee, H., & Kim, Y. (2009). Student and school factors affecting mathematics achievement: International comparisons between Korea, Japan, and the USA. School Psychology International, 30, 520–537.
  • Steenkamp, J. B. E., & Baumgartner, H. (1998). Assessing measurement invariance in cross national consumer research. Journal of Consumer Research 25(1), 78–90.
  • Sun, J., & Stewart, D. (2007). Age and gender effects on resilience in children and adolescents. International Journal of Mental Health Promotion, 9(4), 16–25.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (sixth edition). New Jersey: Pearson.
  • Uzun, S., Bütüner, S. O., & Yiğit, N. (2010). A comparison of the results of TIMSS 1999-2007: The most successful five countries-Turkey sample. Elementary Education Online, 9(3), 1174-1188.
  • Xie, C., & Ma, Y. (2019). The mediating role of cultural capital in the relationship between socio-economic status and student achievement in 14 economies. British Educational Research Journal, 45, 838–855.
  • Yayan, B., & Berberoğlu, G. (2004). A re-analysis of the TIMSS 1999 mathematics assessment data of the Turkish students. Studies in Educational Evaluation, 30(2004), 87-104.

Yüksek Başarılı Asya Ülkelerinde Farklı Cinsiyetlerden Dirençli ve Dirençsiz Öğrencilerin Matematik Başarılarıyla İlişkili Faktörler

Yıl 2025, Cilt: 33 Sayı: 4, 716 - 725, 11.10.2025
https://doi.org/10.24106/kefdergi.1795686

Öz

Çalışmanın amacı: Bu çalışma, öğrenciye ilişkin faktörler ile öğrencilerin matematik başarıları arasındaki ilişkiyi, TIMSS 2019 sekizinci sınıf düzeyinde Singapur, Çin Taipesi, Güney Kore, Japonya ve Hong Kong gibi başarı düzeyi yüksek beş Asya ülkesinde, dirençli ve dirençsiz öğrenciler ile cinsiyet farklılıklarına odaklanarak incelemiştir.
Materyal ve Yöntem: Veriler, toplamda 19.652 öğrenciden oluşan havuz örneklemi kapsamaktadır. Önceki araştırmalarda belirtilen öğrenciye ilişkin yedi faktör, bu Asya ülkelerinde dirençli ve dirençsiz öğrenciler arasında çoklu doğrusal regresyon yöntemiyle test edilmiştir.
Bulgular: Sonuç olarak, matematiğe değer verme ve matematiği sevmenin, dirençli öğrencilerin matematik başarısıyla anlamlı düzeyde pozitif ilişkili olduğu; öz güven ve sosyoekonomik statünün ise yalnızca dirençli erkek öğrencilerin başarısıyla anlamlı düzeyde ilişkili olduğu bulunmuştur. Ayrıca, dirençsiz öğrenciler için, matematiğe değer verme, sosyoekonomik statü, matematiği sevme ve sınıf disiplin ortamı hem kız hem erkek öğrencilerin başarısıyla anlamlı ve pozitif yönde ilişkili bulunmuştur.
Önemli Vurgular: Çalışma, matematiğe değer verme ve matematiği sevmenin, hem dirençli hem de dirençsiz öğrencilerin farklı cinsiyetlerdeki başarılarını tutarlı bir biçimde artırdığını ortaya koymuştur. Matematikte öz güven ve sosyoekonomik statü (SES), dirençli kız öğrenciler için anlamlı bulunmazken, dirençli erkek öğrenciler ve dirençsiz öğrencilerin her iki cinsiyeti için önemli yordayıcılar olarak öne çıkmıştır. Ayrıca, sınıfın disiplin iklimi dirençsiz öğrencilerin başarılarını olumlu yönde etkilerken, dirençli öğrenciler üzerinde anlamlı bir etkisi bulunmamıştır. Buna karşın, okula aidiyet ve zorbalık deneyimleri genel örneklemde matematik başarısı ile anlamlı bir ilişki göstermemiştir.

Kaynakça

  • Abazaoğlu, I., Yatağan, M., Yıldızhan, Y., Arifoğlu, A., & Umurhan, H. (2015). Öğrencilerin Matematik başarısının uluslararası fen ve matematik eğilimleri araştırması sonuçlarına göre değerlendirilmesi [Examination of the students’ mathematics achievement by the trends in international mathematics and science study]. Electronic Turkish Studies, 10(7), 33-49.
  • Agasisti, T., & Longobardi, S. (2014). Inequality in education: Can Italian disadvantaged students close the gap? Journal of Behavioral and Experimental Economics, 52, 8-20.
  • Agasisti, T., Avvisati, F., Borgonovi, F., & Longobardi, S. (2018). Academic resilience: What schools and countries do to help disadvantaged students succeed in PISA. OECD education working papers, 167. OECD Publishing.
  • Akyüz, G., & Pala, N. M. (2010). The effect of student and class characteristics on mathematics literacy and problem solving in PISA 2003. Elementary Education Online, 9(2), 668-678
  • Akyüz, G. (2006). Investigation of the effect of teacher and class characteristics on mathematics achievement in Turkey and European Union countries. Elementary Education Online, 5(2), 75-86.
  • Akyüz, G. (2014). The effects of student and school factors on mathematics achievement in TIMSS 2011. Eğitim ve Bilim, 39(172), 150-162.
  • Alacacı, C., & Erbaş, A. K. (2010). Unpacking the inequality among Turkish schools: Findings from PISA 2006. International Journal of Educational Development, 30(2), 182-192.
  • Allan, J. F., McKenna, J., & Dominey, S. (2014). Degrees of resilience: Profiling psychological resilience and prospective academic achievement in university inductees. British Journal of Guidance & Counselling, 42(1), 9-25.
  • Atar, B. (2011). Application of descriptive and explanatory item response models to TIMSS 2007 Turkey mathematics data. Eğitim ve Bilim, 36(159), 255-269.
  • Avcı, S. (2022). Investigation of the individual characteristics that predict academic resilience. International Journal of Contemporary Educational Research, 9(3), 543-556
  • Bates, D. (2024). Linear mixed-effects models using ‘Eigen’ and S4. R package (version 1.1-35.4). https://cran.r-project.org/web/packages/lme4/lme4.pdf. Accessed 11 June 2024.
  • Demir, I., Kılıç, S., & Deprem, O. (2009). Factors affecting Turkish students’ achievement in mathematics. US-China Education Review, 6(6), 47-53.
  • Demir, I., Kılıç, S., & Ünal, H. (2010). Effects of students’ and schools’ characteristics on mathematics achievement: Findings from PISA 2006. Procedia Social and Behavioral Sciences, 2(2010), 3099-3103.
  • Dinçer, M. A., & Kolasın, G. U. (2009). Türkiye’de öğrenci başarısında eşitsizliğin belirleyicileri [The determination of inequalities in student success in Turkey]. Istanbul, Turkey: Sabanci Universitesi Egitim Girisimi Reformu.
  • Dincer, M. A., & Uysal, G. (2010). The determinants of student achievement in Turkey. International Journal of Educational Development, 30(6), 592-598.
  • Doğan, N., & Barış, F. (2010). Tutum, değer ve özyeterlik değişkenlerinin TIMSS-1999 ve TIMSS-2007 sınavlarında öğrencilerin matematik başarılarını yordama düzeyleri [The prediction of students’ attitudes, values, and self-efficacies variables on their mathematics achievement on TIMSS-1999 and TIMSS-2007]. Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi, 1(1), 44-50.
  • Doll, B., Zucker, S., & Brehm, K. (2004). Resilient classrooms: Creating healthy environments for learning. Guilford Publications.
  • DuMont, K. A., Widom, C.S., & Czaja, S.J. (2007). Predictors of resilience in abused and neglected children grown-up: The role of individual and neighborhood characteristics. Child Abuse and Neglect, 31, 255-274.
  • Engin-Demir, C. (2009). Factors influencing the academic achievement of the Turkish urban poor. International Journal of Educational Development, 29(2009), 17-29.
  • Erberber, E., Stephens, M., Mamedova, S., Ferguson, S., & Kroeger, T. (2015). Socioeconomically disadvantaged students who are academically successful: Examining academic resilience cross-nationally. IEA’s Policy Brief Series, 5. Amsterdam
  • Frempong, G., Visser, M., Feza, N., Winnaar, L., & Nuamah, S. (2016). Resilient learners in schools serving poor communities. Electronic Journal of Research in Educational Psychology, 14(2), 352-367.
  • Güven, B., & Çobakçor, B. O. (2013). Factors influencing mathematical problem-solving achievement of seventh grade Turkish students. Learning and Individual Differences, 23(2013), 131-137.
  • Güzel, Ç. I., & Berberoğlu, G. (2005). An analysis of the Programme for International Student Assessment 2000 (PISA 2000) mathematical literacy data for Brazilian, Japanese, and Norwegian students. Studies in Educational Evaluation, 31, 283–314.
  • Hopkins, D. (2005), The practice and theory of school improvement: International handbook of educational change, (Vol. 4), Springer Science and Business Media.
  • Kılıç, S., Çene, E., & Demir, I. (2012). Comparison of learning strategies for mathematics achievement in Turkey with eight countries. Educational Sciences, 12(4), 2594-2598.
  • Kyriakides, L., & Creemers, B. P. (2008). Using a multidimensional approach to measure the impact of classroom-level factors upon student achievement: A study testing the validity of the dynamic model. School Effectiveness and School Improvement, 19(2), 183-205.
  • Kyriakides, L., Creemers, B., Antoniou, P., & Demetriou, D. (2010). A synthesis of studies searching for school factors: Implications for theory and research. British Educational Research Journal, 36(5), 807–830.
  • Lessard, A., Butler-Kisber, L., Fortin, L., & Marcotte, D. (2014). Analysing the discourse of dropouts and resilient students. The Journal of Educational Research, 107(2), 103–110.
  • Li., M.H. (2008). Helping college students cope: Identifying predictors of active coping in different stressful situations. Journal of Psychiatry, Psychology and Mental Health, 2(1), 1-15.
  • Lorah, J. A. (2018). Effect size measures for multilevel models: Definition, interpretation, and TIMSS example. Large-Scale Assessments in Education, 6(1), 8.
  • Ma, X., Jong, C., & Yuan, J. (2013). Exploring reasons for the East Asian success in PISA. In H. D. Meyer & A. Benavot (Eds.), PISA, power, and policy: The emergence of global educational governance, Oxford: Symposium Books.
  • Martin, A. J., & Marsh, H. W. (2006). Academic resilience and its psychological and educational correlates: A construct validity approach. Psychology in the Schools, 43(3), 267–281.
  • Martin, A. J., & Marsh, H. W. (2008). Academic buoyancy: Towards an understanding of students’ everyday academic resilience. Journal of School Psychology, 46, 53–83.
  • Martin, A.J. & Marsh, H. W. (2009). Academic resilience and academic buoyancy: Multidimensional and hierarchical conceptual framing of causes, correlates and cognate constructs. Oxford Review of Education, 35(3), 353–370.
  • Martin, M.O., Foy, P., Mullis, I.V.S., & O’Dwyer, L.M. (2013). Effective schools in reading, mathematics, and science at the fourth grade. In M.O. Martin & I.V.S. Mullis (Eds.), TIMSS and PIRLS 2011: Relationships among reading, mathematics, and science achievement at the fourth grade—Implications for early learning. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Boston College.
  • Masten, A. S. (2014). Global perspectives on resilience in children and youth. Child Development, 85, 6–20.
  • Maxwell, S., Reynolds, K., Lee, E., Subasic, E., & Bromhead, D. (2017). The impact of school climate and school identification on academic achievement: Multilevel modeling with student and teacher data. Frontiers in Psychology, 8, 1-21.
  • McLafferty M., Mallet J., & McCauley V. (2012). Coping at university: The role of resilience, emotional intelligence, age and gender. Journal of Quantitative Psychological Research, 1, 1–6.
  • Mullis, I. V. S. (2017). Introduction. In Mullis, I. V. S., Martin, M. O. (Eds.). TIMSS 2019 assessment frameworks (pp. 1-10). Chestnut Hill, MA: TIMSS & PIRLS International Study Center at Boston College.
  • Mullis, I. V. S., Martin, M. O., Foy, P., Kelly, D. L., & Fishbein, B. (2020). TIMSS 2019 International Results in Mathematics and Science. Retrieved from Boston College, TIMSS & PIRLS International Study Center. Website: https://timssandpirls.bc.edu/timss2019/international-results/
  • Nilsen, T., Blömeke, S., Hansen, K. Y., & Gustafsson, J. E. (2016). Can schools contribute to enhance equity? The answer may depend on a country’s developmental level. IEA Policy Brief.
  • OECD. (2012). PISA 2012 Results: Excellence through Equity (Volume II): Giving Every Student the Chance to Succeed. Paris: OECD Publishing.
  • OECD. (2018). Equity in education: Breaking down barriers to social mobility. OECD Publishing.
  • Özer, Y., & Anıl, D. (2011). Examining the factors affecting students’ science and mathematics achievement with structural equation modeling. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 41(2011), 313,324.
  • Parker, J. D. A., Hogan, M. J., Eastabrook, J. M., Oke, A., & Wood, L. M. (2006). Emotional intelligence and student retention: Predicting the successful transition from high school to university. Personality and Individual Differences, 41, 1329-1336.
  • R Core Team (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL: https://www.R-project.org/.
  • Radisic, J., & Pettersen, A. (2020). Resilient and nonresilient students in Sweden and Norway—Investigating the interplay between their self-beliefs and the school environment. In T. S. Frones, A.
  • Pettersen, J. Radisic, N. Buchholtz (Eds.), Equity, equality and diversity in the Nordic model of education, Cham, Switzerland: Springer.
  • Reardon, S. F. (2011). The widening academic achievement gap between the rich and the poor: New evidence and possible explanations. In R. Murnane & G. Duncan (Eds.), Whither opportunity? Rising inequality in schools, and children’s life changes. Russel Sage Foundation Press.
  • Sander, P., & Sanders, L. (2009). Measuring academic behavioural confidence: The ABC scale revisited. Studies in Higher Education, 34(1), 19–35.
  • Sandoval-Hernandez, A., & Cortes, D. (2012). Factors and conditions that promote academic resilience: A cross-country perspective. Paper presented at the annual conference of the Comparative and International Education Society, Puerto Rico.
  • Sandoval-Hernandez, A., & Bialowolski, P. (2016). Factors and conditions promoting academic resilience: A TIMSS-based analysis of five Asian education systems. Asia Pacific Education Review, 17, 511–520.
  • Shin, J., Lee, H., & Kim, Y. (2009). Student and school factors affecting mathematics achievement: International comparisons between Korea, Japan, and the USA. School Psychology International, 30, 520–537.
  • Steenkamp, J. B. E., & Baumgartner, H. (1998). Assessing measurement invariance in cross national consumer research. Journal of Consumer Research 25(1), 78–90.
  • Sun, J., & Stewart, D. (2007). Age and gender effects on resilience in children and adolescents. International Journal of Mental Health Promotion, 9(4), 16–25.
  • Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (sixth edition). New Jersey: Pearson.
  • Uzun, S., Bütüner, S. O., & Yiğit, N. (2010). A comparison of the results of TIMSS 1999-2007: The most successful five countries-Turkey sample. Elementary Education Online, 9(3), 1174-1188.
  • Xie, C., & Ma, Y. (2019). The mediating role of cultural capital in the relationship between socio-economic status and student achievement in 14 economies. British Educational Research Journal, 45, 838–855.
  • Yayan, B., & Berberoğlu, G. (2004). A re-analysis of the TIMSS 1999 mathematics assessment data of the Turkish students. Studies in Educational Evaluation, 30(2004), 87-104.
Toplam 59 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Matematik Eğitimi
Bölüm Research Article
Yazarlar

Musa Sadak 0000-0001-6036-1279

Yayımlanma Tarihi 11 Ekim 2025
Gönderilme Tarihi 26 Mayıs 2025
Kabul Tarihi 10 Ekim 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 33 Sayı: 4

Kaynak Göster

APA Sadak, M. (2025). Factors Related to the Mathematics Achievement of Resilient and Nonresilient Students with Different Genders in Top Performing Asian Countries. Kastamonu Education Journal, 33(4), 716-725. https://doi.org/10.24106/kefdergi.1795686

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