Araştırma Makalesi
BibTex RIS Kaynak Göster

Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma

Yıl 2023, Cilt: 43 Sayı: 3, 1623 - 1643, 30.12.2023
https://doi.org/10.17152/gefad.1352037

Öz

Bu çalışmada TIMSS 2019 8. Sınıf Türkiye verisi için matematiğe yönelik tutum ve matematik başarısı arasındaki ilişkiyi incelemek ve bireylerin matematiğe yönelik tutum profillerini belirleyerek, bu profillere göre matematik başarısındaki farklılıkların tespit edilmesi amaçlanmıştır. Örtük Profil Analizi ile gerçekleştirilen analizler sonucunda dört tutum profili belirlenmiştir. Birinci profil (n = 304, %0.08), matematik dersine karşı çok olumsuz tutuma sahip grubu; ikinci profil (n = 1882, %47) matematiğe olumsuz tutuma sahip grubu, üçüncü profil (n = 1290, %33) tarafsız tutuma sahip olan grubu, dördüncü grup (n = 456, %12) olumlu tutuma sahip olan grup olarak adlandırılmıştır. Ayrıca öğrencilerin matematiğe karşı tutumları, 'matematiği sevmek', 'matematiğe değer vermek' ve 'matematiğe güven'den oluşan çok boyutlu bütünleşik bir yapı olarak tanımlayan literatürle benzer sonuçlar elde edilmiştir. Elde edilen profillere göre matematik başarı farklılıkları test edilmiş ve kovaryant değişkenler eklenerek profiller hakkında ayrıntılı bilgiler elde edilmiştir. Eğitimcilerin ve yöneticilerin öğrencilerin matematiğe yönelik olumlu tutuma sahip olmalarına katkı sağlayacak eğitim ve program faaliyetlerinin yapılması önerilmiştir.

Kaynakça

  • Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52(3), 317-332. https://doi.org/10.1007/BF02294359
  • Arslan, C., Yavuz, G., & Deringol-Karatas, Y. (2014). Attitudes of elementary school students towards solving mathematics problems. Procedia-Social and Behavioral Sciences, 152, 557-562. https://doi.org/ 10.1016/j.sbspro.2014.09.243
  • Asparouhov, T., & Muth´en, B. (2014). Auxiliary variables in mixture modeling: Three-step approaches using Mplus. Structural Equation Modeling: A Multidisciplinary Journal, 21(3), 329–341. https://doi.org/10.1080/10705511.2014.915181
  • Bakk, Z., Tekle, F. B., & Vermunt, J. K. (2013). Estimating the association between latent class membership and external variables using bias-adjusted three-step approaches. Sociological methodology, 43(1), 272-311. https://doi.org/10.1177/0081175012470644.
  • Bakk, Z., & Vermunt, J. K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural equation modeling: a multidisciplinary journal, 23(1), 20-31. https://doi.org/10.1080/10705511.2014.955104.
  • Bayaga, A., & Wadesango, N. (2014). Analysis of students’ attitudes on mathematics achievement-factor structure approach. International Journal of Educational Sciences, 6(1), 45-50. https://doi.org/ 10.1080/09751122.2014.11890116
  • Berger, N., Mackenzie, E., & Holmes, K. (2020). Positive attitudes towards mathematics and science are mutually beneficial for student achievement: A latent profile analysis of TIMSS 2015. The Australian Educational Researche, 47, 409–444. https://doi.org/10.1007/s13384-020-00379-8.
  • Byrnes, J. P., & Wasik, B. A. (2009). Factors predictive of mathematics achievement in kindergarten, first and third grades: An opportunity–propensity analysis. Contemporary Educational Psychology, 34(2), 167–183. https://doi.org/10.1016/j.cedpsych.2009.01.002.
  • Chen, L., Bae, S. R., Battista, C., Qin, S., Chen, T., Evans, T. M., & Menon, V. (2018). Positive attitude toward math supports early academic success: Behavioral evidence and neurocognitive mechanisms. Psychological Science, 29(3), 390–402. https://doi.org/10.1177/0956797617735528.
  • Chouinard, R., Karsenti, T., & Roy, N. (2007). Relations among competence beliefs, utility value, achievement goals, and effort in mathematics. British Journal of Educational Psychology, 77(3), 501–517. https://doi.org/10.1348/000709906x133589
  • Davadas, S. D., & Lay, Y. F. (2020). Contributing factors of secondary students’ attitude towards mathematics. European Journal of Educational Research, 9(2), 489-498. https://doi.org/10.12973/ eu-jer.9.2.489
  • Demirkıran, F., Elalmış, S., & Doğan, E. E. (2023). Matematik Dersine Yönelik Tutum ile Başarı Arasındaki İlişki: Bir TIMSS Çalışması. Edebiyat Dilbilim Eğitim ve Bilimsel Araştırmalar Dergisi, 2(1), 145-157.
  • Di Martino, P., & Zan, R. (2011). Attitude towards Mathematics: A bridge between beliefs and emotions. ZDM-International Journal on Mathematics Education, 43(4), 471-482. https://doi.org/10.1007/ s11858-011-0309-6
  • Dowker, A., Cheriton, O., Horton, R., & Mark, W. (2019). Relationships between attitudes and performance in young children’s mathematics. Educational Studies in Mathematics, 100(3), 211–230. https://doi.org/10.1007/s10649-019-9880-5.
  • Ferguson, S.L., Moore, E.W., & Hull, D.M. (2020). Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers. International Journal of Behavioral Development, 44(5), 458-468. https://doi.org/10.1177/0165025419881721
  • Hwang, S., & Son, T. (2021). Students' Attitude toward Mathematics and Its Relationship with Mathematics Achievement. Journal of Education and e-Learning Research, 8(3), 272-280.
  • Gardner, P. L. (1975). Attitudes to science: A review. Studies in Science Education, 2(1), 1-41. https://doi.org/10.1080/03057267508559818
  • Jung, T., & Wickrama, K. A. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2(1), 302–317. https://doi.org/10.1111/j.1751-9004.2007.00054.x.
  • Kadijevich, D. J. (2008). TIMSS 2003: Relating dimensions of mathematics attitude to mathematics achievement. Proceedings of the Institute for Pedagogical Research, 40(2), 327–346. https://doi.org/10.2298/ZIPI0802327K
  • Kiwanuka, H. N., Van Damme, J., Van den Noortgate, W., & Reynolds, C. (2020). Temporal relationship between attitude toward mathematics and mathematics achievement. International Journal of Mathematical Education in Science and Technology, 51, 1–25. https://doi.org/10.1080/0020739x.2020.1832268.
  • Lee, Y., & Yoo, S. (2020). Individual profiles and team classes of the climate for creativity: A multilevel latent profile analysis. Creativity and Innovation Management, 29(3), 438–452. https://doi.org/10.1111/caim.12371
  • Lin, S., & Huang, Y. (2014). Development and application of a Chinese version of the short attitudes toward mathematics inventory. International Journal of Science and Mathematics Education, 14(1), 193-216. https://doi.org/10.1007/ s10763-014-9563-8
  • Lo, Y., Mendell, N.R., & Rubin, D.B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767-778. https://doi.org/10.1093/biomet/88.3.767
  • Ma, X., & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal for Research in Mathematics Education, 28, 26–47. https://doi.org/10.2307/749662.
  • Ma, Y. (2022). Profiles of student science attitudes and its associations with gender and science achievement. International Journal of Science Education, 44(11), 1876-1895.
  • Marsh, H.W., Ludtke, O., Trautwein, U., & Morin, A.J. (2009). Classical latent profile analysis of academic self-concept dimensions: Synergy of person-and variable-centered approaches to theoretical models of self-concept. Structural Equation Modeling, 16, 191-225. https://doi.org/0.1080/10705510902751010
  • Martin, M. O., Von Davier, M., & Mullis, I. V. (2020). Methods and procedures: TIMSS 2019 technical report. Paper presented at the TIMSS & PIRLS International Association for the Evaluation of Educational Achievement.
  • Masyn, K.E. (2013). Latent class analysis and finite mixture modeling. In T.L. (Eds.), The Oxford handbook of quantitative methods (pp. 551-611). Oxford University.
  • Mazana, M. Y., Montero, C. S., & Casmir, R. O. (2018). Investigating students’ attitude towards learning mathematics. International Electronic Journal of Mathematics Education, 14(1). https://doi.org/10. 29333/iejme/3997
  • Mubeen, S., Saeed, S., & Arif, M. H. (2013). Attitude towards mathematics and academic achievement in mathematics among secondary level boys and girls. Journal of Humanities and Social Science, 6(4), 38–41. https://doi.org/10.9790/0837-0643841.
  • 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/
  • Muthén, L.K., & Muthén, B.O. (1998-2017). Mplus user’s guide (8th Edition). Muthén & Muthén.
  • Nylund, K.L., Asparouhov, T., & Muthén, B.O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14(4), 535-569. https://doi.org/10.1080/10705510701575396
  • Nylund-Gibson, K., & Masyn, K.E. (2016). Covariates and mixture modeling: Results of a simulation study exploring the impact of misspecified effects on class enumeration. Structural Equation Modeling, 23, 782-797. https://doi.org/10.1080/10705511.2016.1221313
  • Pepin, B. (2011). Pupils’ attitudes towards mathematics: A comparative study of Norwegian and English secondary students. ZDM-International Journal on Mathematics Education, 43(4), 535-546. https://doi.org/10.1007/s11858-011-0314-9
  • Perloff, R. M. (2016). The dynamics of Persuasion: Communication and attitudes in the twenty-first century. Routledge
  • Radisic, J., Videnovic, M., & Baucal, A. (2018). Distinguishing successful students in mathematics – A comparisonacross European countries. Psihologija, 51(1), 69–89. https://doi.org/10.2298/PSI170522019R
  • Sunghwan, H., & Taekwon, S. (2021). Students’ attitude toward mathematics and its relationship with mathematics achievement. Journal of Education and e-Learning Research, 8(3), 272-280. https://doi.org/ 10.20448/journal.509.2021.83.272.280
  • Tabuk, M. (2019). Matematiğe ilişkin tutum ile matematik başarısı arasındaki ilişki üzerine bir meta-analiz çalışması. Marmara Üniversitesi Atatürk Eğitim Fakültesi Eğitim Bilimleri Dergisi, 49, 167-186.
  • Tein, J. Y., Coxe, S., & Cham, H. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling, 20(4), 640-657. https://doi.org/10.1080/10705511.2013.824781.
  • Tueller, S., & Lubke, G. (2010). Evaluation of structural equation mixture models: Parameter estimates and correct class assignment. Structural Equation Modeling, 17(2), 165-192. https://doi.org/10.1080/10705511003659318.
  • Utsumi, M. C., & Mendes, C. R. (2000). Researching the attitudes towards mathematics in basic education. Educational Psychology, 20(2), 237-243. https://doi.org/10.1080/713663712
  • Zhao, Q., Wininger, S., & Hendricks, J. (2022). The interactive effects of gender and implicit theories of abilitieson mathematics and science achievements.The Australian Educational Researcher,49(1), 115–133.https://doi.org/10.1007/s13384-021-00430-2

A Study on Determining Students' Mathematical Attitude Profiles by Latent Profile Analysis

Yıl 2023, Cilt: 43 Sayı: 3, 1623 - 1643, 30.12.2023
https://doi.org/10.17152/gefad.1352037

Öz

In this study, it was aimed to examine the relationship between attitudes towards mathematics and mathematics achievement for TIMSS 2019 8th grade Turkey data and to determine the differences in mathematics achievement according to these profiles by determining the attitudes profiles of individuals towards mathematics. As a result of the analyses carried out with the Latent Profile Analysis, four attitude profiles were determined. The first profile (n = 304, 0.08%) was the group with a very negative attitude towards mathematics; second profile (n = 1882, 47%) group with negative attitude towards mathematics, third profile (n = 1290, 33%) group with neutral attitude, fourth group (n = 456, 12%) with positive attitude. In addition, similar results were obtained with the literature describing students' attitudes towards mathematics as a multidimensional integrated structure consisting of 'Liking Mathematics', 'valuing mathematics' and ‘Confident in Mathematics’. Mathematical achievement differences were tested according to the profiles obtained, and detailed information about the profiles was obtained by adding covariant variables. It is suggested that educators and administrators carry out educational and program activities that will contribute to students' positive attitudes towards mathematics.

Kaynakça

  • Akaike, H. (1987). Factor analysis and AIC. Psychometrika, 52(3), 317-332. https://doi.org/10.1007/BF02294359
  • Arslan, C., Yavuz, G., & Deringol-Karatas, Y. (2014). Attitudes of elementary school students towards solving mathematics problems. Procedia-Social and Behavioral Sciences, 152, 557-562. https://doi.org/ 10.1016/j.sbspro.2014.09.243
  • Asparouhov, T., & Muth´en, B. (2014). Auxiliary variables in mixture modeling: Three-step approaches using Mplus. Structural Equation Modeling: A Multidisciplinary Journal, 21(3), 329–341. https://doi.org/10.1080/10705511.2014.915181
  • Bakk, Z., Tekle, F. B., & Vermunt, J. K. (2013). Estimating the association between latent class membership and external variables using bias-adjusted three-step approaches. Sociological methodology, 43(1), 272-311. https://doi.org/10.1177/0081175012470644.
  • Bakk, Z., & Vermunt, J. K. (2016). Robustness of stepwise latent class modeling with continuous distal outcomes. Structural equation modeling: a multidisciplinary journal, 23(1), 20-31. https://doi.org/10.1080/10705511.2014.955104.
  • Bayaga, A., & Wadesango, N. (2014). Analysis of students’ attitudes on mathematics achievement-factor structure approach. International Journal of Educational Sciences, 6(1), 45-50. https://doi.org/ 10.1080/09751122.2014.11890116
  • Berger, N., Mackenzie, E., & Holmes, K. (2020). Positive attitudes towards mathematics and science are mutually beneficial for student achievement: A latent profile analysis of TIMSS 2015. The Australian Educational Researche, 47, 409–444. https://doi.org/10.1007/s13384-020-00379-8.
  • Byrnes, J. P., & Wasik, B. A. (2009). Factors predictive of mathematics achievement in kindergarten, first and third grades: An opportunity–propensity analysis. Contemporary Educational Psychology, 34(2), 167–183. https://doi.org/10.1016/j.cedpsych.2009.01.002.
  • Chen, L., Bae, S. R., Battista, C., Qin, S., Chen, T., Evans, T. M., & Menon, V. (2018). Positive attitude toward math supports early academic success: Behavioral evidence and neurocognitive mechanisms. Psychological Science, 29(3), 390–402. https://doi.org/10.1177/0956797617735528.
  • Chouinard, R., Karsenti, T., & Roy, N. (2007). Relations among competence beliefs, utility value, achievement goals, and effort in mathematics. British Journal of Educational Psychology, 77(3), 501–517. https://doi.org/10.1348/000709906x133589
  • Davadas, S. D., & Lay, Y. F. (2020). Contributing factors of secondary students’ attitude towards mathematics. European Journal of Educational Research, 9(2), 489-498. https://doi.org/10.12973/ eu-jer.9.2.489
  • Demirkıran, F., Elalmış, S., & Doğan, E. E. (2023). Matematik Dersine Yönelik Tutum ile Başarı Arasındaki İlişki: Bir TIMSS Çalışması. Edebiyat Dilbilim Eğitim ve Bilimsel Araştırmalar Dergisi, 2(1), 145-157.
  • Di Martino, P., & Zan, R. (2011). Attitude towards Mathematics: A bridge between beliefs and emotions. ZDM-International Journal on Mathematics Education, 43(4), 471-482. https://doi.org/10.1007/ s11858-011-0309-6
  • Dowker, A., Cheriton, O., Horton, R., & Mark, W. (2019). Relationships between attitudes and performance in young children’s mathematics. Educational Studies in Mathematics, 100(3), 211–230. https://doi.org/10.1007/s10649-019-9880-5.
  • Ferguson, S.L., Moore, E.W., & Hull, D.M. (2020). Finding latent groups in observed data: A primer on latent profile analysis in Mplus for applied researchers. International Journal of Behavioral Development, 44(5), 458-468. https://doi.org/10.1177/0165025419881721
  • Hwang, S., & Son, T. (2021). Students' Attitude toward Mathematics and Its Relationship with Mathematics Achievement. Journal of Education and e-Learning Research, 8(3), 272-280.
  • Gardner, P. L. (1975). Attitudes to science: A review. Studies in Science Education, 2(1), 1-41. https://doi.org/10.1080/03057267508559818
  • Jung, T., & Wickrama, K. A. (2008). An introduction to latent class growth analysis and growth mixture modeling. Social and Personality Psychology Compass, 2(1), 302–317. https://doi.org/10.1111/j.1751-9004.2007.00054.x.
  • Kadijevich, D. J. (2008). TIMSS 2003: Relating dimensions of mathematics attitude to mathematics achievement. Proceedings of the Institute for Pedagogical Research, 40(2), 327–346. https://doi.org/10.2298/ZIPI0802327K
  • Kiwanuka, H. N., Van Damme, J., Van den Noortgate, W., & Reynolds, C. (2020). Temporal relationship between attitude toward mathematics and mathematics achievement. International Journal of Mathematical Education in Science and Technology, 51, 1–25. https://doi.org/10.1080/0020739x.2020.1832268.
  • Lee, Y., & Yoo, S. (2020). Individual profiles and team classes of the climate for creativity: A multilevel latent profile analysis. Creativity and Innovation Management, 29(3), 438–452. https://doi.org/10.1111/caim.12371
  • Lin, S., & Huang, Y. (2014). Development and application of a Chinese version of the short attitudes toward mathematics inventory. International Journal of Science and Mathematics Education, 14(1), 193-216. https://doi.org/10.1007/ s10763-014-9563-8
  • Lo, Y., Mendell, N.R., & Rubin, D.B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767-778. https://doi.org/10.1093/biomet/88.3.767
  • Ma, X., & Kishor, N. (1997). Assessing the relationship between attitude toward mathematics and achievement in mathematics: A meta-analysis. Journal for Research in Mathematics Education, 28, 26–47. https://doi.org/10.2307/749662.
  • Ma, Y. (2022). Profiles of student science attitudes and its associations with gender and science achievement. International Journal of Science Education, 44(11), 1876-1895.
  • Marsh, H.W., Ludtke, O., Trautwein, U., & Morin, A.J. (2009). Classical latent profile analysis of academic self-concept dimensions: Synergy of person-and variable-centered approaches to theoretical models of self-concept. Structural Equation Modeling, 16, 191-225. https://doi.org/0.1080/10705510902751010
  • Martin, M. O., Von Davier, M., & Mullis, I. V. (2020). Methods and procedures: TIMSS 2019 technical report. Paper presented at the TIMSS & PIRLS International Association for the Evaluation of Educational Achievement.
  • Masyn, K.E. (2013). Latent class analysis and finite mixture modeling. In T.L. (Eds.), The Oxford handbook of quantitative methods (pp. 551-611). Oxford University.
  • Mazana, M. Y., Montero, C. S., & Casmir, R. O. (2018). Investigating students’ attitude towards learning mathematics. International Electronic Journal of Mathematics Education, 14(1). https://doi.org/10. 29333/iejme/3997
  • Mubeen, S., Saeed, S., & Arif, M. H. (2013). Attitude towards mathematics and academic achievement in mathematics among secondary level boys and girls. Journal of Humanities and Social Science, 6(4), 38–41. https://doi.org/10.9790/0837-0643841.
  • 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/
  • Muthén, L.K., & Muthén, B.O. (1998-2017). Mplus user’s guide (8th Edition). Muthén & Muthén.
  • Nylund, K.L., Asparouhov, T., & Muthén, B.O. (2007). Deciding on the number of classes in latent class analysis and growth mixture modeling: A Monte Carlo simulation study. Structural Equation Modeling: A Multidisciplinary Journal, 14(4), 535-569. https://doi.org/10.1080/10705510701575396
  • Nylund-Gibson, K., & Masyn, K.E. (2016). Covariates and mixture modeling: Results of a simulation study exploring the impact of misspecified effects on class enumeration. Structural Equation Modeling, 23, 782-797. https://doi.org/10.1080/10705511.2016.1221313
  • Pepin, B. (2011). Pupils’ attitudes towards mathematics: A comparative study of Norwegian and English secondary students. ZDM-International Journal on Mathematics Education, 43(4), 535-546. https://doi.org/10.1007/s11858-011-0314-9
  • Perloff, R. M. (2016). The dynamics of Persuasion: Communication and attitudes in the twenty-first century. Routledge
  • Radisic, J., Videnovic, M., & Baucal, A. (2018). Distinguishing successful students in mathematics – A comparisonacross European countries. Psihologija, 51(1), 69–89. https://doi.org/10.2298/PSI170522019R
  • Sunghwan, H., & Taekwon, S. (2021). Students’ attitude toward mathematics and its relationship with mathematics achievement. Journal of Education and e-Learning Research, 8(3), 272-280. https://doi.org/ 10.20448/journal.509.2021.83.272.280
  • Tabuk, M. (2019). Matematiğe ilişkin tutum ile matematik başarısı arasındaki ilişki üzerine bir meta-analiz çalışması. Marmara Üniversitesi Atatürk Eğitim Fakültesi Eğitim Bilimleri Dergisi, 49, 167-186.
  • Tein, J. Y., Coxe, S., & Cham, H. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling, 20(4), 640-657. https://doi.org/10.1080/10705511.2013.824781.
  • Tueller, S., & Lubke, G. (2010). Evaluation of structural equation mixture models: Parameter estimates and correct class assignment. Structural Equation Modeling, 17(2), 165-192. https://doi.org/10.1080/10705511003659318.
  • Utsumi, M. C., & Mendes, C. R. (2000). Researching the attitudes towards mathematics in basic education. Educational Psychology, 20(2), 237-243. https://doi.org/10.1080/713663712
  • Zhao, Q., Wininger, S., & Hendricks, J. (2022). The interactive effects of gender and implicit theories of abilitieson mathematics and science achievements.The Australian Educational Researcher,49(1), 115–133.https://doi.org/10.1007/s13384-021-00430-2

Ayrıntılar

Birincil Dil Türkçe
Konular Eğitimde Ölçme ve Değerlendirme (Diğer)
Bölüm Makaleler
Yazarlar

Fatıma Münevver SAATÇİOĞLU 0000-0003-4797-207X

Yayımlanma Tarihi 30 Aralık 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 43 Sayı: 3

Kaynak Göster

APA SAATÇİOĞLU, F. M. (2023). Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi, 43(3), 1623-1643. https://doi.org/10.17152/gefad.1352037
AMA SAATÇİOĞLU FM. Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma. GEFAD. Aralık 2023;43(3):1623-1643. doi:10.17152/gefad.1352037
Chicago SAATÇİOĞLU, Fatıma Münevver. “Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma”. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi 43, sy. 3 (Aralık 2023): 1623-43. https://doi.org/10.17152/gefad.1352037.
EndNote SAATÇİOĞLU FM (01 Aralık 2023) Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi 43 3 1623–1643.
IEEE F. M. SAATÇİOĞLU, “Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma”, GEFAD, c. 43, sy. 3, ss. 1623–1643, 2023, doi: 10.17152/gefad.1352037.
ISNAD SAATÇİOĞLU, Fatıma Münevver. “Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma”. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi 43/3 (Aralık 2023), 1623-1643. https://doi.org/10.17152/gefad.1352037.
JAMA SAATÇİOĞLU FM. Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma. GEFAD. 2023;43:1623–1643.
MLA SAATÇİOĞLU, Fatıma Münevver. “Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma”. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi, c. 43, sy. 3, 2023, ss. 1623-4, doi:10.17152/gefad.1352037.
Vancouver SAATÇİOĞLU FM. Örtük Profil Analizi İle Öğrencilerin Matematik Tutum Profillerinin Belirlenmesi Üzerine Bir Araştırma. GEFAD. 2023;43(3):1623-4.