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Eğitim Araştırmalarında Kanonik Korelasyon Analizinin Kullanımı: Türkiye Bağlamında Sistematik Bir İnceleme

Yıl 2025, Cilt: 4 Sayı: 2, 32 - 60, 29.12.2025
https://doi.org/10.58650/educatione.1802660

Öz

Kanonik korelasyon analizi (KKA), her biri iki veya daha fazla değişken içeren iki değişken kümesi arasındaki ilişkileri incelemek için kullanılabilen çok değişkenli bir istatistiksel tekniktir. Bu yöntem, Türkiye'deki çalışmalar da dahil olmak üzere eğitim araştırmalarında giderek daha fazla uygulanmaktadır. Bu çalışmanın amacı, Türkiye'de yürütülen eğitim araştırmalarında KKA'nın nasıl kullanıldığı ve raporlandığını incelemektir. Çalışma, sistematik bir inceleme yaklaşımı benimsemiş ve toplam 73 hakemli dergi makalesi incelenmiştir. Bulgular, eğitim araştırmalarında KKA'nın Türkiye'de 2005 yılında ilk kez kullanılmasından bu yana, özellikle fen eğitimi, rehberlik ve psikolojik danışmanlık, eğitim yönetimi ve eğitim ölçme alanlarında daha fazla ilgi gördüğünü ortaya koymuştur. Çalışmanın bulguları ayrıca, araştırmaların çoğunun KKA için geleneksel raporlama uygulamalarını izlediğini göstermiştir. Ancak, bazı araştırmaların KKA'nın tüm önemli varsayımlarını raporlamadığı veya sonuçlarının pratik önemini açıklamadığı tespit edilmiştir. KKA sonuçlarının birkaç yanlış yorumlanması ve geleneksel olmayan terminolojinin kullanılması da tespit edilmiştir. Sonuçlara dayanarak, bu çalışma eğitim araştırmalarında KKA'nın daha iyi kullanılması ve raporlanması için öneriler sunmakta ve araştırmacıların KKA'yı daha doğru ve net bir şekilde uygulamalarına yardımcı olacak basit bir kılavuz sağlamaktadır.

Etik Beyan

Bu çalışma, kamuya açık belgelerin analizini içerdiğinden ve insan denekleri kapsamadığından, etik onay gerekli değildir.

Kaynakça

  • Akaho, S. (2006). A kernel method for canonical correlation analysis. arXiv preprint cs/0609071.
  • Alpert, M. I., & Peterson, R. A. (1972). On the interpretation of canonical analysis. Journal of Marketing Research, 9(2), 187-192.
  • Andrew, G., Arora, R., Bilmes, J., & Livescu, K. (2013, May). Deep canonical correlation analysis. In International conference on machine learning (pp. 1247-1255). PMLR.
  • Arıkan, S., & D'Costa, A. (2016). ÖSS ve LES ile ölçülen sayısal ve sözel beceriler arasındaki ilişki [The relationship between quantitative and qualitative abilities of students in ÖSS and LES]. Mersin University Journal of the Faculty of Education, 12(1), 303-313. http://dx.doi.org/10.17860/efd.71302
  • Bayındır, D. (2023). The relation between cognitive processes and problem-solving performances of preschoolers. Journal of Theoretical Educational Science, 16(4), 887-902. http://doi.org/10.30831/akukeg.1342333
  • Boz, Y., & Boz, N. (2010). The nature of the relationship between teaching concerns and sense of efficacy. European Journal of Teacher Education, 33(3), 279-291. https://doi.org/10.1080/02619768.2010.490910
  • Capraro, R. M., & Capraro, M. M. (2001). Commonality analysis: Understanding variance contributions to overall canonical correlation effects of attitude toward mathematics on geometry achievement. General Linear Model Journal, 27(2), 16-23.
  • Çapa‐Aydın, Y., Sungur, S., & Uzuntiryaki, E. (2009). Teacher self‐regulation: Examining a multidimensional construct. Educational Psychology, 29(3), 345-356. https://doi.org/10.1080/01443410902927825
  • Çetin, B., İlhan, M., & Yılmaz, F. (2014). Olumsuz değerlendirilme korkusu ve akademik risk alma arasındaki ilişkinin kanonik korelasyonla incelenmesi [An investigation of the Relationship between the fear of receiving negative criticism and of taking academic risk through canonical correlation analysis]. Educational Sciences: Theory & Practice, 14(1), 135-158. https://doi.org/10.12738/estp.2014.1.1616
  • Doğan, N., & Sevindik, H. (2011). İlköğretim 6. sınıflar için uygulanan seviye belirleme sınavı’nın uygunluk geçerliği [Concurrent validity of proficiency examination for elementary school sixth grade students]. Education and Science, 36(160), 309-319.
  • Gittins, R. (1985). Canonical Analysis: A review with applications in ecology. Springer-Verlag.
  • Güven, G., & Kozcu Çakır, N. (2019). The relation between teachers' attitudes towards renewable energy sources and critical thinking dispositions. Journal of Baltic Science Education, 18(5), 717-731.
  • Güzeller, C. (2005). İlköğretim akademik başarı not ortalamaları ile OKÖSYS alt test puanları arasındaki uygunluk geçerliği çalışması [The concurrent validity between primary school academic success grades and OKÖSYS subtest grades]. Ahi Evran University Journal of Kırşehir Education Faculty, 6(2), 133-143.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective. Pearson.
  • Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28, 321-377.
  • Kan, A. (2005). ÖSS’ye kaynaklık eden alan derslerindeki başarı ile ÖSS’den elde edilen puanlar arasındaki ilişkinin incelenmesi [The relationship betweeıı studeııts’ acamedic grades and OSS scores]. Education and Science, 30(137), 38-44.
  • Karakaya, İ. (2011). Öğretmenlik programlarındaki öğrencilerin ÖSS puanları ile akademik başarıları arasındaki ilişkinin incelenmesi [Examining the relationship between students' öss scores and academic achievement in teacher training programs]. Journal of Measurement and Evaluation in Education and Psychology, 2(1), 155-163.
  • Kaya-Uyanik, G., Gur-Erdogan, D., & Canan-Gungoren, O. (2019). Examination of the relationship between prospective teachers’ occupational anxiety and technological pedagogical content knowledge by canonical correlation. International Journal of Educational Methodology, 5(3), 407-420. https://doi.org/10.12973/ijem.5.3.407
  • Kılıç, A. F. (2024). FAfA: Factor analysis for all An R package to conduct factor analysis with RShiny application. Journal of Measurement and Evaluation in Education and Psychology, 15(4), 446-451. https://doi.org/10.21031/epod.1555805
  • Kozcu Çakır, N. (2020). The relation between self-efficacy beliefs towards science teaching and learning strategies of primary school teacher candidates. International Journal of Research in Education and Science, 6(2), 347-360.
  • Nimon, K., Henson, R. K., & Gates, M. S. (2010). Revisiting interpretation of canonical correlation analysis: A tutorial and demonstration of canonical commonality analysis. Multivariate Behavioral Research, 45(4), 702-724. https://doi.org/10.1080/00273171.2010.498293
  • Nimon, K., & Reio Jr, T. G. (2011). The use of canonical commonality analysis for quantitative theory building. Human Resource Development Review, 10(4), 451-463. https://doi.org/10.1177/1534484311417682
  • Özdemir, B., & Gelbal, S. (2014). PISA 2009 sonuçlarına göre öğrenci başarısını etkileyen faktörlerin kanonik ortak etki analizi ile incelenmesi [Investigating factors that affect Turkish students’ academic success with canonical commonality analysis according to PISA 2009 results]. Education and Science, 39(175), 41-57.
  • Özdemir, B., & Seef, N. (2017). Examining the factors of self-compassion scale with canonical commonality analysis: Syrian sample. Eurasian Journal of Educational Research, 17(70), 19-36. http://dx.doi.org/10.14689/ejer.2017.70.2
  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
  • Parkhomenko, E., Tritchler, D., & Beyene, J. (2009). Sparse canonical correlation analysis with application to genomic data integration. Statistical Applications in Genetics and Molecular Biology, 8(1). https://doi.org/10.2202/1544-6115.1406
  • Pugh, R. C., & Hu, Y. (1991). Use and interpretation of canonical correlation analyses in Journal of Educational Research articles: 1978-1989. The Journal of Educational Research, 84(3), 147-152.
  • Sherry, A., & Henson, R. K. (2005). Conducting and interpreting canonical correlation analysis in personality research: A user-friendly primer. Journal of Personality Assessment, 84(1), 37-48. https://doi.org/10.1207/s15327752jpa8401_09
  • Stevens, J. P. (2009). Applied multivariate statistics for the social sciences. Taylor & Francis.
  • Stewart, D., & Love, W. (1968). A general canonical correlation index. Psychological Bulletin, 70(3), 160-163.
  • Tabachnick, B. G., & Fidell, L. S. (2006). Using multivariate statistics (5th ed.). Pearson.
  • Tekkaya, C., Akyol, G., & Sungur, S. (2012). Relationships among teachers’ knowledge and beliefs regarding the teaching of evolution: A case for Turkey. Evolution: Education and Outreach, 5, 477-493. https://doi.org/10.1007/s12052-012-0433-y
  • Totan, T. (2014). The canonical effect of task articulation, peer relations, and self-regulation based social and emotional learning needs to fields of self-efficacy. Education & Science, 39(171), 331-343.
  • Tuluk, G., & Kepceoglu, I. (2019). Pre-service teachers' web pedagogical content knowledge and online information searching strategies. International Journal of Evaluation and Research in Education, 8(2), 229-236. https://doi.org/10.11591/ijere.v8i2.18771
  • Uysal, İ., & Kılıç, A. F. (2022). Çok değişkenli normallik: Testler ne kadar doğru ne kadar güçlü [Multivariate normality: How accurate and how powerful are the tests]? İçinde F. Nayır & Ş. Poyrazlı (Ed.), Eğitim Bilimlerinde Güncel Araştırmalar. Anı.
  • Uzun, A., Özkılıç, R., & Şentürk, A. (2013). The perception of educational software development self-efficacy among undergraduate CEIT teacher candidates. Current Issues in Education, 16(2).
  • Van Der Burg, E., & de Leeuw, J. (1983). Non‐linear canonical correlation. British Journal of Mathematical and Statistical Psychology, 36(1), 54-80.
  • Weiss, D. J. (1972). Canonical correlation analysis in counseling psychology research. Journal of Counseling Psychology, 19(3), 241. https://psycnet.apa.org/doi/10.1037/h0032675
  • Wood, D. A., & Erskine, J. A. (1976). Strategies in canonical correlation with application to behavioral data. Educational and Psychological Measurement, 36(4), 861-878. https://doi.org/10.1177/001316447603600409
  • Wróbel, S., Turek, C., Stępień, E., & Piwowar, M. (2024). Data integration through canonical correlation analysis and its application to OMICs research. Journal of Biomedical Informatics, 151, 104575. https://doi.org/10.1016/j.jbi.2023.104575

The Use of Canonical Correlation Analysis in Educational Research: A Systematic Review of Turkish Context

Yıl 2025, Cilt: 4 Sayı: 2, 32 - 60, 29.12.2025
https://doi.org/10.58650/educatione.1802660

Öz

Canonical correlation analysis (CCA) is a multivariate statistical technique that can be used to explore the relationships between two sets of variables each containing two or more variables. This method has been increasingly applied in educational research, including studies from Türkiye. The purpose of this study is to examine how CCA has been used and reported in educational studies conducted in Türkiye. The study adopted a systematic review approach, and a total of 73 peer-reviewed journal articles were reviewed. The findings showed that CCA in educational studies has gained more attention in Türkiye since its first use in 2005, especially in the fields of science education, guidance and psychological counseling, educational administration, and educational measurement. The findings of the study also revealed that most of the studies followed the conventional reporting practices for CCA. However, it was found that some studies did not report all of the important assumptions of CCA or explain the practical significance of their results. A few misinterpretations of the CCA results and use of unconventional terminology were also detected. Based on the results, this review presents recommendations for better use and reporting of CCA in educational studies and provides a simple guideline to help researchers apply CCA more accurately and clearly.

Etik Beyan

As this study involved the analysis of publicly available documents and did not include human subjects, ethical approval was not necessary.

Kaynakça

  • Akaho, S. (2006). A kernel method for canonical correlation analysis. arXiv preprint cs/0609071.
  • Alpert, M. I., & Peterson, R. A. (1972). On the interpretation of canonical analysis. Journal of Marketing Research, 9(2), 187-192.
  • Andrew, G., Arora, R., Bilmes, J., & Livescu, K. (2013, May). Deep canonical correlation analysis. In International conference on machine learning (pp. 1247-1255). PMLR.
  • Arıkan, S., & D'Costa, A. (2016). ÖSS ve LES ile ölçülen sayısal ve sözel beceriler arasındaki ilişki [The relationship between quantitative and qualitative abilities of students in ÖSS and LES]. Mersin University Journal of the Faculty of Education, 12(1), 303-313. http://dx.doi.org/10.17860/efd.71302
  • Bayındır, D. (2023). The relation between cognitive processes and problem-solving performances of preschoolers. Journal of Theoretical Educational Science, 16(4), 887-902. http://doi.org/10.30831/akukeg.1342333
  • Boz, Y., & Boz, N. (2010). The nature of the relationship between teaching concerns and sense of efficacy. European Journal of Teacher Education, 33(3), 279-291. https://doi.org/10.1080/02619768.2010.490910
  • Capraro, R. M., & Capraro, M. M. (2001). Commonality analysis: Understanding variance contributions to overall canonical correlation effects of attitude toward mathematics on geometry achievement. General Linear Model Journal, 27(2), 16-23.
  • Çapa‐Aydın, Y., Sungur, S., & Uzuntiryaki, E. (2009). Teacher self‐regulation: Examining a multidimensional construct. Educational Psychology, 29(3), 345-356. https://doi.org/10.1080/01443410902927825
  • Çetin, B., İlhan, M., & Yılmaz, F. (2014). Olumsuz değerlendirilme korkusu ve akademik risk alma arasındaki ilişkinin kanonik korelasyonla incelenmesi [An investigation of the Relationship between the fear of receiving negative criticism and of taking academic risk through canonical correlation analysis]. Educational Sciences: Theory & Practice, 14(1), 135-158. https://doi.org/10.12738/estp.2014.1.1616
  • Doğan, N., & Sevindik, H. (2011). İlköğretim 6. sınıflar için uygulanan seviye belirleme sınavı’nın uygunluk geçerliği [Concurrent validity of proficiency examination for elementary school sixth grade students]. Education and Science, 36(160), 309-319.
  • Gittins, R. (1985). Canonical Analysis: A review with applications in ecology. Springer-Verlag.
  • Güven, G., & Kozcu Çakır, N. (2019). The relation between teachers' attitudes towards renewable energy sources and critical thinking dispositions. Journal of Baltic Science Education, 18(5), 717-731.
  • Güzeller, C. (2005). İlköğretim akademik başarı not ortalamaları ile OKÖSYS alt test puanları arasındaki uygunluk geçerliği çalışması [The concurrent validity between primary school academic success grades and OKÖSYS subtest grades]. Ahi Evran University Journal of Kırşehir Education Faculty, 6(2), 133-143.
  • Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis: A global perspective. Pearson.
  • Hotelling, H. (1936). Relations between two sets of variates. Biometrika, 28, 321-377.
  • Kan, A. (2005). ÖSS’ye kaynaklık eden alan derslerindeki başarı ile ÖSS’den elde edilen puanlar arasındaki ilişkinin incelenmesi [The relationship betweeıı studeııts’ acamedic grades and OSS scores]. Education and Science, 30(137), 38-44.
  • Karakaya, İ. (2011). Öğretmenlik programlarındaki öğrencilerin ÖSS puanları ile akademik başarıları arasındaki ilişkinin incelenmesi [Examining the relationship between students' öss scores and academic achievement in teacher training programs]. Journal of Measurement and Evaluation in Education and Psychology, 2(1), 155-163.
  • Kaya-Uyanik, G., Gur-Erdogan, D., & Canan-Gungoren, O. (2019). Examination of the relationship between prospective teachers’ occupational anxiety and technological pedagogical content knowledge by canonical correlation. International Journal of Educational Methodology, 5(3), 407-420. https://doi.org/10.12973/ijem.5.3.407
  • Kılıç, A. F. (2024). FAfA: Factor analysis for all An R package to conduct factor analysis with RShiny application. Journal of Measurement and Evaluation in Education and Psychology, 15(4), 446-451. https://doi.org/10.21031/epod.1555805
  • Kozcu Çakır, N. (2020). The relation between self-efficacy beliefs towards science teaching and learning strategies of primary school teacher candidates. International Journal of Research in Education and Science, 6(2), 347-360.
  • Nimon, K., Henson, R. K., & Gates, M. S. (2010). Revisiting interpretation of canonical correlation analysis: A tutorial and demonstration of canonical commonality analysis. Multivariate Behavioral Research, 45(4), 702-724. https://doi.org/10.1080/00273171.2010.498293
  • Nimon, K., & Reio Jr, T. G. (2011). The use of canonical commonality analysis for quantitative theory building. Human Resource Development Review, 10(4), 451-463. https://doi.org/10.1177/1534484311417682
  • Özdemir, B., & Gelbal, S. (2014). PISA 2009 sonuçlarına göre öğrenci başarısını etkileyen faktörlerin kanonik ortak etki analizi ile incelenmesi [Investigating factors that affect Turkish students’ academic success with canonical commonality analysis according to PISA 2009 results]. Education and Science, 39(175), 41-57.
  • Özdemir, B., & Seef, N. (2017). Examining the factors of self-compassion scale with canonical commonality analysis: Syrian sample. Eurasian Journal of Educational Research, 17(70), 19-36. http://dx.doi.org/10.14689/ejer.2017.70.2
  • Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., ... & Moher, D. (2021). The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
  • Parkhomenko, E., Tritchler, D., & Beyene, J. (2009). Sparse canonical correlation analysis with application to genomic data integration. Statistical Applications in Genetics and Molecular Biology, 8(1). https://doi.org/10.2202/1544-6115.1406
  • Pugh, R. C., & Hu, Y. (1991). Use and interpretation of canonical correlation analyses in Journal of Educational Research articles: 1978-1989. The Journal of Educational Research, 84(3), 147-152.
  • Sherry, A., & Henson, R. K. (2005). Conducting and interpreting canonical correlation analysis in personality research: A user-friendly primer. Journal of Personality Assessment, 84(1), 37-48. https://doi.org/10.1207/s15327752jpa8401_09
  • Stevens, J. P. (2009). Applied multivariate statistics for the social sciences. Taylor & Francis.
  • Stewart, D., & Love, W. (1968). A general canonical correlation index. Psychological Bulletin, 70(3), 160-163.
  • Tabachnick, B. G., & Fidell, L. S. (2006). Using multivariate statistics (5th ed.). Pearson.
  • Tekkaya, C., Akyol, G., & Sungur, S. (2012). Relationships among teachers’ knowledge and beliefs regarding the teaching of evolution: A case for Turkey. Evolution: Education and Outreach, 5, 477-493. https://doi.org/10.1007/s12052-012-0433-y
  • Totan, T. (2014). The canonical effect of task articulation, peer relations, and self-regulation based social and emotional learning needs to fields of self-efficacy. Education & Science, 39(171), 331-343.
  • Tuluk, G., & Kepceoglu, I. (2019). Pre-service teachers' web pedagogical content knowledge and online information searching strategies. International Journal of Evaluation and Research in Education, 8(2), 229-236. https://doi.org/10.11591/ijere.v8i2.18771
  • Uysal, İ., & Kılıç, A. F. (2022). Çok değişkenli normallik: Testler ne kadar doğru ne kadar güçlü [Multivariate normality: How accurate and how powerful are the tests]? İçinde F. Nayır & Ş. Poyrazlı (Ed.), Eğitim Bilimlerinde Güncel Araştırmalar. Anı.
  • Uzun, A., Özkılıç, R., & Şentürk, A. (2013). The perception of educational software development self-efficacy among undergraduate CEIT teacher candidates. Current Issues in Education, 16(2).
  • Van Der Burg, E., & de Leeuw, J. (1983). Non‐linear canonical correlation. British Journal of Mathematical and Statistical Psychology, 36(1), 54-80.
  • Weiss, D. J. (1972). Canonical correlation analysis in counseling psychology research. Journal of Counseling Psychology, 19(3), 241. https://psycnet.apa.org/doi/10.1037/h0032675
  • Wood, D. A., & Erskine, J. A. (1976). Strategies in canonical correlation with application to behavioral data. Educational and Psychological Measurement, 36(4), 861-878. https://doi.org/10.1177/001316447603600409
  • Wróbel, S., Turek, C., Stępień, E., & Piwowar, M. (2024). Data integration through canonical correlation analysis and its application to OMICs research. Journal of Biomedical Informatics, 151, 104575. https://doi.org/10.1016/j.jbi.2023.104575
Toplam 40 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Eğitimde Ölçme ve Değerlendirme (Diğer)
Bölüm Araştırma Makalesi
Yazarlar

Ali Temurtaş 0000-0002-4657-0469

Gönderilme Tarihi 13 Ekim 2025
Kabul Tarihi 24 Kasım 2025
Yayımlanma Tarihi 29 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 4 Sayı: 2

Kaynak Göster

APA Temurtaş, A. (2025). The Use of Canonical Correlation Analysis in Educational Research: A Systematic Review of Turkish Context. EDUCATIONE, 4(2), 32-60. https://doi.org/10.58650/educatione.1802660