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Investigating Factors Affecting Scientific Literacy with Structural Equation Modeling and Multilevel Structural Equation Modeling: Case of PISA 2015

Year 2022, Volume: 51 Issue: 2, 795 - 824, 31.08.2022
https://doi.org/10.14812/cuefd.933101

Abstract

There is no empirical evidence in the literature regarding the problems encountered in the use of single-level analyzes on hierarchical data and the implementation of a single-multilevel structural equation model. In this study, the models were created by using Structural Equation Modeling and Multilevel Structural Equation Modeling for the effects of factors such as enjoyment in learning science, instrumental motivation, scientific self-efficacy, hinderances in education, and hinderance to learning which are claimed to predict Turkish students’ science performance who participated PISA 2015. The effects of the predictive variables were estimated with two different single-level models constructed by aggregating and disaggregating the data. Then, single-level models are compared with the two-level model in terms of model fit and standardized parameters. As a result, since it was observed that standard error in regression coefficients decreased for the model which disregarded group levels, and variance-within-groups was not included in the model which disregarded individual levels which caused a data loss, the results were biased, and the effectiveness of the statistical test was weakened. In light of the results of this study, some recommendations were suggested for future studies which may consider dealing with analyzing hierarchical data.

References

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Fen Okuryazarlığını Etkileyen Faktörlerin Tek ve Çok Düzeyli Yapısal Eşitlik Modeli ile İncelenmesi: PISA 2015 Örneği

Year 2022, Volume: 51 Issue: 2, 795 - 824, 31.08.2022
https://doi.org/10.14812/cuefd.933101

Abstract

Hiyerarşik veriler üzerinde tek düzeyli analizlerin kullanımı ile tek ve çok düzeyli yapısal eşitlik modelinin uygulanmasında karşılaşılan sorunlara ilişkin literatürde ampirik bir kanıt bulunmamaktadır. Bu çalışmada, Türkiye’de PISA 2015 uygulamasına katılmış bireylerin fen başarısını yordadığı düşünülen fen öğrenmekten zevk alma, fen öğreniminde araçsal güdülenme, fen öz yeterliği, eğitim sürecindeki engeller, öğrenme engeli değişkenlerinin etkisi tek düzeyli ve çok düzeyli yapısal eşitlik ile modellenmiştir. Yordayıcı değişkenlerin etkileri, verilerin toplanması ve ayrıştırılması ile oluşturulan iki tek düzeyli model ile kestirilmiş ve model uyumu ile standartlaştırılmış parametreler açısından iki düzeyli model ile karşılaştırılmıştır. Sonuç olarak grup düzeyi göz ardı edilen modelde regresyon katsayılarına ait standart hataların azalmasından, birey düzeyi göz ardı edilen modelde ise grup içi varyans analize dâhil edilmediğinden ve veri kaybı yaşanmasından dolayı yanlı sonuçlar elde edilmiş ve istatiksel testin gücünü azaltmıştır. Bu sonuçların, gelecekte hiyerarşik verilerde yapılacak çalışmalarda kullanılacak analizler için araştırmacılara fikir sunması beklenmektedir. 

References

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  • Acosta, S. T. & Hsu, H. Y. (2014). Negotiating diversity: An empirical investigation into family, school and student factors influencing New Zealand adolescents’ science literacy. Educational Studies, 40(1), 98-115.https://doi.org/10.1080/03055698.2013.830243
  • Aktamış, H., Kiremit, H. Ö., & Kubilay, M. (2016). Öğrencilerin öz-yeterlik inançlarının fen başarılarına ve demografik özelliklerine göre incelenmesi. Adnan Menderes Üniversitesi Eğitim Fakültesi Eğitim Bilimleri Dergisi, 7(2), 1-10.
  • Al Şensoy, S., & Sağsöz, A. (2015). Öğrenci başarısının sınıfların fiziksel koşulları ile ilişkisi. Kırşehir Eğitim Fakültesi Dergisi, 16(3), 87-104.
  • Anagün, Ş. S. (2011). PISA 2006 sonuçlarına göre öğretme-öğrenme süreci değişkenlerinin öğrencilerin fen okuryazarlıklarına etkisi. Eğitim ve Bilim, 36(162), 84-102.
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  • Bandura, A. (1994). Self-efficacy. In V. S. Ramachaudran (Ed.), Encyclopedia of human behavior (Vol. 4) Is (pp. 71–81). Academic Press. https://doi.org/10.1002/9780470479216.corpsy0836
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  • Bilican Demir, S., & Yıldırım, O. (2021). Indirect effect of economic, social, and cultural status on immigrant students’ science performance through science dispositions: A multilevel analysis. Education and Urban Society, 53(3), 336–356. https://doi.org/10.1177/0013124520928602
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  • Bussie`re, P., Knighton, T., & Pennock, D. (2007). Measuring up: Canadian results of the OECD PISA study—the performance of Canada’s youth in science, reading and mathematics: 2006 first results for Canadians aged 15 (Report No: 590-593). Canadian Ministry of Industry. http://www5.statcan.gc.ca/bsolc/olc-cel/olc-cel?catno=81–590-X&chropg=1&lang=eng
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  • Doménech-Betoret, F., Abellán-Roselló, L., & Gómez-Artiga, A. (2017). Self-efficacy, satisfaction, and academic achievement: The mediator role of students' expectancy-value beliefs. Frontiers in Psychology, 8, 1193. https://doi.org/10.3389/fpsyg.2017.01193
  • Draper, D. (1995). Inference and hierarchical modelling in the social sciences. Journal of Educational Statistics, 20(2), 115-148. https://doi.org/10.3102%2F10769986020002115
  • Dyer, N. G., Hanges, P. J., & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. The Leadership Quarterly, 16(1), 149–167. https://doi.org/10.1016/j.leaqua.2004.09.009
  • Döş, İ., & Atalmış, E. H. (2016). OECD verilerine göre PISA sınav sonuçlarının değerlendirilmesi. Abant İzzet Baysal Üniversitesi Eğitim Fakültesi Dergisi, 16(2), 432-450. https://doi.org/10.17240/aibuefd.2016.16.2-5000194936
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There are 70 citations in total.

Details

Primary Language English
Subjects Studies on Education
Journal Section Article
Authors

Eda Akdoğdu Yıldız 0000-0003-4374-4379

Mehmet Can Demir 0000-0001-7849-7078

Selahattin Gelbal 0000-0001-5181-7262

Publication Date August 31, 2022
Submission Date May 5, 2021
Published in Issue Year 2022 Volume: 51 Issue: 2

Cite

APA Akdoğdu Yıldız, E., Demir, M. C., & Gelbal, S. (2022). Investigating Factors Affecting Scientific Literacy with Structural Equation Modeling and Multilevel Structural Equation Modeling: Case of PISA 2015. Çukurova Üniversitesi Eğitim Fakültesi Dergisi, 51(2), 795-824. https://doi.org/10.14812/cuefd.933101

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