SavedAdd your journal

Journals / International Journal of Assessment Tools in Education / 2026 / Volume: 6 Issue: 3

Measuring Nature of Science Views of Middle School Students

Yalçın Yalaki(Hacettepe University)0000-0003-0939-4766
Nuri Doğan(Hacettepe University)0000-0001-6274-2016
Serhat İrez(Marmara University)0000-0003-3294-4666
Nihal Doğan(Bolu Abant İzzet Baysal Üniversitesi)
Gültekin Çakmakçı(Hacettepe University)
Başak Erdem Kara(Hacettepe University)0000-0003-3066-2892
Pages
—
Publication Date
2019-10-15
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This test was easier and had higher discrimination, which can provide useful measurement data about students’ understanding of NOS for diagnostic or formative purposes.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Developing scientific literacy for all students is the most often stated purpose of contemporary science education.
📊
Key Findings & Data:The instrument was applied to 1397 middle school students.
💡
Conclusion & Impact:This test was easier and had higher discrimination, which can provide useful measurement data about students’ understanding of NOS for diagnostic or formative purposes.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Nature of science · middle school · assessment

Abstract

Developing scientific literacy for all students is the most often stated purpose of contemporary science education. Nature of science (NOS) is seen as an important component of scientific literacy. There are various perceptions of NOS in the science education community and NOS itself is an ever-changing construct. This makes it challenging to develop instruments for measuring understanding of NOS at different levels. Many instruments have been developed and are being developed to assess NOS learning, which indicates the importance attributed to this subject. In this study, we developed a multiple-choice test to measure NOS understanding of middle school students. The instrument was applied to 1397 middle school students. The 24 item multiple-choice test had KR-20 reliability coefficient of 0.74. A 12 item multiple-choice test created as a subset of the 24 items of the original test. This test was easier and had higher discrimination, which can provide useful measurement data about students’ understanding of NOS for diagnostic or formative purposes.

Özet

Developing scientific literacy for all students is the most often stated purpose of contemporary science education. Nature of science (NOS) is seen as an important component of scientific literacy. There are various perceptions of NOS in the science education community and NOS itself is an ever-changing construct. This makes it challenging to develop instruments for measuring understanding of NOS at different levels. Many instruments have been developed and are being developed to assess NOS learning, which indicates the importance attributed to this subject. In this study, we developed a multiple-choice test to measure NOS understanding of middle school students. The instrument was applied to 1397 middle school students. The 24 item multiple-choice test had KR-20 reliability coefficient of 0.74. A 12 item multiple-choice test created as a subset of the 24 items of the original test. This test was easier and had higher discrimination, which can provide useful measurement data about students’ understanding of NOS for diagnostic or formative purposes.

🔖

Cite This Article

Yalaki, Y., Doğan, N., İrez, S., Doğan, N., Çakmakçı, G., Kara, B. E. (2019). Measuring Nature of Science Views of Middle School Students. International Journal of Assessment Tools in Education, Volume: 6 Issue: 3. https://doi.org/10.21449/ijate.561154

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (29)

  1. American Association for the Advancement of Science. (1990). Science for All Americans. New York: Oxford University Press.
  2. American Association for the Advancement of Science. (1993). Project 2061: Benchmarks for science literacy. New York: Oxford University Press.
  3. Abd-El-Khalick, F. (2014). The evolving landscape related to assessment of nature of science. In N. G. Lederman & S. K. Abell (Eds.), Handbook of Research on Science Education, Volume II (pp. 635-664). New York: Routledge.
  4. Aikenhead, G. S. (1988). An analysis of four ways of assessing student beliefs about STS topics. Journal of research in science teaching, 25(8), 607-629.
  5. Aikenhead, G. S., & Ryan, A. G. (1992). The development of a new instrument: ‘Views on Science—Technology—Society’(VOSTS). Science education, 76(5), 477-491.
  6. Brown, T. A. (2015). Confirmatory factor analysis for applied research (2nd ed.). New York, NY: Guilford Press.
  7. Büyüköztürk, Ş. (2012). Sosyal bilimler için veri analizi el kitabı [Data analysis handbook for social sciences]. Ankara: Pegem Akademi.
  8. Cooley, W. W. & Klopfer, L. E. (1961). TOUS: Test on understanding science. Princeton, NJ: Education Testing Service.
  9. Hacıeminoğlu, E., Yılmaz-Tüzün, Ö., & Ertepınar, H. (2014) Development and validation of nature of science instrument for elementary school students. Education 3-13, 42(3), 258-283
  10. Hair, J. F., Black, W. C, Babin, B.J. & Anderson, R. E. (2009). Multivariate data analysis (7. ed.). Upper Saddle River, NJ: Pearson Education.
  11. Haladyna, T. M. (2004). Developing and validating multiple-choice test items (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates.
  12. Hambleton, R. K., & Swaminathan, H. (2010). Item response theory: principles and applications. Norwell, MA: Kluwer Nijhoff Publishing.
  13. Kline, R. B. (2015). Principles and practice of structural equation modeling (4th ed.). New York, NY: Guilford Press.
  14. Lederman, N.G. (1992). Students’ and Teachers’ Conceptions of the Nature of Science: A Review of the Research, Journal of Research in Science Teaching, 29(4), 331- 359.
  15. Lederman, N.G. (2007). Nature of science: Past, present, and future. In S.K. Abell &N.G. Lederman (Eds.), Handbook of research in science education (pp. 831–880). Mahwah, NJ: Lawrence Erlbaum Associates.
  16. Lederman, N. G., Abd-El-Khalick, F., Bell, R. L., & Schwartz, R. (2002). Views of nature of science questionnaire (VNOS): Toward valid and meaningful assessment of learners’ conceptions of nature of science. Journal of Research in Science Teaching, 39(6), 497-521.
  17. Lederman, J. S., & Khishfe, R. (2002) Views of nature of science, Form D. Unpublished paper: Illinois Institute of Technology, Chicago, IL.
  18. Lederman, N. G., & O'Malley, M. (1990). Students' perceptions of tentativeness in science: Development, use, and sources of change. Science Education, 74(2), 225-239.
  19. Matthews, M. R. (1998). In defense of modest goals when teaching about the nature of science. Journal of Research in Science Teaching 35(2), 161–174.
  20. Milli Eğitim Bakanlığı [MEB]. (2013). İlköğretim kurumları (ilkokullar ve ortaokullar) fen bilimleri dersi (3, 4, 5, 6, 7 ve 8. sınıflar) öğretim programı. [Primary schools (elementary and middle) science lesson (3, 4, 5, 6, 7 and 8th grades) curriculum]. Ankara: MEB
  21. Milli Eğitim Bakanlığı [MEB]. (2018). İlköğretim kurumları (ilkokullar ve ortaokullar) fen bilimleri dersi (3, 4, 5, 6, 7 ve 8. sınıflar) öğretim programı. [Primary schools (elementary and middle) science lesson (3, 4, 5, 6, 7 and 8th grades) curriculum]. Ankara: MEB
  22. Nunnally, J. C. (1973). Research strategies and measurement methods for investigating human development. In J. R. Nesselroade & H. W. Reese, Life-span developmental psychology: Methodological issues. Oxford, England: Academic Press.
  23. National Research Council (1996). National science education standards. Washington, DC: National Academy Press.
  24. Next Generation Science Standards Lead States. (2013). Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press.
  25. Pallant, J. (2005). SPSS survival manual: a step by step guide to data analysis using SPSS. Maidenhead: Open University Press/McGraw-Hill,
  26. Reckase, M. D. (1979). Unifactor latent trait models applied to multifactor tests: Results and implications. Journal of Educational Statistics, 4(3), 207-230.
  27. Tabachnick, B. G. & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Upper Saddle River, NJ: Pearson Education.
  28. Temel, S., Şen, Ş. & Özcan, Ö. (2018) The development of the nature of science view scale (NOSvs) at university level. Research in Science & Technological Education, 36(1), 55-68
  29. Wang, Y. & Liu, Q. (2005). Comparison of Akaike information criterion (AIC) and Bayesian information criterion (BIC) in selection of stock–recruitment relationships. Fisheries Research, 77, 220–225.