Investigation of the Relationship Between Science Motivation and the 21st Century Skill Levels of Secondary School Students
DOI:
https://doi.org/10.47750/pegegog.14.03.01Keywords:
science motivation, 21st-century skills, secondary school students, path analysisAbstract
This study aimed to comprehensively examine the relationship between science motivation and the 21st-century skill levels of secondary school students. The study was conducted according to the quantitative methodology using the correlational survey method. The convenience sampling approach was adopted in the study. The study group was analyzed in terms of gender and grade level variables. Additionally, the measurement models created for middle school students' “Science Motivation” (SM) and “21st Century Skills” (21stCS), as well as the theoretical structural model was created. The study included 507 secondary school students (252 females, 255 males). Based on the results of the study, reviewing SM scale and its sub-dimensions, there was no significant difference between genders in the dimensions except for "Intrinsic Motivation." In addition, a significant difference was found between the grade levels in terms of (SM) level. There was no significant difference in the different sub-dimensions of the 21stCS according to gender; however, a significant difference was found in terms of grade levels. Generally, positive correlations were found between the sub-dimensions of the SM scale and the sub-dimensions of the 21stCS levels. Additionally, there is a statistically significant relationship between science motivation and cognitive skill, affective skill, and socio-cultural skill. These findings emphasize that science education and motivation in this field may play a significant role in the development of 21stCS.
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Ahonen A. K., Kinnunen P. (2015). How do students value the importance of twenty-first century skills? Scandinavian Journal of Educational Research, 59(4), 395–412.
Akcay, A. O., Semercioglu, M. S., & Güllü, H. (2022, April). The Relationship between Pre-Service Primary School Teachers' Perception of 21st-Century Skills, Mathematical Literacy Self-Efficiency, and Financial Literacy Attitudes and Behaviors. Elementary School Forum 9(1), 81-97.
Alderman, M. K. (2004). Motivation for achievement: Possibilities for teaching and learning (2nd ed.). New Jersey: Lawrence Erlbaum Associates Publishers.
Ananiadou, K., & Claro, M. (2009). 21St century skills and competences for new millennium learners in OECD countries. OECD education working papers. OECD Publishing (NJ1).
Aydın, S. (2021). Yabancı dil hazırlık sınıfı öğrencilerinin 21. yüzyıl becerileri, başarı odaklı motivasyonları ve İngilizce öğrenmeye yönelik motivasyonları arasındaki ilişkiler. Yayımlanmış yüksek lisan tezi, Bartın Üniversitesi, Eğitim Bilimleri Enstitüsü, Bartın.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological Bulletin, 107(2), 238.
Biggs, J. (1987). Student approaches to learning and studying. Australian Council for Educational Research.
Binkley, M., Erstad, O., Herman, J., Raizen, S., Ripley, M., Miller-Ricci, M., & Rumble, M. (2012). Defining twenty-first century skills. Assessment and teaching of 21st century skills, 17-66.
Bozkurt, Ş. B., & Çakir, H. (2016). Ortaokul öğrencilerinin 21. yüzyıl öğrenme beceri düzeylerinin cinsiyet ve sınıf seviyesine göre incelenmesi. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi, 39(39), 69-82.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136-162). CA: Sage.
Bybee, R. W. (2010). Advancing STEM education: A 2020 vision. Technology and Engineering Teacher, 70(1), 30-35.
Çeliker, H. D., Tokcan, A., & Korkubilmez, S. (2015). Does motivation toward science learning affect the scientific creativity?. Mustafa Kemal Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 12(30), 167-192.
Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268.
Dede, C. (2010). Comparing frameworks for 21st century skills. 21st century skills: Rethinking how students learn, 20(2010), 51-76.
Demir, R., Öztürk, N., & Dökme, İ. (2012). Investigation of 7th grade primary school students’ motivation towards science and technology course in terms of some variables. Mehmet Akif Ersoy University Journal of Education Faculty, 23, 1-2.
Field, A. (2013). Discovering statistics using IBM SPSS statistics. CA: Sage Publications Ltd.
Fraenkel, Jack R., & Wallen, Norman E. (2009). How to design and evaluate research in education (7th ed.). New York: McGraw-Hill.
Doğaç, E., & Gök, F. (2020). Yaparak yaşayarak öğrenme yönteminin 5. sınıf öğrencilerinin astronomiye karşı tutumlarına ve fen öğrenme motivasyonlarına etkisi. Türkiye Eğitim Dergisi, 5(2), 285-301.
George, D., & Mallery, P. (2010). SPSS for Windows step by step: A simple guide and reference. Allyn & Bacon.
Güvercin, Ö., Tekkaya, C., & Sungur, S. (2010). A cross age study of elementary students’ motivation towards science learning. Hacettepe Üniversitesi Eğitim Fakültesi Dergisi, 39(39), 233-243.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
Hellriegel, D. (2011). Organizational behavior. South-Western Cengage Learning.
Hu, L. T., & Bentler, P. M. (1999). Cut off criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
Işın, O. (2019). Fen eğitiminde motivasyon ölçeği: Geçerlik ve güvenirlik çalışması. Yayımlanmamış doktora tezi. Yıldız Teknik Üniversitesi, Eğitim Bilimleri Enstitüsü, İstanbul.
Jannah, M., Prasojo, L. D., & Jerusalem, M. A. (2020). Elementary school teachers’ perceptions of digital technology based learning in the 21st century: promoting digital technology as the proponent learning tools. Al Ibtida: Jurnal Pendidikan Guru MI, 7(1), 1-18.
Johnstone, A. H. (1991). Why is science difficult to learn? Things are seldom what they seem. Journal of Computer Assisted Learning, 7(2), 75-83.
Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language. Scientific Software International.
Karakaş, M. M. (2015). Ortaokul sekizinci sınıf öğrencilerinin fen bilimlerine yönelik 21. yüzyıl beceri düzeylerinin ölçülmesi. Yayınlanmamış yüksek lisans tezi. Eskişehir Osmangazi Üniversitesi Eğitim Bilimleri Enstitüsü, Eskişehir.
Karasar, N. (2005). Bilimsel araştırma yöntemi. Ankara: Nobel Yayın Dağıtım.
Koballa, T.R., Jr. & Glynn S. M. (2007). Attitudinal and motivational constructs in science learning. Sandra K. Abell & Norman G. Lederman (Eds.), Handbook of research on science education, Lawrence Erlbaum.
Kozikoglu, I., & Onur, Z. (2019). Predictors of Lifelong Learning: Information Literacy and Academic Self-Efficacy. Cypriot Journal of Educational Sciences, 14(4), 492-506.
Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002). The importance of the normality assumption in large public health data sets. Annual Review of Public Health, 23(1), 151-169.
Mai, M. Y., Yusuf, M., & Saleh, M. (2015). Motivation and engagement as a predictor of students’ science achievement satisfaction of Malaysian of secondary school students. European Journal of Social Sciences Education and Research, 5(1), 25-33.
Marsh, H. W., Balla, J. R., & McDonald, R. P. (1988). Goodness-of-fit indexes in confirmatory factor analysis: The effect of sample size. Psychological Bulletin, 103(3), 391.
MEB Eğitimi Araştırma ve Geliştirme Dairesi Başkanlığı. (2011). MEB 21. yüzyıl öğrenci profili. Retrieved October 11, 2022 from: https://www.meb.gov.tr/earged/ earged/21.%20yy_og_pro.pdf.
Millar, R. (1991). Why is science hard to learn?. Journal of Computer assisted learning, 7(2), 66-74.
National Research Council. (2011). Assessing 21st century skills: Summary of a workshop. The National Academies Press.
National Research Council. (2012). Education for life and work: Developing transferable knowledge and skills in the 21st century. National Academies Press.
Norman, G., & Streiner, D. (2008). Biostatistics: The bare essentials. People's Medical Publishing House.
Okumuş, S., Koc, Y. & Doymus, K. (2019). Determining the effect of cooperative learning and models on the conceptual understanding of the chemical reactions. Educational Policy Analysis and Strategic Research, 14(3), 154-177.
Olsen, A. K., & Chernobilsky, E. (2016). The effects of technology on academic motivation and achievement in a middle school mathematics classroom. NERA Conference Proceedings 2016.
Osborne, J., Simon, S., & Collins, S. (2003). Attitudes towards science: A review of the literature and its implications. International Journal of Science Education, 25(9), 1049-1079.
Özdilek, Z., Okumuş, S. & Doymuş, K. (2018). The effects of model-supported cooperative and individual learning methods on prospective science teachers’ understanding of solutions. Journal of Baltic Science Education, 17(6), 945-959.
Partnership for 21st Century Learning (P21). (2007). Framework for 21st century learning. Retrieved 20 October, 2022 from http://www.p21.org/our-work/p21-framework.
Pintrich, P.R., Schunk, D.H., (2002). Motivation in Education: Theory, Research and Applications, Upper Saddle River, NJ: Merrill Prentice Hall.
Rana, R. A., Mahmood, N., & Reid, N. (2015). Motivation and science performance: influence on student learning in science. Science Institute (Lahore), 27(2), 1445-1452.
Sternberg, R. J., & Williams, W. M. (2009). Educational psychology, (2nd ed.). Pearson.
Smith, J., & Hu, R. (2013). Rethinking teacher education: Synchronizing Eastern and Western views of teaching and learning to promote 21st century skills and global perspectives. Education Research and Perspectives, 40(2013), 86-108.
Tabachnick, B. G., & Fidell, L. S. (2007). Experimental designs using ANOVA. Belmont, CA: Thomson/Brooks/Cole.
Taloo. (2007). Business organisation & management. New Delhi, India: Tata McGraw-Hill.
Trilling, B., & Fadel, C. (2009). 21st century skills: Learning for life in our times. John Wiley & Sons.
UNESCO (2016). School and teaching practices for twenty‐first century challenges: Lessons from the Asia‐Pacific region (Phase II): Regional synthesis report. Paris, France: UNESCO. Retrieved October 15, 2022 from http://unesdoc.unesco.org/images/0024/002440/244022E.pdf
Uzun, N., & Keleş, Ö. (2010). Fen öğrenmeye yönelik motivasyonun bazı demografik özelliklere göre değerlendirilmesi. Gazi Eğitim Fakültesi Dergisi, 30(2), 561-584.
Van Laar E., Van Deursen A., Van Dijk J., De Haan J. (2017). The relation between 21st-century skills and digital skills: A systematic literature review. Computers in Human Behavior, 72, 577–588.
Wigfield, A., & Eccles, J. S. (2000). Expectancy–value theory of achievement motivation. Contemporary Educational Psychology, 25(1), 68-81.
Yenice, N., Saydam, G., & Telli, S. (2012). İlköğretim öğrencilerinin fen öğrenmeye yönelik motivasyonlarini etkileyen faktörlerin belirlenmesi. Ahi Evran Üniversitesi Kırşehir Eğitim Fakültesi Dergisi, 13(2), 231-247.
Yıldırım, H. İ., & Kansız, F. (2018). Ortaokul öğrencilerinin fen öğrenmeye yönelik motivasyonları üzerine bir araştırma. Cumhuriyet Uluslararası Eğitim Dergisi, 7(3), 241-268.
Yıldırım, R., & Ortak, Ş. (2021). Ortaokul öğrencilerinin 21. yüzyıl öğrenme ve yenilenme becerilerini kullanma düzeylerinin belirlenmesi. Turkish Studies-Educational Sciences, 16(6).
Zorlu, Y., & Zorlu, F. (2021). Investigation of the relationship between preservice science teachers' 21st century skills and science learning self-efficacy beliefs with structural equation model. Journal of Turkish Science Education, 18(1), 1-16.
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