The Relation Between ICT and Science in PISA 2015 for Bulgarian and Finnish Students

Bryce Odell; Adam M. Galovan; Maria Cutumisu

doi:10.29333/ejmste/7805

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Bryce Odell ¹, Adam M. Galovan ¹, Maria Cutumisu ¹ ^*

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¹ University of Alberta, CANADA^* Corresponding Author

Abstract

The relationship between Information and Communication Technology (ICT) and science performance has been the focus of much recent research, especially due to the prevalence of ICT in our digital society. However, the exploration of this relationship has yielded mixed results. Thus, the current study aims to uncover the learning processes that are linked to students’ science performance by investigating the effect of ICT variables on science for 15-year-old students in two countries with contrasting levels of technology implementation (Bulgaria n = 5,928 and Finland n = 5,882). The study analyzed PISA 2015 data using structural equation modeling to assess the impact of ICT use, availability, and comfort on students’ science scores, controlling for students’ socio-economic status. In both countries, results revealed that (1) ICT use and availability were associated with lower science scores and (2) students who were more comfortable with ICT performed better in science. This study can inform practical implementations of ICT in classrooms that consider the differential effect of ICT and it can advance theoretical knowledge around technology, learning, and cultural context.

Keywords

ICT
science
PISA
technology
factor analysis
structural equation modeling

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, 2020, Volume 16, Issue 6, Article No: em1846

https://doi.org/10.29333/ejmste/7805

Publication date: 21 Feb 2020

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References

Asparouhov, T., & Muthén, B. (2014). Multiple-group factor analysis alignment. Structural Equation Modeling: A Multidisciplinary Journal, 21(4), 495-508.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood, NJ: Prentice-Hall.
Bulut, O., & Cutumisu, M. (2018). When Technology Does Not Add Up: ICT Use Negatively Predicts Mathematics and Science Achievement for Finnish and Turkish Students in PISA 2012. Journal of Educational Multimedia and Hypermedia, 27(1), 25-42. Waynesville, NC USA: Association for the Advancement of Computing in Education (AACE). Retrieved on June 7, 2019 from https://www.learntechlib.org/primary/p/178514/.
Cheung, A. C., & Slavin, R. E. (2013). The effectiveness of educational technology applications for enhancing mathematics achievement in K-12 classrooms: A meta-analysis. Educational Research Review, 9, 88-113. https://doi.org/10.1016/j.edurev.2013.01.001
Cobern, W. W. (1993). Contextual Constructivism: The impact of culture on the learning and teaching of science. In: K. Tobin (Ed) The Practice of Constructivism in Science Education, pp 51-69, Lawrence-Erlbaum, Hillsdale, NJ.
Cuban, L. (2001). Oversold and underused: Computers in the classroom. Cambridge, MA: Harvard University Press.
Cussó-Calabuig, R., Farran, X. C., & Bosch-Capblanch, X. (2018). Effects of intensive use of computers in secondary school on gender differences in attitudes towards ICT: A systematic review. Education and Information Technologies, 23(5), 1-29. https://doi.org/10.1007/s10639-018-9706-6
De Witte, K., & Rogge, N. (2014). Does ICT matter for effectiveness and efficiency in mathematics education? Computers & Education, 75, 173-184. https://doi.org/10.1016/j.compedu.2014.02.012
European Union (March, 2019a). 2^nd survey of schools: ICT in Education. Digital Single Market. Retrieved from https://ec.europa.eu/digital-single-market/en/news/2nd-survey-schools-ict-education
European Union (March, 2019b). 2^nd survey of schools: ICT in Education. Bulgaria Country Report. Digital Single Market. https://doi.org/10.2759/83567
European Union (March, 2019c). 2^nd survey of schools: ICT in Education. Finland Country Report. Digital Single Market. https://doi.org/10.2759/364303
Gamazo, A., Martínez-Abad, F., Olmos-Migueláñez, S., & Rodríguez-Conde, M. J. (2018). Evaluación de factores relacionados con la eficacia escolar en PISA 2015. Un análisis multinivel1 Assessment of factors related to school effectiveness in PISA 2015. A multilevel analysis. Revista de educación, 379, 56-84.
George, D., & Mallery, M. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference, 17.0 update (10a ed.) Boston, MA: Pearson.
Gurria, A. (2016). PISA 2015 results in focus. PISA in Focus, (67), 1, OECD Publishing, Paris.
Hayduk, L. (2014). Seeing perfectly fitting factor models that are causally misspecified: Understanding that close-fitting models can be worse. Educational and Psychological Measurement, 74(6), 905-926.
Holzinger, K., & Swineford, F. (1937). The bi-factor method. Psychometrika, 2, 41-54.
Hu, X., Gong, Y., Lai, C., & Leung, F. K. (2018). The relationship between ICT and student literacy in mathematics, reading, and science across 44 countries: A multilevel analysis. Computers & Education. 125, 1-13. https://doi.org/10.1016/j.compedu.2018.05.021
ICTC (2016). Information and Communication Technology Council. Digital talent road to 2020 and beyond: A national strategy to develop Canada’s talent in a global digital economy. Retrieved from https://www.ictc-ctic.ca/wpcontent/uploads/2016/03/ICTC_DigitalTalent2020_ENGLISH_FINAL_March2016.pdf
Johnson, L., Becker, S. A., Estrada, V., Freeman, A., Kampylis, P., Vuorikari, R., & Punie, Y. (2014). NMC Horizon Report Europe: 2014 Schools Edition. The New Media Consortium. https://doi.org/10.2791/83258
Kline, R. B. (2015). Principles and practice of structural equation modelling (4th ed.). Guilford Press.
Little, T. D. (2013). Longitudinal structural equation modeling. New York, USA: Guilford Press.
Luu, K., & Freeman, J. G. (2011). An analysis of the relationship between information and communication technology (ICT) and scientific literacy in Canada and Australia. Computers & Education, 56(4), 1072-1082.
Martin-Perpiñá, M., Viñas i Poch, F., & Malo Cerrato, S. (2019). Media multitasking impact in homework, executive function and academic performance in Spanish adolescents. Psicothema, 31(1), 81-87.
Meng, L., Qiu, C., & Boyd‐Wilson, B. (2019). Measurement invariance of the ICT engagement construct and its association with students’ performance in China and Germany: Evidence from PISA 2015 data. British Journal of Educational Technology, 5(6), 3233-3251.
Muthén, L. K., & Muthén, B. O. (2012). Mplus statistical modeling software: Release 7.0. Los Angeles, CA: Muthén & Muthén.
Naumann, J. (2015). A model of online reading engagement: Linking engagement, navigation, and performance in digital reading. Computers in Human Behavior, 53, 263-277.
Nordicity (2017). Canada’s video game industry in 2017. Final report. Prepared for the Entertainment Software Association of Canada. Retrieved from http://theesa.ca/wp-content/uploads/2017/11/ESAC-Video-Games-in-Canada-Profile-2017_FINAL.pdf
Norris, P. (2001). Digital Divide: Civic Engagement, Information Poverty and the Internet Worldwide. Cambridge, UK: Cambridge University Press.
Novak, J., Purta, M., Marciniak, T., Ignatowicz, K., Rozenbaum, K., & Yearwood, K. (2018). The rise of Digital Challengers: How digitization can become the next growth engine for Central and Eastern Europe. McKinsey & Company. Retrieved from https://digitalchallengers.mckinsey.com/files/McKinsey%20CEE%20report_The%20Rise%20of%20Digital%20Challengers.pdf
OECD (2005). PISA 2003 Technical Report. PISA, OECD Publishing, Paris. Retrieved from http://www.oecd.org/education/school/programmeforinternationalstudentassessmentpisa/35188570.pdf
OECD (2009). PISA 2006 Technical Report. PISA, OECD Publishing, Paris. Retrieved from https://www.educacionyfp.gob.es/inee/dam/jcr:921a96c8-ac4a-4a50-9f20-191849cd5fa6/42025182.pdf
OECD (2014a). PISA 2012 Technical Report. PISA, OECD Publishing, Paris. Retrieved from: http://www.oecd.org/pisa/pisaproducts/PISA-2012-technical-report-final.pdf
OECD (2014b). PISA 2015 ICT Familiarity Questionnaire, PISA, OECD Publishing, Paris. Retrieved from: http://www.oecd.org/pisa/data/CY6_QST_MS_ICQ_Final.pdf
OECD (2014c). PISA 2015 Student Questionnaire, PISA, OECD Publishing, Paris. Retrieved from http://www.oecd.org/pisa/data/CY6_QST_MS_STQ_CBA_Final.pdf
OECD (2015). Students, Computers and Learning: Making the Connection. PISA, OECD Publishing, Paris, https://doi.org/10.1787/9789264239555-en
OECD (2016). PISA 2015 Results (Volume I): Excellence and Equity in Education, PISA, OECD Publishing, Paris. https://doi.org/10.1787/9789264266490-en
OECD (2017a). PISA 2015 Assessment and Analytical Framework: Science, Reading, Mathematic, Financial Literacy and Collaborative Problem Solving, revised edition, PISA, OECD Publishing, Paris. https://doi.org/10.1787/9789264281820-en
OECD (2017b). PISA 2015 Technical Report, PISA, OECD Publishing, Paris. Retrieved from https://www.oecd.org/pisa/sitedocument/PISA-2015-technical-report-final.pdf
OECD (n.d.) OECD PISA. Retrieved from http://www.oecd.org/pisa/
Petko, D., Cantieni, A., & Prasse, D. (2017). Perceived quality of educational technology matters: A secondary analysis of students’ ICT use, ICT-related attitudes, and PISA 2012 test scores. Journal of Educational Computing Research, 54(8), 1070-1091.
Piaget, J. (1952). The origins of intelligence in children (Vol. 8, No. 5, p. 18). New York: International Universities Press.
Randi, J. (1982). Flim-flam. Buffalo, NY: Prometheus.
Ridao-Cano, C., & Bodewig, C. (2018). Growing United: Upgrading Europe’s Convergence Machine. World Bank Report on the European Union. Retrieved from http://pubdocs.worldbank.org/en/244481520499464074/Growing-United-v03-online-18-03-08.pdf
Rodrigues, M., & Biagi, F. (2017). Digital technologies and learning outcomes of students from low socio-economic background: An Analysis of PISA 2015. Joint Research Centre (JRC) Science for Policy Report. Retrieved from: https://core.ac.uk/download/pdf/84886900.pdf
Rubin, D. B. (1987). Multiple Imputation for Nonresponse in Surveys. New York, NY, USA: John Wiley and Sons.
Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68-78.
Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th edn.). Boston. Ma: Pearson.
van der Linden, S., Maibach, E., Cook, J., Leiserowitz, A., & Lewandowsky, S. (2017). Inoculating against misinformation. Science, 358(6367), 1141-1142.
Waight, N., & Abd-El-Khalick, F. (2007). The impact of technology on the enactment of “inquiry” in a technology enthusiast sixth grade science classroom. Journal of Research in Science Teaching, 44, 154-182.
Webb, M. E. (2005). Affordances of ICT in science learning: Implications for an integrated pedagogy. International Journal of Science Education, 27, 705–736.
Yeganehfar, M., Zarei, A., Isfandyari-Mogghadam, A. R., & Famil-Rouhani, A. (2018). Justice in technology policy: A systematic review of gender divide literature and the marginal contribution of women on ICT. Journal of Information, Communication and Ethics in Society, 16(2), 123-137. https://doi.org/10.1108/JICES-06-2017-0038
Zandvliet, D. B. (2012). ICT learning environments and science education: Perception to practice. In Second international handbook of science education (pp. 1277-1289). Springer, Dordrecht.
Zhang, D., & Liu, L. (2016). How Does ICT Use Influence Students’ Achievements in Math and Science Over Time? Evidence from PISA 2000 to 2012. Eurasia Journal of Mathematics, Science & Technology Education, 12(9).

How to cite this article

APA

Odell, B., Galovan, A. M., & Cutumisu, M. (2020). The Relation Between ICT and Science in PISA 2015 for Bulgarian and Finnish Students. Eurasia Journal of Mathematics, Science and Technology Education, 16(6), em1846. https://doi.org/10.29333/ejmste/7805

Vancouver

Odell B, Galovan AM, Cutumisu M. The Relation Between ICT and Science in PISA 2015 for Bulgarian and Finnish Students. EURASIA J Math Sci Tech Ed. 2020;16(6):em1846. https://doi.org/10.29333/ejmste/7805

AMA

Odell B, Galovan AM, Cutumisu M. The Relation Between ICT and Science in PISA 2015 for Bulgarian and Finnish Students. EURASIA J Math Sci Tech Ed. 2020;16(6), em1846. https://doi.org/10.29333/ejmste/7805

Chicago

Odell, Bryce, Adam M. Galovan, and Maria Cutumisu. "The Relation Between ICT and Science in PISA 2015 for Bulgarian and Finnish Students". Eurasia Journal of Mathematics, Science and Technology Education 2020 16 no. 6 (2020): em1846. https://doi.org/10.29333/ejmste/7805

Harvard

Odell, B., Galovan, A. M., and Cutumisu, M. (2020). The Relation Between ICT and Science in PISA 2015 for Bulgarian and Finnish Students. Eurasia Journal of Mathematics, Science and Technology Education, 16(6), em1846. https://doi.org/10.29333/ejmste/7805

MLA

Odell, Bryce et al. "The Relation Between ICT and Science in PISA 2015 for Bulgarian and Finnish Students". Eurasia Journal of Mathematics, Science and Technology Education, vol. 16, no. 6, 2020, em1846. https://doi.org/10.29333/ejmste/7805