Öz
This study aims to evaluate the science achievements of Turkish students based on 2018 PISA data both according to Information and Communications Technology (ICT) variables of student and school levels. With a relational research model, regression analysis was used to measure the variance factors affecting science achievement. Also, two-level Hierarchical Linear Modelling (HLM) analysis was used to add school-level analysis. According to the results, it can be said that student-level ICT variables explain approximately 20% of the total variance in science success of students. The positive determinants are ICT resources, subject-related ICT use during lessons, and perceived ICT competence. The negative determinants are the use of ICT at school in general, ICT use as social interaction, and ICT use outside of school.
Anahtar Kelimeler
Kaynakça
- Anıl, D. & Özer, Y. (2012). The effect of the aim and frequency of computer usage on student achievement according to PISA 2006. Procedia-Social and Behavioral Sciences, 46, 5484-5488.
- Cheema, J. R. & Zhang, B. (2013). Quantity and quality of computer use and academic achievement: Evidence from a large-scale international test program. International Journal of Education and Development using Information and Communication Technology (IJEDICT), 9(2), 95-106.
- Delen, E., & Bulut, O. (2011). The relationship between students’ exposure to technology and their achievement in science and math. The Turkish Online Journal of Educational Technology, 10, 311-317.
- Elçiçek, M.. & Erdemci, H. (2021). Investigation of 21st-century competencies and e-learning readiness of higher education students on the verge of digital transformation. Journal of Computer and Education Research, 9 (17), 80-101. DOI: 10.18009/jcer.835877
- Erdoğdu, F., & Erdoğdu, E. (2015). The impact of access to ICT, student background and school/home environment on academic success of students in Turkey: An international comparative analysis. Computers & Education, 82, 26–49.
- EU (2018). Communication from the commission to the european parliament, the council, the European economic and social committee and the committee of the regions: On the digital education action plan. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52018DC0022&from=EN
- EU (2020). Digital education action plan. https://ec.europa.eu/education/education-in-the-eu/digital-education-action-plan_en
- 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.
- Hughes, C. (2020). Some implications of COVID‐19 for remote learning and the future of schooling. In progress reflection No. 36. On current and critical issues in curriculum, learning and assessment, UNESCO International Bureau of Education. Retrieved from https://unesdoc.unesco.org/ark:/48223/pf0000373229
- Jerrim, J., Lopez-Agudob, L. A., Marcenaro-Gutierrezb, O. D. & Shure, N. (2017). What happens when econometrics and psychometrics collide? An example using the PISA data. Economics of Education Review, 61, 51–58.
- Kubiatko, M. & Vlčková, K. (2010). The relationship between ICT use and science knowledge for Czech students: A secondary analysis of PISA 2006. International Journal of Science and Mathematics Education, 8(3), 523-543. https://doi.org/10.1007/s10763-010-9195-6
- Kunina-Habenicht, O. & Goldhammer, F. (2020). ICT engagement: A new construct and its assessment in PISA 2015. Large-scale Assessments in Education, 8(6), 1-21.
- Lorenceau, A., Marec C. & Mostafa, T. (2019). Upgrading the ICT questionnaire items in PISA 2021. OECD Education Working Paper No. 202.
- Luu, K. (2009). An analysis of the relationship between information and communication technology (ICT) and scientific literacy in Canada and Australia. [Unpublished master’s thesis]. Queen’s University Kingston.
- 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, 50(6), 3233–3251. https://doi.org/10.1111/bjet.12729
- 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), 1-15. https://doi.org/10.29333/ejmste/7805
- OECD (2019). PISA 2018 assessment and analytical framework, OECD Publishing, Retrieved from https://doi.org/10.1787/b25efab8-en.
- Papanastasiou, E. C., Zembylas, M., & Vrasidas, C. (2003). Can computer use hurt science achievement? The USA results from PISA. Journal of Science Education and Technology, 12(3), 325–332. https://doi.org/10.1023/A:1025093225753
- Park, Y. (2017). How can we help kids protect themselves online? Retrieved from https://www.weforum.org/agenda/2017/01/digital-danger-kids-protect-themselves-online/
- Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and data analysis methods (2nd ed.). Sage Publications, Inc.
- Rodrigues, M. & Biagi, F. (2017). Digital technologies and learning outcomes of students from low socio-economic background: An Analysis of PISA 2015. Publications Office of the European Union. Retrieved from https://doi.org/10.2760/415251
- Spiezia, V., (2010). Does computer use increase educational achievements? Student-level evidence from PISA. OECD Journal: Economic Studies, 1, 1-22.
- UN News (2020). Startling disparities in digital learning emerge as COVID-19 spreads: UN education agency. Retrieved from https://news.un.org/en/story/2020/04/1062232.
- 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),2431-2449.
Öz
This study aims to evaluate the science achievements of Turkish students based on 2018 PISA data both according to Information and Communications Technology (ICT) variables of student and school levels. With a relational research model, regression analysis was used to measure the variance factors affecting science achievement. Also, two-level Hierarchical Linear Modelling (HLM) analysis was used to add school-level analysis. According to the results, it can be said that student-level ICT variables explain approximately 20% of the total variance in science success of students. The positive determinants are ICT resources, subject-related ICT use during lessons, and perceived ICT competence. The negative determinants are the use of ICT at school in general, ICT use as social interaction, and ICT use outside of school.
Anahtar Kelimeler
Kaynakça
- Anıl, D. & Özer, Y. (2012). The effect of the aim and frequency of computer usage on student achievement according to PISA 2006. Procedia-Social and Behavioral Sciences, 46, 5484-5488.
- Cheema, J. R. & Zhang, B. (2013). Quantity and quality of computer use and academic achievement: Evidence from a large-scale international test program. International Journal of Education and Development using Information and Communication Technology (IJEDICT), 9(2), 95-106.
- Delen, E., & Bulut, O. (2011). The relationship between students’ exposure to technology and their achievement in science and math. The Turkish Online Journal of Educational Technology, 10, 311-317.
- Elçiçek, M.. & Erdemci, H. (2021). Investigation of 21st-century competencies and e-learning readiness of higher education students on the verge of digital transformation. Journal of Computer and Education Research, 9 (17), 80-101. DOI: 10.18009/jcer.835877
- Erdoğdu, F., & Erdoğdu, E. (2015). The impact of access to ICT, student background and school/home environment on academic success of students in Turkey: An international comparative analysis. Computers & Education, 82, 26–49.
- EU (2018). Communication from the commission to the european parliament, the council, the European economic and social committee and the committee of the regions: On the digital education action plan. Retrieved from https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52018DC0022&from=EN
- EU (2020). Digital education action plan. https://ec.europa.eu/education/education-in-the-eu/digital-education-action-plan_en
- 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.
- Hughes, C. (2020). Some implications of COVID‐19 for remote learning and the future of schooling. In progress reflection No. 36. On current and critical issues in curriculum, learning and assessment, UNESCO International Bureau of Education. Retrieved from https://unesdoc.unesco.org/ark:/48223/pf0000373229
- Jerrim, J., Lopez-Agudob, L. A., Marcenaro-Gutierrezb, O. D. & Shure, N. (2017). What happens when econometrics and psychometrics collide? An example using the PISA data. Economics of Education Review, 61, 51–58.
- Kubiatko, M. & Vlčková, K. (2010). The relationship between ICT use and science knowledge for Czech students: A secondary analysis of PISA 2006. International Journal of Science and Mathematics Education, 8(3), 523-543. https://doi.org/10.1007/s10763-010-9195-6
- Kunina-Habenicht, O. & Goldhammer, F. (2020). ICT engagement: A new construct and its assessment in PISA 2015. Large-scale Assessments in Education, 8(6), 1-21.
- Lorenceau, A., Marec C. & Mostafa, T. (2019). Upgrading the ICT questionnaire items in PISA 2021. OECD Education Working Paper No. 202.
- Luu, K. (2009). An analysis of the relationship between information and communication technology (ICT) and scientific literacy in Canada and Australia. [Unpublished master’s thesis]. Queen’s University Kingston.
- 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, 50(6), 3233–3251. https://doi.org/10.1111/bjet.12729
- 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), 1-15. https://doi.org/10.29333/ejmste/7805
- OECD (2019). PISA 2018 assessment and analytical framework, OECD Publishing, Retrieved from https://doi.org/10.1787/b25efab8-en.
- Papanastasiou, E. C., Zembylas, M., & Vrasidas, C. (2003). Can computer use hurt science achievement? The USA results from PISA. Journal of Science Education and Technology, 12(3), 325–332. https://doi.org/10.1023/A:1025093225753
- Park, Y. (2017). How can we help kids protect themselves online? Retrieved from https://www.weforum.org/agenda/2017/01/digital-danger-kids-protect-themselves-online/
- Raudenbush, S. W., & Bryk, A. S. (2002). Hierarchical Linear Models: Applications and data analysis methods (2nd ed.). Sage Publications, Inc.
- Rodrigues, M. & Biagi, F. (2017). Digital technologies and learning outcomes of students from low socio-economic background: An Analysis of PISA 2015. Publications Office of the European Union. Retrieved from https://doi.org/10.2760/415251
- Spiezia, V., (2010). Does computer use increase educational achievements? Student-level evidence from PISA. OECD Journal: Economic Studies, 1, 1-22.
- UN News (2020). Startling disparities in digital learning emerge as COVID-19 spreads: UN education agency. Retrieved from https://news.un.org/en/story/2020/04/1062232.
- 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),2431-2449.
Ayrıntılar
| Birincil Dil | İngilizce |
|---|---|
| Konular | Alan Eğitimleri |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 21 Aralık 2021 |
| Gönderilme Tarihi | 8 Nisan 2021 |
| Kabul Tarihi | 2 Ağustos 2021 |
| Yayımlandığı Sayı | Yıl 2021 Cilt: 9 Sayı: 18 |
Cited By
Does ICT involvement really matter? An investigation of Turkey’s case in PISA 2018
Education and Information Technologies
https://doi.org/10.1007/s10639-022-11067-8
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