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Predictors of Mathematics Achievement of Students in Turkey: An Analysis of the Variables of Information and Communication Technologies Familiarity

Yıl 2022, Sayı: 54, 272 - 296, 02.01.2022
https://doi.org/10.9779/pauefd.845834

Öz

Mathematics achievement is seen as one of the important indicators of students' academic success for various reasons. Although it is known that there are many factors affecting students' mathematics achievement, factors related to students' familiarity with information and communication technologies come to the fore due to the Covid-19 pandemic. This study, it is aimed to investigate the predictor of ICT familiarity factors on students' mathematics achievement. This study is quantitative research in the relational survey type. The sample of the study consists of 6890 students aged 15 from Turkey. Multiple linear regression analysis was used in the analysis of the data. The results of the research show that the increase in the duration of ICT use in mathematics lessons, the interest and competence of students in ICT, the accessibility of ICT at home, and the use of ICT for leisure purposes can increase the mathematics achievement of 15-year-old students in Turkey. With this result, it is shown in this study that the use of ICT outside of school and in school in general, the sharing of ICT in social environments, and the increase in the duration of using ICT outside of classes can negatively affect mathematics achievement of 15-year-old students.

Kaynakça

  • Albiser, E., Echazarra, A., Fraser, P., Fülöp, G., Schwabe, M., & Tremblay, K. (2020). School education during Covid-19: Were teachers and students ready? Turkey - Country Note. Paris: OECD. [Available online at: http://www.oecd.org/education/Turkey-coronavirus-education-country-note.pdf], Retrieved on May 19, 2020.
  • Altun, M. (2006). Matematik öğretiminde gelişmeler. Uludağ Üniversitesi Eğitim Fakültesi Dergisi, 19(2), 223-238.
  • Aslanargun, E., Bozkurt, S. ve Sarıoğlu, S. (2016). Sosyo ekonomik değişkenlerin öğrencilerin akademik başarısı üzerine etkileri. Uşak Üniversitesi Sosyal Bilimler Dergisi, 9(3), 201-234.
  • Atalay, N., & Anagün, Ş. S. (2014). Kırsal alanlarda görev yapan sınıf öğretmenlerinin bilgi ve iletişim teknolojilerinin kullanımına ilişkin görüşleri. Eğitimde Nitel Araştırmalar Dergisi, 2(3), 9-27. doi:10.14689/issn.2148-2624.1.2c3s1m
  • Aypay, A. (2010). Information and communication technology (ICT) usage and achievement of Turkish students in PISA 2006. Turkish Online Journal of Educational Technology-TOJET, 9(2), 116-124.
  • Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual review of psychology, 52(1), 1-26. doi:10.1146/annurev.psych.52.1.1
  • Biagi, F., & Loi, M. (2013). Measuring ICT use and learning outcomes: Evidence from recent econometric studies. European Journal of Education, 48(1), 28-42. doi:10.1111/ejed.12016
  • Boudreau, J., & Rice, S. (2015). Bright, shiny objects and the future of HR. Harvard Business Review, 93(7), 72-78.
  • 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.
  • Byungura, J. C., Hansson, H., Muparasi, M., & Ruhinda, B. (2018). Familiarity with Technology among First-Year Students in Rwandan Tertiary Education. Electronic Journal of e-Learning, 16(1), 30-45.
  • Conbere, J., & Heorhiadi, A. (2017). Escaping the Tower of Babble. OD practitioner, 49(1), 28-34.
  • Corti, L. (2008). Secondary analysis. In L. M. Given (Ed.), The Sage encyclopedia of qualitative research methods Volumes 1 and 2 (801-803). Thousand Oaks, California: SAGE Publications, Inc.
  • Coxe, S., West, S. G., & Aiken, L. S. (2013). Generalized linear models. In T. D. Little (Ed.), The Oxford handbook of quantitative methods Volume 2: Statistical analysis (26-51). New York: Oxford University Press
  • Deaney, R., Ruthven, K., & Hennessy, S. (2003). Pupil perspectives on the contribution of information and communication technology to teaching and learning in the secondary school. Research Papers in Education, 18(2), 141-165. doi:10.1080/0267152032000081913
  • Delen, E., & Bulut, O. (2011). The Relationship between Students' Exposure to Technology and Their Achievement in Science and Math. Turkish Online Journal of Educational Technology-TOJET, 10(3), 311-317.
  • Durgun, Ö. (2011). Türkiye’de yoksulluk ve çocuk yoksulluğu üzerine bir inceleme. Bilgi Ekonomisi ve Yönetimi Dergisi, 6(1), 143-154.
  • Dursun, Ş., & Dede, Y. (2004). Öğrencilerin matematikte başarısını etkileyen faktörler matematik öğretmenlerinin görüşleri bakımından. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi, 24(2), 217-230.
  • Eurydice. (2004). Key data on information and communication technology in schools in Europe 2004 Edition. Brussels: Eurydice.
  • Farina, P., San Martín, E., Preiss, D. D., Claro, M., & Jara, I. (2015). Measuring the relation between computer use and reading literacy in the presence of endogeneity. Computers & Education, 80, 176–186. doi:10.1016/j.compedu.2014.08.010
  • Gümüş, S., & Atalmış, E. H. (2011). Exploring the relationship between purpose of computer usage and reading skills of Turkish students: evidence from PISA 2006. Turkish Online Journal Of Educational Technology-TOJET, 10(3), 129-140.
  • Hajjar, S. T. E. (2018). Statistical analysis: Internal-consistency reliability and construct validity. International Journal of Quantitative and Qualitative Research Methods, 6(1), 46-57.
  • 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. doi:10.1016/j.compedu.2018.05.021
  • Jacobsen, W. C., & Forste, R. (2011). The wired generation: Academic and social outcomes of electronic media use among university students. Cyberpsychology, Behavior, and Social Networking, 14(5), 275-280. doi:10.1089/cyber.2010.0135
  • Johnston, M. P. (2017). Secondary data analysis: A method of which the time has come. Qualitative and Quantitative Methods in Libraries, 3(3), 619-626.
  • Karaman, M. K., & Kurfallı, H. (2008). Sınıf öğretmenlerinin bilgi ve iletişim teknolojilerini öğretim amaçlı kullanım düzeyleri. Kuramsal Eğitimbilim Dergisi, 1(2), 43-56.
  • Karanja, M. (2018). Role of ICT in dissemination of information in secondary schools in Kenya: A literature based review. Journal of Information and Technology, 2(1), 28-38.
  • Kim, J. H. (2019). Multicollinearity and misleading statistical results. Korean Journal of Anesthesiology, 72(6), 558-569. doi:10.4097/kja.19087
  • Kubiatko, M., & Vlckova, 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. doi:10.1007/s10763-010-9195-6
  • Kuhlemeier, H., & Hemker, B. (2007). The impact of computer use at home on students’ Internet skills. Computers & Education, 49(2), 460-480. doi:10.1016/j.compedu.2005.10.004
  • 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. doi:10.1146/annurev.publhealth.23.100901.140546
  • 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. doi:10.1016/j.compedu.2010.11.008
  • 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. doi:10.1111/bjet.12729
  • Midi, H., Sarkar, S. K., & Rana, S. (2010). Collinearity diagnostics of binary logistic regression model. Journal of Interdisciplinary Mathematics, 13(3), 253-267. https://doi.org/10.1080/09720502.2010.10700699
  • Mirazchiyski, P. (2014). Analyzing the TALIS data using the IEA IDB Analyzer. In A. Becker (Ed.), TALIS user guide for the international database (28-72). Paris: OECD Publishing.
  • Nimon, K. (2010). Regression commonality analysis: Demonstration of an SPSS solution. Multiple Linear Regression Viewpoints, 36(1), 10-17.
  • 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. doi:10.29333/ejmste/7805
  • OECD. (2005). PISA 2003 technical report. Paris: OECD Publishing. doi.org/10.1787/9789264010543-en
  • OECD. (2009). PISA data analysis manual: SPSS (Second Edition). Paris: OECD Publishing. doi:10.1787/9789264056275-en
  • OECD. (2017). PISA 2015 technical report. Paris: OECD Publishing. [Available online at: https://www.oecd.org/pisa/sitedocument/PISA-2015-technical-report-final.pdf], Retrieved on April 23, 2020.
  • OECD. (2019). PISA 2018 results (VolumeI): What students know and can do. Paris: OECD Publishing. doi:10.1787/5f07c754-en
  • Oliver, R. (2002). The role of ICT in higher education for the 21st century: ICT as a change agent for education. Paper presented at the Higher education for the 21st century conference, Curtin. [Available online at: https://www.qualityes.org/wp-content/uploads/2018/06/The_role_of_ICT_in_higher_education_for_the_21st_c-2.pdf], Retrieved on March 18, 2020.
  • Özkan, U. B. (2020). Öğrencilerde eudaimonianın ve akademik başarının yordayıcısı olarak ekonomik, sosyal ve kültürel düzey. Yaşadıkça Eğitim, 34(2), 344-359. doi:10.33308/26674874.2020342208
  • Özsoy, G. (2005). Problem çözme becerisi ile matematik başarısı arasındaki ilişki. Gazi Eğitim Fakültesi Dergisi, 25(3), 179-190.
  • Papanastasiou, E. C., Zembylas, M., & Vrasidas, C. (2005). An examination of the PISA database to explore the relationship between computer use and science achievement. Educational Research and Evaluation, 11(6), 529–543. doi:10.1080/13803610500254824
  • Park, S., & Weng, W.(2020). The relationship between ICT-related factors and student academic achievement and the moderating effect of country economic indexes across 39 countries: Using multilevel structural equation modelling. Educational Technology & Society, 23(3), 1–15.
  • 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. doi:10.1177/0735633116649373
  • Ranguelov, S., Horvath, A., Dalferth, S., & Noorani, S. (2011). Key data on learning and innovation through ICT at school in Europe 2011. Brussels: Education, Audiovisual and Culture Executive Agency. doi:10.2797/61068
  • Renshaw, C. E., & Taylor, H. A. (2000). The educational effectiveness of computer-based instruction. Computers & Geosciences, 26(6), 677-682. doi:10.1016/S0098-3004(99)00103-X
  • Rutkowski, L., Gonzalez, E., Joncas, M. ve von Davier, M. (2010). International large-scale assessment data: Issues in secondary analysis and reporting. Educational Researcher, 39(2), 142-151. doi:10.3102/0013189X10363170
  • 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. doi:10.1037110003-066X.55.1.68
  • Sarıer, Y. (2010). Ortaöğretime Giriş Sınavları (OKS-SBS) ve PISA sonuçları ışığında eğitimde fırsat eşitliğinin değerlendirilmesi. Ahi Evran Üniversitesi Eğitim Fakültesi Dergisi, 11(3), 107-129.
  • Savaş, E., Taş, S., & Duru, A. (2010). Matematikte öğrenci başarısını etkileyen faktörler. İnönü Üniversitesi Eğitim Fakültesi Dergisi, 11(1), 113-132.
  • Shatskikh, S.Y., & Melkumova, L. E. (2016). Normality assumption in statistical data analysis. Proceedings from ITNT-2016: International Conference Information Technology and Nanotechnology. Samara, Russia: CEUR-Workshop. [Available online at: http://ceur-ws.org/Vol-1638/Paper90.pdf], Retrieved on March 18, 2020.
  • Sherif, V. (2018). Evaluating preexisting qualitative research data for secondary analysis. Forum: Qualitative Social Research, 19(2), 26-42.
  • Skryabin, M., Zhang, J., Liu, L., & Zhang, D. (2015). How the ICT development level and usage influence student achievement in reading, mathematics, and science. Computers & Education, 85, 49-58. doi:10.1016/j.compedu.2015.02.004
  • Šorgo, A., Verčkovnik, T., & Kocijančič, S. (2010). Information and communication technologies (ICT) in biology teaching in Slovenian secondary schools. Eurasia Journal of Mathematics, Science and Technology Education, 6(1), 37-46. doi:10.12973/ejmste/75225
  • Srijamdee, K., & Pholphirul, P. (2020). Does ICT familiarity always help promote educational outcomes? Empirical evidence from PISA-Thailand. Education and Information Technologies, 25, 2933-2970. doi:10.1007/s10639-019-10089-z10.1080/10723030802533853
  • Streiner, D. L. (2003). Starting at the beginning: an introduction to coefficient alpha and internal consistency. Journal of personality assessment, 80(1), 99-103. doi:10.1207/S15327752JPA8001_18
  • Suna, H. E., Tanberkan, H., Taş, U. E., Eroğlu, E., & Altun, Ü. (2019). PISA 2018 Türkiye ön raporu. Ankara: T.C. Millî Eğitim Bakanlığı
  • Thamarana, S. (2015). The role of information and communication technologies in achieving standards in English language teaching. The Criterion: An International Journal in English, 6(4), 227-232.
  • Tomul, E. (2007). Türkiye’de eğitime katılım üzerinde gelirin etkisi. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi, 2(22), 122-131.
  • Tondeur, J., Van Braak, J., & Valcke, M. (2007). Curricula and the use of ICT in education: Two worlds apart?. British Journal of Educational Technology, 38(6), 962-976. doi:10.1111/j.1467-8535.2006.00680.x
  • Turner, P. D. (1997, March, 24-28). Secondary analysis of qualitative data. Annual Meeting of the American Educational Research Association, Chicago, IL, USA.
  • Volman, M., Van Eck, E., Heemskerk, I., & Kuiper, E. (2005). New technologies, new differences. Gender and ethnic differences in pupils' use of ICT in primary and secondary education. Computers & Education, 45(1), 35-55. doi:10.1016/j.compedu.2004.03.001
  • York, T. T., Gibson, C. ve Rankin, S. (2015). Defining and measuring academic success. Practical Assessment, Research, and Evaluation, 20(1), 1-20. doi:10.7275/hz5x-tx03

Türkiye’deki Öğrencilerin Matematik Başarısının Belirleyicileri: Bilgi ve İletişim Teknolojilerine Aşinalık Değişkenlerine İlişkin Bir Analiz

Yıl 2022, Sayı: 54, 272 - 296, 02.01.2022
https://doi.org/10.9779/pauefd.845834

Öz

Matematik başarısı, çeşitli nedenlerle öğrencilerin akademik başarısının önemli göstergelerinden biri olarak görülmektedir. Matematik başarısına verilen önem, öğrencilerin matematik başarısını etkileyen faktörlerin neler olabileceği sorusunu da akıllara getirmektedir. Öğrencilerin matematik başarısını etkileyen pek çok faktör olduğu bilinmekle birlikte Covid-19 pandemisi nedeniyle öğrencilerin bilgi ve iletişim teknolojilerine olan aşinalıkları ile ilgili faktörler ön plana çıkmaktadır. Bu çalışmada, BİT aşinalık faktörlerinin öğrencilerin matematik başarısı üzerindeki yordayıcılığını araştırmak amaçlanmaktadır. İlişkisel tarama türünde nicel bir araştırma olan bu çalışmanın verileri PISA-2018’den elden edilen ikincil verilerdir. Çalışmanın örneklemini Türkiye'den 15 yaşındaki 6890 öğrenci oluşturmaktadır. Verilerin analizinde çoklu doğrusal regresyon analizi kullanılmıştır. Analizler için IDB Analyzer programından yararlanılmıştır. Araştırmanın sonuçları, Türkiye’de matematik derslerinde BİT kullanma süresinin, öğrencilerde BİT’e yönelik ilgi ve yetkinliğin, BİT’e evde erişebilirliğin ve boş zamanlarda eğlence amaçlı olarak BİT kullanımının artmasının 15 yaş grubu öğrencilerin matematik başarılarını artırabileceğini göstermektedir. Bu sonuçla birlikte, Türkiye’de okul dışında okul çalışmaları için ve okulda genel olarak BİT kullanımının, sosyal ortamlarda BİT’le ilgili yapılan paylaşımların ve dersler dışında (evde veya okulda) BİT kullanma süresinin artmasının 15 yaş grubu öğrencilerin matematik başarılarını olumsuz yönde etkileyebileceği bu çalışmada gösterilmektedir.

Kaynakça

  • Albiser, E., Echazarra, A., Fraser, P., Fülöp, G., Schwabe, M., & Tremblay, K. (2020). School education during Covid-19: Were teachers and students ready? Turkey - Country Note. Paris: OECD. [Available online at: http://www.oecd.org/education/Turkey-coronavirus-education-country-note.pdf], Retrieved on May 19, 2020.
  • Altun, M. (2006). Matematik öğretiminde gelişmeler. Uludağ Üniversitesi Eğitim Fakültesi Dergisi, 19(2), 223-238.
  • Aslanargun, E., Bozkurt, S. ve Sarıoğlu, S. (2016). Sosyo ekonomik değişkenlerin öğrencilerin akademik başarısı üzerine etkileri. Uşak Üniversitesi Sosyal Bilimler Dergisi, 9(3), 201-234.
  • Atalay, N., & Anagün, Ş. S. (2014). Kırsal alanlarda görev yapan sınıf öğretmenlerinin bilgi ve iletişim teknolojilerinin kullanımına ilişkin görüşleri. Eğitimde Nitel Araştırmalar Dergisi, 2(3), 9-27. doi:10.14689/issn.2148-2624.1.2c3s1m
  • Aypay, A. (2010). Information and communication technology (ICT) usage and achievement of Turkish students in PISA 2006. Turkish Online Journal of Educational Technology-TOJET, 9(2), 116-124.
  • Bandura, A. (2001). Social cognitive theory: An agentic perspective. Annual review of psychology, 52(1), 1-26. doi:10.1146/annurev.psych.52.1.1
  • Biagi, F., & Loi, M. (2013). Measuring ICT use and learning outcomes: Evidence from recent econometric studies. European Journal of Education, 48(1), 28-42. doi:10.1111/ejed.12016
  • Boudreau, J., & Rice, S. (2015). Bright, shiny objects and the future of HR. Harvard Business Review, 93(7), 72-78.
  • 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.
  • Byungura, J. C., Hansson, H., Muparasi, M., & Ruhinda, B. (2018). Familiarity with Technology among First-Year Students in Rwandan Tertiary Education. Electronic Journal of e-Learning, 16(1), 30-45.
  • Conbere, J., & Heorhiadi, A. (2017). Escaping the Tower of Babble. OD practitioner, 49(1), 28-34.
  • Corti, L. (2008). Secondary analysis. In L. M. Given (Ed.), The Sage encyclopedia of qualitative research methods Volumes 1 and 2 (801-803). Thousand Oaks, California: SAGE Publications, Inc.
  • Coxe, S., West, S. G., & Aiken, L. S. (2013). Generalized linear models. In T. D. Little (Ed.), The Oxford handbook of quantitative methods Volume 2: Statistical analysis (26-51). New York: Oxford University Press
  • Deaney, R., Ruthven, K., & Hennessy, S. (2003). Pupil perspectives on the contribution of information and communication technology to teaching and learning in the secondary school. Research Papers in Education, 18(2), 141-165. doi:10.1080/0267152032000081913
  • Delen, E., & Bulut, O. (2011). The Relationship between Students' Exposure to Technology and Their Achievement in Science and Math. Turkish Online Journal of Educational Technology-TOJET, 10(3), 311-317.
  • Durgun, Ö. (2011). Türkiye’de yoksulluk ve çocuk yoksulluğu üzerine bir inceleme. Bilgi Ekonomisi ve Yönetimi Dergisi, 6(1), 143-154.
  • Dursun, Ş., & Dede, Y. (2004). Öğrencilerin matematikte başarısını etkileyen faktörler matematik öğretmenlerinin görüşleri bakımından. Gazi Üniversitesi Gazi Eğitim Fakültesi Dergisi, 24(2), 217-230.
  • Eurydice. (2004). Key data on information and communication technology in schools in Europe 2004 Edition. Brussels: Eurydice.
  • Farina, P., San Martín, E., Preiss, D. D., Claro, M., & Jara, I. (2015). Measuring the relation between computer use and reading literacy in the presence of endogeneity. Computers & Education, 80, 176–186. doi:10.1016/j.compedu.2014.08.010
  • Gümüş, S., & Atalmış, E. H. (2011). Exploring the relationship between purpose of computer usage and reading skills of Turkish students: evidence from PISA 2006. Turkish Online Journal Of Educational Technology-TOJET, 10(3), 129-140.
  • Hajjar, S. T. E. (2018). Statistical analysis: Internal-consistency reliability and construct validity. International Journal of Quantitative and Qualitative Research Methods, 6(1), 46-57.
  • 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. doi:10.1016/j.compedu.2018.05.021
  • Jacobsen, W. C., & Forste, R. (2011). The wired generation: Academic and social outcomes of electronic media use among university students. Cyberpsychology, Behavior, and Social Networking, 14(5), 275-280. doi:10.1089/cyber.2010.0135
  • Johnston, M. P. (2017). Secondary data analysis: A method of which the time has come. Qualitative and Quantitative Methods in Libraries, 3(3), 619-626.
  • Karaman, M. K., & Kurfallı, H. (2008). Sınıf öğretmenlerinin bilgi ve iletişim teknolojilerini öğretim amaçlı kullanım düzeyleri. Kuramsal Eğitimbilim Dergisi, 1(2), 43-56.
  • Karanja, M. (2018). Role of ICT in dissemination of information in secondary schools in Kenya: A literature based review. Journal of Information and Technology, 2(1), 28-38.
  • Kim, J. H. (2019). Multicollinearity and misleading statistical results. Korean Journal of Anesthesiology, 72(6), 558-569. doi:10.4097/kja.19087
  • Kubiatko, M., & Vlckova, 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. doi:10.1007/s10763-010-9195-6
  • Kuhlemeier, H., & Hemker, B. (2007). The impact of computer use at home on students’ Internet skills. Computers & Education, 49(2), 460-480. doi:10.1016/j.compedu.2005.10.004
  • 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. doi:10.1146/annurev.publhealth.23.100901.140546
  • 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. doi:10.1016/j.compedu.2010.11.008
  • 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. doi:10.1111/bjet.12729
  • Midi, H., Sarkar, S. K., & Rana, S. (2010). Collinearity diagnostics of binary logistic regression model. Journal of Interdisciplinary Mathematics, 13(3), 253-267. https://doi.org/10.1080/09720502.2010.10700699
  • Mirazchiyski, P. (2014). Analyzing the TALIS data using the IEA IDB Analyzer. In A. Becker (Ed.), TALIS user guide for the international database (28-72). Paris: OECD Publishing.
  • Nimon, K. (2010). Regression commonality analysis: Demonstration of an SPSS solution. Multiple Linear Regression Viewpoints, 36(1), 10-17.
  • 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. doi:10.29333/ejmste/7805
  • OECD. (2005). PISA 2003 technical report. Paris: OECD Publishing. doi.org/10.1787/9789264010543-en
  • OECD. (2009). PISA data analysis manual: SPSS (Second Edition). Paris: OECD Publishing. doi:10.1787/9789264056275-en
  • OECD. (2017). PISA 2015 technical report. Paris: OECD Publishing. [Available online at: https://www.oecd.org/pisa/sitedocument/PISA-2015-technical-report-final.pdf], Retrieved on April 23, 2020.
  • OECD. (2019). PISA 2018 results (VolumeI): What students know and can do. Paris: OECD Publishing. doi:10.1787/5f07c754-en
  • Oliver, R. (2002). The role of ICT in higher education for the 21st century: ICT as a change agent for education. Paper presented at the Higher education for the 21st century conference, Curtin. [Available online at: https://www.qualityes.org/wp-content/uploads/2018/06/The_role_of_ICT_in_higher_education_for_the_21st_c-2.pdf], Retrieved on March 18, 2020.
  • Özkan, U. B. (2020). Öğrencilerde eudaimonianın ve akademik başarının yordayıcısı olarak ekonomik, sosyal ve kültürel düzey. Yaşadıkça Eğitim, 34(2), 344-359. doi:10.33308/26674874.2020342208
  • Özsoy, G. (2005). Problem çözme becerisi ile matematik başarısı arasındaki ilişki. Gazi Eğitim Fakültesi Dergisi, 25(3), 179-190.
  • Papanastasiou, E. C., Zembylas, M., & Vrasidas, C. (2005). An examination of the PISA database to explore the relationship between computer use and science achievement. Educational Research and Evaluation, 11(6), 529–543. doi:10.1080/13803610500254824
  • Park, S., & Weng, W.(2020). The relationship between ICT-related factors and student academic achievement and the moderating effect of country economic indexes across 39 countries: Using multilevel structural equation modelling. Educational Technology & Society, 23(3), 1–15.
  • 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. doi:10.1177/0735633116649373
  • Ranguelov, S., Horvath, A., Dalferth, S., & Noorani, S. (2011). Key data on learning and innovation through ICT at school in Europe 2011. Brussels: Education, Audiovisual and Culture Executive Agency. doi:10.2797/61068
  • Renshaw, C. E., & Taylor, H. A. (2000). The educational effectiveness of computer-based instruction. Computers & Geosciences, 26(6), 677-682. doi:10.1016/S0098-3004(99)00103-X
  • Rutkowski, L., Gonzalez, E., Joncas, M. ve von Davier, M. (2010). International large-scale assessment data: Issues in secondary analysis and reporting. Educational Researcher, 39(2), 142-151. doi:10.3102/0013189X10363170
  • 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. doi:10.1037110003-066X.55.1.68
  • Sarıer, Y. (2010). Ortaöğretime Giriş Sınavları (OKS-SBS) ve PISA sonuçları ışığında eğitimde fırsat eşitliğinin değerlendirilmesi. Ahi Evran Üniversitesi Eğitim Fakültesi Dergisi, 11(3), 107-129.
  • Savaş, E., Taş, S., & Duru, A. (2010). Matematikte öğrenci başarısını etkileyen faktörler. İnönü Üniversitesi Eğitim Fakültesi Dergisi, 11(1), 113-132.
  • Shatskikh, S.Y., & Melkumova, L. E. (2016). Normality assumption in statistical data analysis. Proceedings from ITNT-2016: International Conference Information Technology and Nanotechnology. Samara, Russia: CEUR-Workshop. [Available online at: http://ceur-ws.org/Vol-1638/Paper90.pdf], Retrieved on March 18, 2020.
  • Sherif, V. (2018). Evaluating preexisting qualitative research data for secondary analysis. Forum: Qualitative Social Research, 19(2), 26-42.
  • Skryabin, M., Zhang, J., Liu, L., & Zhang, D. (2015). How the ICT development level and usage influence student achievement in reading, mathematics, and science. Computers & Education, 85, 49-58. doi:10.1016/j.compedu.2015.02.004
  • Šorgo, A., Verčkovnik, T., & Kocijančič, S. (2010). Information and communication technologies (ICT) in biology teaching in Slovenian secondary schools. Eurasia Journal of Mathematics, Science and Technology Education, 6(1), 37-46. doi:10.12973/ejmste/75225
  • Srijamdee, K., & Pholphirul, P. (2020). Does ICT familiarity always help promote educational outcomes? Empirical evidence from PISA-Thailand. Education and Information Technologies, 25, 2933-2970. doi:10.1007/s10639-019-10089-z10.1080/10723030802533853
  • Streiner, D. L. (2003). Starting at the beginning: an introduction to coefficient alpha and internal consistency. Journal of personality assessment, 80(1), 99-103. doi:10.1207/S15327752JPA8001_18
  • Suna, H. E., Tanberkan, H., Taş, U. E., Eroğlu, E., & Altun, Ü. (2019). PISA 2018 Türkiye ön raporu. Ankara: T.C. Millî Eğitim Bakanlığı
  • Thamarana, S. (2015). The role of information and communication technologies in achieving standards in English language teaching. The Criterion: An International Journal in English, 6(4), 227-232.
  • Tomul, E. (2007). Türkiye’de eğitime katılım üzerinde gelirin etkisi. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi, 2(22), 122-131.
  • Tondeur, J., Van Braak, J., & Valcke, M. (2007). Curricula and the use of ICT in education: Two worlds apart?. British Journal of Educational Technology, 38(6), 962-976. doi:10.1111/j.1467-8535.2006.00680.x
  • Turner, P. D. (1997, March, 24-28). Secondary analysis of qualitative data. Annual Meeting of the American Educational Research Association, Chicago, IL, USA.
  • Volman, M., Van Eck, E., Heemskerk, I., & Kuiper, E. (2005). New technologies, new differences. Gender and ethnic differences in pupils' use of ICT in primary and secondary education. Computers & Education, 45(1), 35-55. doi:10.1016/j.compedu.2004.03.001
  • York, T. T., Gibson, C. ve Rankin, S. (2015). Defining and measuring academic success. Practical Assessment, Research, and Evaluation, 20(1), 1-20. doi:10.7275/hz5x-tx03
Toplam 65 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Umut Birkan Özkan 0000-0001-8978-3213

Yayımlanma Tarihi 2 Ocak 2022
Gönderilme Tarihi 23 Aralık 2020
Kabul Tarihi 27 Ağustos 2021
Yayımlandığı Sayı Yıl 2022 Sayı: 54

Kaynak Göster

APA Özkan, U. B. (2022). Türkiye’deki Öğrencilerin Matematik Başarısının Belirleyicileri: Bilgi ve İletişim Teknolojilerine Aşinalık Değişkenlerine İlişkin Bir Analiz. Pamukkale Üniversitesi Eğitim Fakültesi Dergisi(54), 272-296. https://doi.org/10.9779/pauefd.845834