The Impact of ICT Self-Efficacy and Subject-Oriented ICT Use During Lessons on Mathematics Achievement: A PISA 2022 Türkiye Sample

Elif Nur BOZER ÖZSARAÇ

  • Elif Nur BOZER ÖZSARAÇ: SELÇUK ÜNİVERSİTESİ
  • Year : 2026
  • Vol : 4
  • Issue : 1
  •  Page : 10-25
This study aims to investigate the impact of students' Information and Communication Technology (ICT) self-efficacy (ICTEFFIC) and subject-related ICT use during lessons (ICTSUBJ) on mathematics achievement. Framed within Self-Determination Theory and ICT Engagement Theory, this quantitative secondary data analysis is based on a sample of 6,599 15-year-old students (3,286 males, 3,313 females) from the Program for International Student Assessment (PISA) 2022 Turkey cohort. Data were analyzed using multiple regression analysis based on 10 pooled plausible values in accordance with Rubin's rules, while controlling for socioeconomic status and gender, and employing robust standard errors to account for heteroscedasticity. The findings revealed that even when ESCS and gender were held constant, both ICT self-efficacy and subject-related ICT use significantly and positively predicted mathematics achievement. The regression model explained 15.6% of the variance in mathematics performance. Comparative results demonstrated that pedagogical, subject-related ICT use (B = 12.109, β = 0.146) had approximately twice the predictive power on mathematics achievement compared to digital self-efficacy (B = 6.284, β = 0.080). Furthermore, socioeconomic status was confirmed as the strongest predictor in the model. Regarding gender, although male students scored statistically higher on ICT variables, the effect sizes (Cohen's d) indicating practical significance remained at a negligible level. In conclusion, this study demonstrates that students’ mere psychological competence (self-efficacy) is not solely sufficient for digital technologies to positively contribute to academic achievement. For academic benefit, it is imperative that this digital belief translates into action through curriculum-integrated, teacher-guided, and pedagogically purposeful use in the classroom environment.
Cite this Article As : Bozer Özsaraç, E. N. (2026). The impact of ICT self-efficacy and subject-oriented ICT use during lessons on mathematics achievement: A PISA 2022 Türkiye sample. Edutech Research, 4(1), 10-25. https://doi.org/10.69991/EduRes.2026.7

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Conflict of interest : The authors declare that they have no conflict of interest.
Edutech Research
2026, Vol. 4 (1)
E-ISSN: 3023-6665
Received : , Accepted : , Published Online :

References

  1. Acun Celik, S., Ozkan Elgun, I., & Kalelioğlu, F. (2024). Assessment of student ICT competence according to mathematics, science, and reading literacy: Evidence from PISA 2018. Large-scale Assessments in Education, 12, 18. https://doi.org/10.1186/s40536-024-00218-7
  2. Areepattamannil, S., & Santos, I. M. (2019). Adolescent students’ perceived information and communication technology (ICT) competence and autonomy: Examining links to dispositions toward science in 42 countries. Computers in Human Behavior, 98, 50-58.
  3. Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
  4. Biagi, F., & Loi, M. (2013). Measuring ICT use and learning outcomes: Evidence from recent econometric studies. European Journal of Education, 48(1), 28-42.
  5. 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. https://www.learntechlib.org/primary/p/178514/
  6. Caponera, E., Colonnello, V., Annunziata, F., Palmerio, L., & Russo, P. M. (2026). Digital literacy and ICT use: key predictors of mathematics achievement in schoolchildren. European Journal of Psychology of Education, 41(1), 14.
  7. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.
  8. Courtney, M., Karakus, M., Ersozlu, Z., & Nurumov, K. (2022). The influence of ICT use and related attitudes on students’ math and science performance: Multilevel analyses of the last decade’s PISA surveys. Large-Scale Assessments in Education, 10(1), 8.
  9. Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum.
  10. Erdogdu, F., & Erdogdu, 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.
  11. Fayda‐Kinik, F. S., & Cetin, M. (2025). ICT and academic achievement in secondary education: A hierarchical linear modelling. Journal of Computer Assisted Learning, 41(1), e13070.
  12. Fraenkel, J. R., Wallen, N. E., & Hyun, H. H. (2012). How to design and evaluate research in education (8th ed.). McGraw-Hill.
  13. Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3-8.
  14. Goldhammer, F., Gniewosz, G., & Zylka, J. (2017). ICT engagement in learning environments. In S. Kuger, E. Klieme, N. Jude, & D. Kaplan (Eds.), Assessing contexts of learning (pp. 331-351). Springer International Publishing. https://doi.org/10.1007/978-3-319-45357-6_12
  15. Hatlevik, O. E., Scherer, R., & Christophersen, K. A. (2017). Moving beyond the study of gender differences: An analysis of measurement invariance and differential item functioning of an ICT literacy scale. Computers & Education, 113, 280-293.
  16. Hatlevik, O. E., Throndsen, I., Loi, M. & Gudmundsdottir, G. B. (2018). Students’ ICT self-efficacy and computer and information literacy: Determinants and relationships. Computers & Education, 118, 107-119.
  17. Hristov, M., Yada, T., Fagerlund, J., Näykki, P., & Häkkinen, P. (2025). Understanding the relationships among ICT use, self-efficacy, and achievement in PISA 2022: A multigroup analysis featuring gender and immigrant status. Computers & Education, 105539.
  18. 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.
  19. Johnston, M. P. (2014). Secondary data analysis: A method of which the time has come. Qualitative and quantitative methods in libraries, 3(3), 619-626.
  20. Karasar, N. (2020). Bilimsel araştırma yöntemi: Kavramlar, ilkeler, teknikler. Nobel Akademik Yayıncılık.
  21. 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. https://doi.org/10.1186/s40536-020-00084-z
  22. Li, S. C., & Zhu, J. (2023). Cognitive-motivational engagement in ICT mediates the effect of ICT use on academic achievements: Evidence from 52 countries. Computers & Education, 204, 104871.
  23. Odell, B., Cutumisu, M., & Gierl, M. (2020). A scoping review of the relationship between students' ICT and performance in mathematics and science in the PISA data. Social Psychology of Education, 23(6), 1449–1481. https://doi.org/10.1007/s11218-020-09591-x
  24. OECD. (2023). PISA 2022 results (Volume I): The state of learning and equity in education. OECD Publishing. https://doi.org/10.1787/53f23881-en
  25. OECD. (2024). PISA 2022 technical report. OECD Publishing. https://www.oecd.org/pisa/data/pisa2022technicalreport/
  26. Örnek, F., & Afari, E. (2026). Evaluating the effects of ICT engagement on science and mathematics achievement: Evidence from PISA 2022 using structural equation modeling. Studies in Educational Evaluation, 88, 101583.
  27. 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.
  28. 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.
  29. Rubin, D. (1987). Multiple Imputation for Nonresponse in Surveys, John Wiley and Sons.
  30. Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations: Classic definitions and new directions. Contemporary educational psychology, 25(1), 54-67.
  31. Ryan, R. M., & Deci, E. L. (2017). Self-determination theory: Basic psychological needs in motivation, development, and wellness. Guilford Press.
  32. Smith, E. (2008). Using secondary data in educational and social research. McGraw-Hill Education (UK).
  33. Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive science, 12(2), 257-285.
  34. Unal, E., Uzun, A. M., & Kilis, S. (2022). Does ICT involvement really matter? An investigation of Turkey's case in PISA 2018. Education and Information Technologies, 27, 11443–11465. https://doi.org/10.1007/s10639-022-11067-8
  35. Wang, Z., & Chu, Z. (2023). Examination of higher education teachers’ self-perception of digital competence, self-efficacy, and facilitating conditions: An empirical study in the context of China. Sustainability, 15(14), 10945.
  36. Wang, X. S., Perry, L. B., Malpique, A. & Ide, T. (2023). Factors predicting mathematics achievement in PISA: A systematic review. Large-scale Assessments in Education, 11(24). https://doi.org/10.1186/s40536-023-00174-8
  37. Wei, Y., & Zhang, Y. (2025). Exploration of factors affecting Australian students' mathematics grades: A multiple regression analysis based on PISA 2022 data. Frontiers in Psychology, 16, 1611350. https://doi.org/10.3389/fpsyg.2025.1611350
  38. 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 and Technology Education, 12(9), 2431–2449. https://doi.org/10.12973/eurasia.2016.1297a
  39. Zhu, J., & Li, S. C. (2022). The non-linear relationships between ICT use and academic achievement of secondary students in Hong Kong. Computers & Education, 187, 104546.
  40. Zylka, J., Christoph, G., Kroehne, U., Hartig, J., & Goldhammer, F. (2015). Moving beyond cognitive elements of ICT literacy: First evidence on the structure of ICT engagement. Computers in Human Behavior, 53, 149–160. https://doi.org/10.1016/j.chb.2015.07.008