Eurasia Journal of Mathematics, Science and Technology Education

• Arifin, Z., Saputro, S., & Kamari, A. (2025). The effect of inquiry-based learning on students’ critical thinking skills in science education: A systematic review and meta-analysis. Eurasia Journal of Mathematics, Science and Technology Education, 21(3), Article em2592. https://doi.org/10.29333/ejmste/15988
• Barker, T. H., Habibi, N., Aromataris, E., Stone, J. C., Leonardi-Bee, J., Sears, K., Hasanoff, S., Klugar, M., Tufanaru, C., Moola, S., & Munn, Z. (2024). The revised JBI critical appraisal tool for the assessment of risk of bias for quasi-experimental studies. JBI Evidence Synthesis, 22(3), 378-388. https://doi.org/10.11124/jbies-23-00268
• Borenstein, M. (2022). In a meta-analysis, the I-squared statistic does not tell us how much the effect size varies. Journal of Clinical Epidemiology, 152, 281-284. https://doi.org/10.1016/j.jclinepi.2022.10.003
• Bozorgian, H., & Shamsi, E. (2025). A review of research on metacognitive instruction for listening development. International Journal of Listening, 39(1), 1-16. https://doi.org/10.1080/10904018.2023.2197008
• Brown, A. L. (1987). Metacognition, executive control, self-regulation, and other more mysterious mechanisms. In F. E. Weinert, & R. H. Kluwe (Eds.), Metacognition, motivation, and understanding (pp. 65-116). Lawrence Erlbaum. https://doi.org/10.4324/9781003758167-5
• Cardelle-Elawar, M. (1995). Effects of metacognitive instruction on low achievers in mathematics problems. Teaching and Teacher Education, 11(1), 81-95. https://doi.org/10.1016/0742-051X(94)00019-3
• Cheung, A. C. K., & 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
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum.
• de Boer, H., Donker, A. S., Kostons, D. D., & van der Werf, G. P. (2018). Long-term effects of metacognitive strategy instruction on student academic performance: A meta-analysis. Educational Research Review, 24, 98-115. https://doi.org/10.1016/j.edurev.2018.03.002
• Donker, A. S., de Boer, H., Kostons, D., Dignath van Ewijk, C. C., & van der Werf, M. P. C. (2014). Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Educational Research Review, 11, 1-26. https://doi.org/10.1016/j.edurev.2013.11.002
• Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive-developmental inquiry. American Psychologist, 34(10), 906-911. https://doi.org/10.1037/0003-066X.34.10.906
• Fono, D., & Zohar, A. (2025). Metacognitive instruction: Central aspects of pre-service and novice in-service teachers’ knowledge and professional development. Professional Development in Education, 51(8), 1766-1789. https://doi.org/10.1080/19415257.2024.2409779
• Guo, L. (2022). Using metacognitive prompts to enhance self-regulated learning and learning outcomes: A meta-analysis of experimental studies in computer-based learning environments. Journal of Computer Assisted Learning, 38(3), 811-832. https://doi.org/10.1111/jcal.12650
• Gutierrez de Blume, A. P. G. (2022). Calibrating calibration: A meta-analysis of learning strategy instruction interventions to improve metacognitive monitoring accuracy. Journal of Educational Psychology, 114(4), 681-700. https://doi.org/10.1037/edu0000674
• Hidayat, R., Mohd Saad, M. R., & Wewe, M. (2025). A meta-analysis of the effect of metacognitive instruction on mathematics achievement. Cogent Education, 12(1), Article 2517510. https://doi.org/10.1080/2331186X.2025.2517510
• Hidayat, R., Syed Zamri, S. N. A., & Zulnaidi, H. (2018). Does mastery of goal components mediate the relationship between metacognition and mathematical modelling competency? Educational Sciences: Theory and Practice, 18(3), 579-604. https://doi.org/10.12738/estp.2018.3.0108
• Kramarski, B., & Mevarech, Z. R. (2003). Enhancing mathematical reasoning in the classroom: The effects of cooperative learning and metacognitive training. American Educational Research Journal, 40(1), 281-310. https://doi.org/10.3102/00028312040001281
• Kramarski, B., Mevarech, Z. R., & Arami, M. (2002). The effects of metacognitive instruction on solving mathematical authentic tasks. Educational Studies in Mathematics, 49(2), 225-250. https://doi.org/10.1023/A:1016282811724
• Lee, Y., Capraro, M. M., Capraro, R. M., & Bicer, A. (2018). A meta-analysis: Improvement of students’ algebraic reasoning through metacognitive training. International Education Studies, 11(10), 42-49. https://doi.org/10.5539/ies.v11n10p42
• Lucangeli, D., Fastame, M. C., Pedron, M., Porru, A., Duca, V., Hitchcott, P. K., & Penna, M. P. (2019). Metacognition and errors: The impact of self-regulatory trainings in children with specific learning disabilities. ZDM Mathematics Education, 51, 577-585. https://doi.org/10.1007/s11858-019-01044-w
• Mansilla, N. C., Aravena Díaz, M. D., & Berres, S. (2025). Metacognitive strategies in mathematical modelling: A case study with engineering students. International Journal of Mathematical Education in Science and Technology, 56(11), 2212-2235. https://doi.org/10.1080/0020739X.2024.2404421
• Mevarech, Z. R., & Kramarski, B. (1997). Improve: A multidimensional method for teaching mathematics in heterogeneous classrooms. American Educational Research Journal, 34(2), 365-394. https://doi.org/10.3102/00028312034002365
• Miller, A. H., Espinas, D. R., McNeish, D., & Barnes, M. A. (2025). Dosage response in intensive mathematics interventions for early elementary students with or at-risk for mathematics learning disability. Educational Psychology Review, 37(4), Article 91. https://doi.org/10.1007/s10648-025-10070-y
• Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4, Article 1. https://doi.org/10.1186/2046-4053-4-1
• Montague, M., Enders, C., & Dietz, S. (2011). Effects of cognitive strategy instruction on math problem solving of middle school students with learning disabilities. Learning Disability Quarterly, 34(4), 262-272. https://doi.org/10.1177/0731948711421762
• Muncer, G., Higham, P. A., Gosling, C. J., Cortese, S., Wood-Downie, H., & Hadwin, J. A. (2022). A meta-analysis investigating the association between metacognition and math performance in adolescence. Educational Psychology Review, 34, 301-334. https://doi.org/10.1007/s10648-021-09620-x
• Nakagawa, S., Yang, Y., Macartney, E. L., Spake, R., & Lagisz, M. (2023). Quantitative evidence synthesis: A practical guide on meta-analysis, metaregression, and publication bias tests for environmental sciences. Environmental Evidence, 12, Article 8. https://doi.org/10.1186/s13750-023-00301-6
• Neethirajan, S., Tuteja, S. K., Huang, S.-T., & Kelton, D. (2005). Publication bias in meta-analysis. In H. R. Rothstein, A. J. Sutton, & M. Borenstein (Eds.), Biosensors and bioelectronics (vol. 98). Wiley. https://doi.org/10.1002/0470870168
• Nelson, G., & McMaster, K. L. (2019). The effects of early numeracy interventions for students in preschool and early elementary: A meta-analysis. Journal of Educational Psychology, 111(6), 1001-1022. https://doi.org/10.1037/edu0000334
• Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 8. https://doi.org/10.3389/fpsyg.2017.00422
• Qudratuddarsi, H., Hidayat, R., Shah, R. L. Z. b. R. M., Nasir, N., Imami, M. K. W., & Nor, R. b. M. (2022). Rasch validation of instrument measuring gen-Z science, technology, engineering, and mathematics (STEM) application in teaching during the pandemic. International Journal of Learning, Teaching and Educational Research, 21(6), 104-121. https://doi.org/10.26803/ijlter.21.6.7
• Ran, H., Kim, N. J., & Secada, W. G. (2022). A meta-analysis on the effects of technology’s functions and roles on students’ mathematics achievement in K-12 classrooms. Journal of Computer Assisted Learning, 38(1), 258-284. https://doi.org/10.1111/jcal.12611
• Rojo, M., Gersib, J., Powell, S. R., Shen, Z., King, S. G., Akther, S. S., Arsenault, T. L., Bos, S. E., Lariviere, D. O., & Lin, X. (2024). A meta-analysis of mathematics interventions: Examining the impacts of intervention characteristics. Educational Psychology Review, 36(1), Article 9. https://doi.org/10.1007/s10648-023-09843-0
• Ropovik, I., Adamkovic, M., & Greger, D. (2021). Neglect of publication bias compromises meta-analytic of educational research. PLoS ONE, 16(6), Article Article e0252415. https://doi.org/10.1371/journal.pone.0252415
• Schneider, W., & Artelt, C. (2010). Metacognition and mathematics education. ZDM Mathematics Education, 42, 149-161. https://doi.org/10.1007/s11858-010-0240-2
• Schoenfeld, A. H. (1985). Mathematical problem solving. Academic Press.
• Schraw, G., & Moshman, D. (1995). Metacognitive theories. Educational Psychology Review, 7(4), 351-371. https://doi.org/10.1007/BF02212307
• Sercenia, J. C., & Prudente, M. S. (2023). Effectiveness of the metacognitive-based pedagogical intervention on mathematics achievement: A meta-analysis. International Journal of Instruction, 16(4), 561-578. https://doi.org/10.29333/iji.2023.16432a
• Shilo, A., & Kramarski, B. (2018). Mathematical-metacognitive discourse: How can it be developed among teachers and their students? Empirical evidence from a videotaped lesson and two case studies. ZDM Mathematics Education, 51, 625-640. https://doi.org/10.1007/s11858-018-01016-6
• Sterne, J. A. C., Sutton, A. J., Ioannidis, J. P. A., Terrin, N., Jones, D. R., Lau, J., Carpenter, J., Rucker, G., Harbord, R. M., Schmid, C. H., Tetzlaff, J., Deeks, J. J., Peters, J., Macaskill, P., Schwarzer, G., Duval, S., Altman, D. G., Moher, D., & Higgins, J. P. T. (2011). Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ, 343, Article d4002. https://doi.org/10.1136/bmj.d4002
• Stojanović, E., Ristić, V., McMaster, D. T., & Milanović, Z. (2016). Effect of plyometric training on vertical jump performance in female athletes: A systematic review and meta-analysis. Sports Medicine, 47(5), 975-986. https://doi.org/10.1007/s40279-016-0634-6
• Turmuzi, M., & Lu’luilmaknun, U. (2023). The impact of online learning on the mathematics learning process in Indonesia: A meta-analysis. Journal of Technology and Science Education, 13(3), 694-717. https://doi.org/10.3926/jotse.2138
• Turner, R. M., Bird, S. M., & Higgins, J. P. T. (2013). The impact of study size on meta-analyses: Examination of underpowered studies in Cochrane reviews. PLoS ONE, 8(3), Article e59202. https://doi.org/10.1371/journal.pone.0059202
• Xie, Y., Zeng, F., & Yang, Y. (2024). A meta-analysis of the relationship between metacognition and academic achievement in mathematics: From preschool to university. Acta Psychologica, 249, Article 104486. https://doi.org/10.1016/j.actpsy.2024.104486
• Zhang, Q. I., Hu, J., Wei, L., Cao, R. I., Ma, R., Song, H., & Jin, Y. I. (2019). Effects of traditional Chinese exercise on cognitive and psychological outcomes in older adults with mild cognitive impairment: A systematic review and meta-analysis. Medicine, 98(7), Article e14581. https://doi.org/10.1097/md.0000000000014581
• Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166-183. https://doi.org/10.3102/0002831207312909
• Zohar, A., & Ben-David, A., 2008. Explict teaching of meta-strategic knowledge in authentic classroom settings. Metacognition Learning, 3(1), 59-82. https://doi.org/10.1007/s11409-007-9019-4

APA

Hidayat, R., Zetriuslita, Sudirman, & Wardat, Y. (2026). Evaluating the effect of metacognitive instruction on mathematics achievement: A meta-analysis. Eurasia Journal of Mathematics, Science and Technology Education, 22(12), em2967. https://doi.org/10.29333/ejmste/19955

Vancouver

Hidayat R, Zetriuslita, Sudirman, Wardat Y. Evaluating the effect of metacognitive instruction on mathematics achievement: A meta-analysis. EURASIA J Math Sci Tech Ed. 2026;22(12):em2967. https://doi.org/10.29333/ejmste/19955

AMA

Hidayat R, Zetriuslita, Sudirman, Wardat Y. Evaluating the effect of metacognitive instruction on mathematics achievement: A meta-analysis. EURASIA J Math Sci Tech Ed. 2026;22(12), em2967. https://doi.org/10.29333/ejmste/19955

Chicago

Hidayat, Riyan, Zetriuslita, Sudirman, and Yousef Wardat. "Evaluating the effect of metacognitive instruction on mathematics achievement: A meta-analysis". Eurasia Journal of Mathematics, Science and Technology Education 2026 22 no. 12 (2026): em2967. https://doi.org/10.29333/ejmste/19955

Harvard

Hidayat, R., Zetriuslita, Sudirman, and Wardat, Y. (2026). Evaluating the effect of metacognitive instruction on mathematics achievement: A meta-analysis. Eurasia Journal of Mathematics, Science and Technology Education, 22(12), em2967. https://doi.org/10.29333/ejmste/19955

MLA

Hidayat, Riyan et al. "Evaluating the effect of metacognitive instruction on mathematics achievement: A meta-analysis". Eurasia Journal of Mathematics, Science and Technology Education, vol. 22, no. 12, 2026, em2967. https://doi.org/10.29333/ejmste/19955