•  
  •  
 

Document Type

Article

Abstract

This study uses a meta-analysis model to describe the relationship between self-assessment and achievement in learning mathematics. This meta-analysis covers articles published from 2011 to 2022 and is restricted to studies published in English. Indexed articles by Google Scholar were chosen. The data must meet these criteria: quantitative research, containing correlational research on the relationship between self-assessment and mathematics learning achievement (including correlation values and sample size). Through the data screening process with predetermined criteria, 12 research results were obtained, containing 43 studies to be analyzed. This meta-analysis uses a random effect model due to the heterogeneous data distribution. A publication bias test was carried out with the Fail-safe N model to ensure the quality of the data. The result of the analysis showed that the data distribution was heterogeneous, according to the I2 test, so selecting the random effect model was the right decision. Regarding publication bias, an accurate Fail-safe N test shows that the data are free from publication bias. Thus, the analysis uses a suitable model, and the results of the analysis can be trusted. The total effect size indicates a significant positive correlation (r = 0.295) between self-assessment and students' mathematics achievement. Therefore, the higher the self-assessment index, the higher one's mathematics learning achievement.

First Page

39

Last Page

51

Issue

1

Volume

27

Digital Object Identifier (DOI)

10.21831/pep.v27i1.60617

References

Ahmed, W., van der Werf, G., Kuyper, H., & Minnaert, A. (2013). Emotions, self-regulated leaming, and achievement in Mathematics: A growth curve analysis. Journal of Educational Psychology, 105(1), 150-161. https://doi.org/10.1037/a0030160

Altun, S., & Elden, M. (2013). Self-regulation based learning strategies and self-efficacy perceptions as predictors of male and female students' mathematics achievement. Procedia - Social and Behavioral Sciences, 106, 2354-2364. https://doi.org/10.1016/j.sbspro.2013.12.270

Andrade, H. L. (2019). A critical review of research on student self-assessment. Frontiers in Education, 4(August), 1-13. https://doi.org/10.3389/feduc.2019.00087

Arlinwibowo, J., Retnawati, H., & Kartowagiran, B. (2021). Item response theory utilization for developing the student collaboration ability assessment scale in STEM classes. Ingenierie des Systemes d'Information, 26(4), 409-415. https://doi.org/10.18280/ISI.260409

Arlinwibowo, J., Retnawati, H., & Kartowagiran, B. (2022). The impact of ICT utilization to improve the learning outcome: A meta-analysis. International Journal of Evaluation and Research in Education, 11(2), 522-531. https://doi.org/10.11591/ijere.v11i2.22112

Baiduri, B. (2022). Effect of self and peer assessments on mathematics learning achievement. Al-Jabar : Jurnal Pendidikan Matematika, 13(1), 13-21. https://doi.org/10.24042/ajpm.v13i1.10731

Beumann, S., & Wegner, S. A. (2018). An outlook on self-assessment of homework assignments in higher mathematics education. International Journal of STEM Education, 5(1), 1-7. https://doi.org/10.1186/s40594-018-0146-z

Brown, G. T. L., & Harris, L. R. (2013). Student self-assessment. In J. H. McMillan (Ed.), The SAGE handbook of research on classroom assessment (pp. 367-393). SAGE. https://doi.org/10.4135/9781452218649.n21

Brown, G. T. L., & Harris, L. R. (2014). The future of self-assessment in classroom practice: Reframing self-assessment as a core competency. Frontiers of Learning Research, 2(1), 22-30. https://doi.org/10.14786/flr.v2i1.24

Cabedo, J. D., & Maset-llaudes, A. (2019). How a formative self-assessment program positively influenced examination performance in financial mathematics. Innovations in Education and Teaching International, 57(6), 680-690. https://doi.org/10.1080/14703297.2019.1647267

Castro-Alonso, J. C., Wong, M., Adesope, O. O., Ayres, P., & Paas, F. (2019). Gender imbalance in instructional dynamic versus static visualizations: A meta-analysis. Educational Psychology Review, 31, 361-387. https://doi.org/10.1007/s10648-019-09469-1

Cooper, H. M., Valentine, J. C., & Hedges, L. V. (2009). Handbook of research synthesis and meta-analysis (2nd ed.). Russell Sage Foundation. https://www.jstor.org/stable/10.7758/9781610441384

Dent, A. L., & Koenka, A. C. (2016). The relation between self-regulated learning and academic achievement across childhood and adolescence: A meta-analysis. Educational Psychology Review, 28(3), 425-474. https://doi.org/10.1007/s10648-015-9320-8

Desoete, A., Roeyers, H., & De Clercq, A. (2001). Dynamic assessment of metacognitive skills in young children with mathematics-learning disabilities. In J. Carlson (Ed.), Potential assessment and cognitive training: Actual research and perspectives in theory building and methodology. JAI Press Inc./Elseiver.

Desoete, A. (2007). Evaluating and improving the mathematics teaching-learning process through metacognition. Electronic Journal of Research in Educational Psychology, 5(3), 705-730.

Fadlelmula, F. K., Cakiroglu, E., & Sungur, S. (2014). Developing a structural model on the relationship among motivational beliefs, self-regulated learning strategies, and achievement in Mathematics. International Journal of Science and Mathematics Education, 13, 1355-1375. https://doi.org/10.1007/s10763-013-9499-4

Krieglstein, F., Beege, M., Rey, G. D., Ginns, P., Krell, M., & Schneider, S. (2022). A systematic meta-analysis of the reliability and validity of subjective cognitive load questionnaires in experimental multimedia learning research. Educational Psychology Review, 34, 2485-2541. https://doi.org/10.1007/s10648-022-09683-4

Lai, C., & Hwang, G. (2016). A self-regulated flipped classroom approach to improving students' learning performance in a mathematics course. Computers & Education, 100 September, 126-140. https://doi.org/10.1016/j.compedu.2016.05.006

Li, Y. (2022). Statistical power analysis for the behavioral sciences. In B. B. Frey (Eds.), The SAGE encyclopedia of research design (2nd ed.). Lawrence Erlbaum Associates. https://doi.org/10.4135/9781071812082.n600

Martin-Martin, A., Orduna-Malea, E., Harzing, A. W., & López-Cózar, E. D. (2017). Can we use Google Scholar to identify highly-cited documents? Journal of Informetrics, 11(1), 152-163. https://doi.org/10.1016/j.joi.2016.11.008

McMillan, J. H. (2013). Classroom assessment. In J. H. McMillan (Ed.), SAGE handbook of research on classroom assessment, pp. 1-3. SAGE.

Ministry of Education and Culture. (2016). Panduan penilaian oleh pendidik dan satuan pendidikan untuk sekolah menengah pertama. Kementerian Pendidikan dan Kebudayaan. Retreived from http://ditpJHS.kemdikbud.go.id

Ministry of Education, Culture, Research, and Technology. (2021). Panduan pembelajaran dan asesmen (Jenjang pendidikan dasar dan menengah). Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi. https://kurikulum.kemdikbud.go.id/wp-content/uploads/2022/06/Panduan-Pembelajarn-dan-Asesmen.pdf

Nitko, A. J., & Brookhart, S. M. (2014). Educational assessment of students (6th ed.). Pearson Education, Inc.

Özsoy, G. & Ataman, A. (2009). The effect of metacognitive strategy training on problem solving achievement. International Electronic Journal of Elementary Education, 1(2), 67-82.

Özsoy, G., Memis, A., & Temur, T. (2009). Metacognition, study habits, and attitudes. International Electronic Journal of Elementary Education, 2(1), 154-166.

Özsoy, G. (2011). An investigation of the relationship between metacognition and mathematics achievement. Asia Pacific Education Review, 12, 227-235. https://doi.org/10.1007/s12564-010-9129-6

Özcan, Z. Ç. (2014). Assessment of metacognition in Mathematics: Which one of two methods is a better predictor of Mathematics achievement?. International Online Journal of Educational Sciences, 6(1), 49-57. https://iojes.net/?mod=makale_tr_ozet&makale_id=41068

Panadero, E., Brown, G., & Courtney, M. (2014). Teachers' reasons for using self-assessment: A survey self-report of Spanish teachers. Assessment in Education: Principles, Policy, and Practice, 21(4), 365-383. https://doi.org/10.1080/0969594X.2014.919247

Panadero, E., Jonsson, A., & Botella, J. (2017). Effects of self-assessment on self-regulated learning and self-efficacy: Four meta-analyses. Educational Research Review, 22, 74-98. https://doi.org/10.1016/j.edurev.2017.08.004

Popelka, E. (2015). Improving the accuracy of middle school students' self-assessment, peer assessment, and mathematics achievement. [Doctoral dissertation, University of Louisville]. https://doi.org/10.18297/etd/2324

Retnawati, H., Apino, E., Kartianom, K., Djidu, H., & Anazifa, R. D. (2018). Pengantar analisis meta. Parama Publishing.

Rosário, P., Núñez, J. C., Valle, A., & González-Pienda, J. (2013). Grade level, study time, and grade retention and their effects on motivation, self-regulated learning strategies, and mathematics achievement: A structural equation model. European Journal of Psychology of Education, 28, 1311-1331. https://doi.org/10.1007/s10212-012-0167-9

Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological Bulletin, 86(3), 638-641. https://doi.org/10.1037/0033-2909.86.3.638

Ross, J. A., Hogaboam-Gray, A., & Rolheiser, C. (2002). Student self-evaluation in grade 5-6 mathematics effects on problem- solving achievement. International Journal of Phytoremediation, 21(1), 43-58. https://doi.org/10.1207/S15326977EA0801_03

Schunk, D. H. (1996). Goal and self-evaluative influences during children's cognitive skill learning. American Educational Research Journal, 33(2), 359-382. https://doi.org/10.3102/00028312033002359

Setiadi, H. (2016). Pelaksanaan penilaian pada Kurikulum 2013. Jurnal Penelitian Dan Evaluasi Pendidikan, 20(2), 166-178. https://doi.org/10.21831/pep.v20i2.7173

Tian, Y., Fang, Y., Li, J., Wang, L., & Greenshaw, A. J. (2018). the effect of metacognitive knowledge on Mathematics performance in self-regulated learning framework €” Multiple mediation of self-efficacy and motivation. Front. Psychol., 9, 2518. https://doi.org/10.3389/fpsyg.2018.02518

Yan, Z. (2016). The self-assessment practices of Hong Kong secondary students: Findings with a new instrument. Journal of Applied Measurement, 17(3), 335-353.

Yan, Z., Wang, X., Boud, D., & Lao, H. (2021). The effect of self-assessment on academic performance and the role of explicitness: A meta-analysis. Assessment and Evaluation in Higher Education, 48(1), 1-15. https://doi.org/10.1080/02602938.2021.2012644

Youde, J. J. (2019). Meta-analysis of the effects of reflective self-assessment on academic achievement in primary and secondary populations. [Doctoral dissertation, Seattle Pacific University]. https://digitalcommons.spu.edu/soe_etd/48/

Zare, A., Heydari, H., Davoodi, H. & Kia, M. M. (2022). Modeling the effect of self-evaluation on the progress of second year high school students in mathematics with the mediation of self-regulation and mathematical self-efficacy. Journal of School Psychology and Institutions, 11(2), 62-70. https://dx.doi.org/10.22098/jsp.2022.1717

Zimmerman, B. J., Moylan, A., Hudesman, J., White, N., & Flugman, B. (2011). Enhancing self-reflection and mathematics achievement of at-risk urban technical college students. Psychological Test and Assessment Modeling, 53(1), 141-160. https://www.psychologie-aktuell.com/fileadmin/download/ptam/1-2011_20110328/07_Zimmermann.pdf

Share

COinS