The impact of formative assessment on K-12 learning: a meta-analysis

References

• Abrams, L. M., McMillan, J. H., & Wetzel, A. P. (2015). Implementing benchmark testing for formative purposes: teacher voices about what works. Educational Assessment, Evaluation, & Accountability, 27(4), 347–375. https://doi.org/10.1007/s11092-015-9214-9
   Web of Science ®Google Scholar
• Andrade, H. L. (2019). A critical review of research on student self-assessment. Frontiers in Education, 4, e00087. https://doi.org/10.3389/feduc.2019.00087
   Google Scholar
• Bennett, R. E. (2011). Formative assessment: A critical review. Assessment in Education: Principles, Policy & Practice, 18(1), 5–25. https://doi.org/10.1080/0969594X.2010.513678
   Google Scholar
• Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5(1), 7–74. https://doi.org/10.1080/0969595980050102
   Google Scholar
• Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation, & Accountability, 21(1), 5–31. https://doi.org/10.1007/s11092-008-9068-5
   Web of Science ®Google Scholar
• Borenstein, M., & Hedges, J. V. (2019). Effect sizes for meta-analysis. In H. Cooper, L. V. Hedges, & J. C. Valentine (Eds.), The handbook of research synthesis and meta-analysis (pp. 208–241). Russell Sage Foundation.
   Google Scholar
• Borenstein, M., Hedges, L. V., Higgins, J. P. T., & Rothstein, H. R. (2009). Introduction to meta-analysis. John Wiley & Songs.
   Google Scholar
• Brookhart, S. M., & Lazarus, S. (2017). Formative Assessment for Students with Disabilities.
   Google Scholar
• Burns, M. K., & Parker, D. C. (2014). Curriculum-based assessment for instructional design: Using data to individualize instruction. Guilford.
   Google Scholar
• Cheung, A. C., & Slavin, R. E. (2016). How methodological features affect effect sizes in education. Educational Researcher, 45(5), 283–292. https://doi.org/10.3102/0013189X16656615
   Web of Science ®Google Scholar
• Coffey, J. E., Hammer, D., Levin, D. M., & Grant, T. (2011). The missing disciplinary substance of formative assessment. Journal of Research in Science Teaching, 48(10), 1109–1136. https://doi.org/10.1002/tea.20440
   Web of Science ®Google Scholar
• Dalby, D., & Swan, M. (2019). Using digital technology to enhance formative assessment in mathematics classrooms. British Journal of Educational Technology, 50(2), 832–845. https://doi.org/10.1111/bjet.12606
   Web of Science ®Google Scholar
• Deci, E. L., & Ryan, R. M. (1985). Intrinsic motivation and self-determination in human behavior. Plenum Press. https://doi.org/10.1007/978-1-4899-2271-7
   Google Scholar
• Dignath, C., Buettner, G., & Langfeldt, H. P. (2008). How can primary school students learn self-regulated learning strategies most effectively? Educational Research Review, 3(2), 101–129. https://doi.org/10.1016/j.edurev.2008.02.003
   Web of Science ®Google Scholar
• Dignath, C., & Büttner, G. (2008). Components of fostering self-regulated learning among students: A meta-analysis on intervention studies at primary and secondary school level. Metacognition and Learning, 3(3), 231–264. https://doi.org/10.1007/s11409-008-9029-x
   Web of Science ®Google Scholar
• Double, K., McGrane, J., & Hopfenbeck, T. (2019). The impact of peer assessment on academic performance: A meta-analysis of control group studies. Educational Psychology Review, 32(2), 481–509. https://doi.org/10.1007/s10648-019-09510-3.
   Web of Science ®Google Scholar
• Fable, J. M., & Visscher, A. J. (2018). The effects of a digital formative assessment tool on spelling achievement: Results of a randomized experiment. Computers & Education, 122, 1–8. https://doi.org/10.1016/j.compedu.2018.03.008
   Web of Science ®Google Scholar
• Fisher, Z., & Tipton, E. (2015). Robumeta: An R-package for robust variance estimation in meta-analysis, https://arxiv.org/pdf/1503.02220.pdf
   Google Scholar
• Fisher, Z., Tipton, E., & Zhipeng, H. (2017). Robumeta (2.0) [Computer software]. https://cran.r-project.org/package = robumeta
   Google Scholar
• Fuchs, L. S., & Fuchs, D. (1986). Effects of systematic formative assessment: A meta-analysis. Exceptional Children, 53(3), 199–208. https://doi.org/10.1177/001440298605300301
   PubMed Web of Science ®Google Scholar
• Fuchs, L. S., Fuchs, D., & Compton, D. L. (2004). Monitoring early reading development in first grade: Word identification fluency versus nonsense word fluency. Exceptional Children, 71(1), 7–21. https://doi.org/10.1177/001440290407100101
   Web of Science ®Google Scholar
• Fuchs, L. S., Fuchs, D., & Hamlett, C. L. (1989). Computers and curriculum-based measurement: Effects of teacher feedback systems. School Psychology Review, 18(1), 112–125. https://doi.org/10.1080/02796015.1989.12085405
   Web of Science ®Google Scholar
• Gikandi, J. W., Morrow, D., & Davis, N. E. (2011). Online formative assessment in higher education: A review of the literature. Computer and Education, 57(4), 2333–2351. https://doi.org/10.1016/j.compedu.2011.06.004
   Web of Science ®Google Scholar
• Havnes, A., Smith, K., Dysthe, O., & Ludvigsen, K. (2012). Formative assessment and feedback: Making learning visible. Studies in Educational Evaluation, 38(1), 21–27. https://doi.org/10.1016/j.stueduc.2012.04.001
   Google Scholar
• Hedges, L. V. (1981). Distribution theory for Glass’s estimator of effect size and related estimators. Journal of Educational Statistics, 6(2), 107–128. https://doi.org/10.3102/10769986006002107
   Google Scholar
• Hedges, L. V. (2007). Effect sizes in cluster-randomized designs. Journal of Educational and Behavioral Statistics, 32(4), 341–370. https://doi.org/10.3102/1076998606298043
   Web of Science ®Google Scholar
• Hedges, L. V. (2011). Effect sizes in three-level cluster-randomized designs. Journal of Educational and Behavioral Statistics, 36(3), 346–380. https://doi.org/10.3102/1076998610376617
   Web of Science ®Google Scholar
• Hedges, L. V., & Hedberg, E. C. (2007). Intraclass correlations for planning group randomized trials in education. Educational Evaluation and Policy Analysis, 29(1), 60–87. https://doi.org/10.3102/0162373707299706
   Web of Science ®Google Scholar
• Hodgen, J., & Marshall, B. (2005). Assessment for learning in English and mathematics: A comparison. Curriculum Journal, 16(2), 153–176. https://doi.org/10.1080/09585170500135954
   Google Scholar
• Kelly, P., Andreasen, K. E., Kousholt, K., McNess, E., & Ydesen, C. (2018). Education governance and standardized tests in Denmark and England. Journal of Education Policy, 33(6), 739–758. https://doi.org/10.1080/02680939.2017.1360518
   Web of Science ®Google Scholar
• Kingston, N., & Nash, B. (2011). Formative assessment: A meta-analysis and a call for research. Educational Measurement: Issues and Practice, 30(4), 28–37. https://doi.org/10.1111/j.1745-3992.2011.00220.x
   Google Scholar
• Klute, M., Apthorp, H., Harlacher, J., & Reale, M. (2017). Formative assessment and elementary school student academic achievement: A review of the evidence (REL 2017-259). Washington, DC: Regional Educational Laboratory Central. https://ies.ed.gov/ncee/edlabs/regions/central/pdf/REL_2017259.pdf
   Google Scholar
• Lee, H., Chung, H. Q., Zhang, Y., Abedi, J., & Warschauer, M. (2020). The effectiveness and features of formative assessment in US K-12 education: A systematic review. Applied Measurement in Education, 33(2), 124–140. https://doi.org/10.1080/08957347.2020.1732383
   Web of Science ®Google Scholar
• Lyon, C. J., Wylie, E. C., Brockway, D., & Mavronikos, E. (2018). Formative assessment and the role of teachers’ content area. School Science and Mathematics, 118(5), 144–155. https://doi.org/10.1111/ssm.12277
   Web of Science ®Google Scholar
• Maier, U., Wolf, N., & Randler, C. (2016). Effects of a computer-assisted formative assessment intervention based on multiple-tier diagnostic items and different feedback types. Computers & Education, 95, 85–98. https://doi.org/10.1016/j.compedu.2015.12.002
   Web of Science ®Google Scholar
• Marshall, B., & Gibbons, S. (2018). Assessing English: A comparison between Canada and England’s assessment procedures. Education Sciences, 8(4), e211. https://doi.org/10.3390/educsci8040211
   Google Scholar
• McLaughlin, T., & Yan, Z. (2017). Diverse delivery methods and strong psychological benefits: A review of online formative assessment. Journal of Computer Assisted Learning, 33(6), 562–574. https://doi.org/10.1111/jcal.12200
   Web of Science ®Google Scholar
• Meusen-Beekman, K. D., Brinke, D. J., & Boshuizen, H. P. A. (2015). Developing young adolescents’ self-regulation by means of formative assessment: A theoretical perspective. Cogent Education, 2(1), 1–16. https://doi.org/10.1080/2331186X.2015.1071233
   Web of Science ®Google Scholar
• Militello, M., Schweid, J., & Sireci, S. G. (2010). Formative assessment systems: Evaluating the fit between school districts’ needs and assessment systems’ characteristics. Educational Assessment, Evaluation, & Accountability, 22(1), 29–52. https://doi.org/10.1007/s11092-010-9090-2
   Web of Science ®Google Scholar
• Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & Group, T. P. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097
   PubMed Web of Science ®Google Scholar
• Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199–218. https://doi.org/10.1080/03075070600572090
   Web of Science ®Google Scholar
• Niemiec, C. P., & Ryan, R. M. (2009). Autonomy, competence, and relatedness in the classroom: Applying self-determination theory to educational practice. Theory and Research in Education, 7(2), 133–144. https://doi.org/10.1177/1477878509104318
   Google Scholar
• Panadero, E., Brown, G. T. L., & Strijbos, J. (2016). The future of student self-assessment: A review of known unknowns and potential directions. Educational Psychological Review, 28(4), 803–830. https://doi.org/10.1007/s10648-015-9350-2
   Web of Science ®Google Scholar
• Paris, S. G., & Newman, R. S. (1990). Development aspects of self-regulated learning. Educational Psychologist, 25(1), 87–102. https://doi.org/10.1207/s15326985ep2501_7
   Web of Science ®Google Scholar
• Pigott, T. D., & Polanin, J. R. (2019). Methodological guidance paper: High-quality meta-analysis in a systematic review. Review of Educational Research, 90(1), 24–26. https://doi.org/10.3102/0034654319877153
   Web of Science ®Google Scholar
• Pustejovsky, J. E., & Rodgers, M. A. (2019). Testing for funnel plot asymmetry of standardized mean differences. Research Synthesis Methods, 10(1), 57–71. https://doi.org/10.1002/jrsm.1332
   PubMed Web of Science ®Google Scholar
• Ramaprasad, A. (1983). On the definition of feedback. Behavioral Science, 28(1), 4–13. https://doi.org/10.1002/bs.3830280103
   Google Scholar
• Rodgers, M. A., & Pustejovsky, J. E. (2020). Evaluating meta-analytic methods to detect selective reporting in the presence of dependent effect sizes. Psychological Methods, 26(2), 141–160. https://doi.org/10.1037/met0000300
   Web of Science ®Google Scholar
• Scriven, M. (1967). The Methodology of Evaluation. In R. Tyler, R. Gagné, & M. Scriven (Eds.), Perspectives of Curriculum Evaluation (AERA Monograph Series on Curriculum Evaluation, No. 1) (pp. 39–83). Rand McNally.
   Google Scholar
• Skopec, M., Issa, H., Reed, J., & Harris, M. (2020). The role of geographic bias in knowledge diffusion: A systematic review and narrative synthesis. Research Integrity and Peer Review, 5(1), 1–14. https://doi.org/10.1186/s41073-019-0088-0.
   PubMedGoogle Scholar
• Sweller, J. (1999). Instructional design in technical areas. Australian Council for Educational Research (No. 43). Victoria.
   Google Scholar
• Tanner-Smith, E., & Tipton, E. (2014). Robust variance estimation with dependent effect sizes: Practical considerations and a software tutorial in Stata and SPSS. Research Synthesis Methods, 5(1), 13–30. https://doi.org/10.1002/jrsm.1091
   PubMed Web of Science ®Google Scholar
• What Works Clearinghouse. (2020). WWC procedures handbook (version 4.1). https://ies.ed.gov/ncee/wwc/Docs/referenceresources/WWC-Procedures-Handbook-v4-1-508.pdf
   Google Scholar
• Wiliam, D. (2010). An integrative summary of the research literature and implications for a new theory of formative assessment. In H. Andrade, & G. J. Cizek (Eds.), Handbook of formative assessment (pp. 18–40). Routledge.
   Google Scholar
• Wiliam, D. (2011). What is assessment for learning? Studies in Educational Evaluation, 37(1), 3–14. https://doi.org/10.1016/j.stueduc.2011.03.001
   Google Scholar
• Wiliam, D. (2018). Feedback: At the heart of – But definitely not all of – Formative assessment. In A. Lipnevich, & J. Smith (Eds.), The Cambridge handbook of instructional feedback (pp. 3–28). Cambridge University Press. https://doi.org/10.1017/9781316832134.003
   Google Scholar
• Wisniewski, B., Zierer, K., & Hattie, J. (2020). The power of feedback revisited: A meta-analysis of educational feedback research. Frontiers in Psychology, 10, 3084–3087. https://doi.org/10.3389/fpsyg.2019.03087.
   PubMed Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar