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• Sources marked with an asterisk (*) indicate studies included in the meta-analysis.
• *Abrams, L. M., Varier, D., & Mehdi, T. (2021). The intersection of school context and teachers’ data use practice: Implications for an integrated approach to capacity building. Studies in Educational Evaluation, 69, 1-13. https://doi.org/10.1016/j.stueduc.2020.100868
• Açıkel, C. (2009). Meta-analysis and its place in evidence based medicine. Bulletin of Clinical Psychopharmacology,19(2), 164-172.
• Albrect, N., Lou, M., & Neill, S. (2014). The importance of data literacy in leadership education: Factors related to data use in instructional leadership. 03 June 2014, 10th International Academic Conference, Vienna.
• Athanases, S., Wahleithner, J., & Bennett, L. (2012). Learning to attend to culturally and linguistically diverse learners through teacher inquiry in teacher education. Teachers College Record, 114(7), 1-50.
• Barutçugil, İ. (2002). Bilgi yönetimi. Kariyer Publishing
• Başol, G., & Johanson, G. (2009). Effectiveness of frequent testing over achievement: A meta-analysis study. International Journal of Human Sciences, 6(2), 99-121.
• Bernhardt, V. L. (2009). Data use: Data-driven decision making takes a big-picture view of the needs of teachers and students. Journal of Staff Development, 30(1), 24-27.
• *Bettesworth, L. R. (2006). Administrators' use of data to guide decision-making. [Doctoral dissertation]. University of Oregon, Eugene, OR. Borenstein, M., Hedges, L.V., Higgins, J.P.T., & Rothstein H. (2013). Comprehensive meta-analysis. Englewood, NJ: Biostat.
• Carey, M., Grainger, P., & Christie, M. (2018). Preparing preservice teachers to be data literate: a queensland case study. Asia-Pacific Journal of Teacher Education, 46(3), 267-278. https://doi.org/10.1080/1359866X.2017.1402860
• Childress, M. (2009). Data-driven decision making: The development and validation of an instrument to measure principals’ practices. Academic Leadership: The Online Journal, 7(1), 67-75.
• Coburn, C. E., & Turner, E. O. (2011). Research on data use: A framework and analysis. Measurement: Interdisciplinary Research & Perspective, 9(4), 173–206. https://doi.org/10.1080/15366367.2011.626729
• Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New York: Academic Pres.,
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• Cowie, B., & Cooper, B. (2017). Exploring the challenge of developing student teacher data literacy. Assessment in Education: Principles, Policy and Practice, 24(2), 147-163. https://doi.org/10.1080/0969594X.2016.1225668
• Cumming, G. (2012). Understanding the new statistics. New York: Routledge, Taylor and Francis Group.
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• Darling-Hammond, L., & Orphanos, S. (2006). Leadership development in California. Retrieved from https://cepa.stanford.edu/sites/default/files/12-Darling-Hammond%283-07%29.pdf
• Datnow, A., Park, V., & Wohlstetter, P. (2007). Achieving with data: How highperforming school systems use data to improve instruction for elementary students. Los Angeles, CA: Center on Educational Governance, Rossier School of Education, University of Southern California.
• Dejear, M. L. (2016). A study of how culture, collaboration, and advocacy influence data-driven decision making at community colleges. [Doctor of philosophy]. Iowa State University, Ames, Iowa.
• DeLuca, C., & Bellara, A. (2013). The current state of assessment education aligning policy, standards, and teacher education curriculum. Journal of Teacher Education, 64(4), 356-372. https://doi.org/10.1177/0022487113488144
• Doğan, E. (2021). Evaluating the data-driven decision making process in school management according to the views of the administrators. [Unpublished doctoral dissertation]. Gazi University, Ankara.
• Dunn, K., Airola, D., Lo, W., & Garrison, M. (2013). What teachers think about what they can do with data: Development and validation of the data driven decision-making efficacy and anxiety inventory. Contemporary Educational Psychology, 38(1), 87-98. http://dx.doi.org/10.1016/j.cedpsych.2012.11.002
• Earl, L., & Katz, S. (2002). Leading schools in a data rich world. In K. Leithwood and P. Hallinger (Eds.), Second international handbook of educational leadership and administration. Kluwer.
• *Ebbeler, J., Poortman, C., Schildkamp, K., & Pieters, J. (2016). The effects of a data use intervention on educators’ satisfaction and data literacy. Educational Assessment, Evaluation and Accountability, 29(1), 83-105. https://link.springer.com/article/10.1007/s11092-016-9251-z
• Edwards, J., Lyons, C., & Jost, M. L. (1997). Quality instruction based on data to better meet student needs. Paper presented at the Annual Meeting of the American Educational Research Association (March 24-28). ERIC Document Reproduction NO. ED440119.
• Ellis, P. D. (2010). The essential guide to effect sizes: Statistical power, meta-analysis, and the interpretation of research results. Cambridge: Cambridge University Press.
• Faber, J. M., & Visscher, A. J. (2014). Digitale leerlingvolgsystemen: Een review van de effecten op leerprestaties. 4W. Retrieved from http://www.kennisnet.nl/onder zoek/alle-onderzoeken/digitale-leerlingvolgsystemen-een-review-van-deeffecten-op-leerprestaties/
• Farley-Ripple, E., & Buttram, J. (2014). Developing collaborative data use through professional learning communities: Early lessons from Delaware. Studies in Educational Evaluation, 42, 41–53. http://dx.doi.org/10.1016%2Fj.stueduc.2013.09.006
• Feldman, J. & Tung, R. (2001). Whole school reform: how schools use the data-based inquiry and decision-making process. Seattle, WA: American Educational Research Association.
• Gambell, T. (2004). Teachers working around large-scale assessment: Reconstructing professionalism and professional development. English Teaching: Practice and Critique, 3(2), 48-73.
• Gesel, S. A., LeJeune, L. M., Chow, J. C., Sinclair, A. C., & Lemons, C. J. (2020). A meta-analysis of the impact of professional development on teachers’ knowledge, skill, and self-efficacy in data-based decision-making. Journal of Learning Disabilities, 1–15. https://doi.org/10.1177/0022219420970196
• *Green, J. L., Schmitt-Wilson, S., Versland, T., Kelting-Gibson, L., & Nollmeyer, G. E. (2016). Teachers and data literacy: A blueprint for professional development to foster data driven decision making. Journal of Continuing Education and Professional Development, 3(1), 14-32. http://dx.doi.org/10.7726/jcepd.2016.1002
• Gummer, E., & Mandinach, E. (2015). Building a conceptual framework for data literacy. Teachers College Record, 117(4), 1-22.
• Harris, N. (2011). The impact of professional development in data-based decision making on the teaching practices of educators. [Doctoral dissertation]. Walden University College of Education, Walden.
• Hunter, J. E., & Schmidt, F. L. (1990). Methods of meta-analysis: Correcting error and bias in research findings. Thousand Oaks, CA, US: Sage Publications, Inc.
• Jacobs, J., Gregory, A., Hoppey, D., & Yendol-Hoppey, D. (2009). Data literacy: Understanding teachers' data use in a context of accountability and response to intervention. Action in Teacher Education, 31(3), 41-55. https://doi.org/10.1080/01626620.2009.10463527
• *Jimenez, B. A., Mims, P. J., & Browder, D. M. (2012). Data-based decisions guidelines for teachers of students with severe ıntellectual and developmental disabilities. Education and Training in Autism and Developmental Disabilities, 47(4), 407–413.
• Johnson, T. (2015). Professional development effects on teachers’ perceptions in analyzing and using student data. [Doctoral dissertation]. Walden University College of Education, USA.
• Jung, P. G., McMaster, K. L., Kunkel, A., Shin, J., & Stecker, P. M. (2018). Effects of data-based individualization for students with intensive learning needs: A meta-analysis. Learning Disabilities Research & Practice, 33(3), 144–155. https://doi.org/gd4g8m
• Kerr, K. A., Marsh, J. A., Ikemoto, G. S., Darilek, H., & Barney, H. (2006). Strategies to promote data use for instructional improvement: actions, outcomes, and lessons from three urban districts. American Journal of Education, 112(4), 496-520.
• Keuning, T., Van Gell, M., & Visscher, A. (2017). Why a Data-Based Decision-Making Intervention Works in Some Schools and Not in Others. Learning Disabilities Research & Practice, 32(1), 1–14. http://dx.doi.org/10.1111/ldrp.12124
• Killion, J., & Bellamy, G. T. (2000). On the job: Data analysts focus school improvement efforts. Journal of Staff Development, 21(1), 27-31. Khan, H. R., Kim, J., & Chang, C. H. (2018). Toward an understanding of data literacy. http://hdl.handle.net/2142/100243
• *Kippers, W. B., Poortman, C. L., Schildkamp, K., & Visscher, A. J. (2018). Data literacy: What do educators learn and struggle with during a data use intervention? Studies in Educational Evaluation, 56, 31-21. https://doi.org/10.1016/j.stueduc.2017.11.001
• LaPointe-McEwan, D., DeLuca, C., & Klinger, D. (2017). Supporting evidence use in networked professional learning: the role of the middle leader. Educational Research, 59(2), 136-153. https://doi.org/10.1080/00131881.2017.1304346
• Lange, C., Range, B., & Welsh, K. (2012). Conditions for effective data use to improve schools: Recommendations for school leaders. International Journal of Educational Leadership Preparation, 7(3), 1-11.
• Levin, J. A., & Datnow, A. (2012). The principal role in data driven decision making: Using case study data to develop multimediator models of educational reform. School Effectiveness and School Improvemenet, 23(2), 179-201. http://dx.doi.org/10.1080/09243453.2011.599394
• Luo, M., Albrecht, N., & Neill, S. (2015). Factors related to data use in instructional leadership: The importance of data literacy in leadership education. International Journal of Teaching and Education, 3(1), 24-44.
• Mandinach, E. B., & Gummer, E. S. (2013). A systemic view of implementing data literacy in educator preparation. Educational Researcher, 42(1), 30-37. http://dx.doi.org/10.3102/0013189X12459803
• Mandinach, E. B., & Gummer, E. S. (2016). What does it mean for teachers to be data literate: Laying out the skills, knowledge, and dispositions. Teaching and Teacher Education, 60. http://dx.doi.org/10.1016/j.tate.2016.07.011
• Mandincah, E.B., Honey, M., & Light, D. (2006). A theoretical framework for datadriven decision making. Paper presented at the Annual Meeting of AERA, CA.
• Marsh, J. A., Pane, J. F., & Hamilton, L. S. (2006). Santa Monica, CA: https://www.rand.org/content/dam/rand/pubs/occasional_papers/2006/RAND_OP170.
• Mason, S. A. (2003). Learning from data: The role ofprofessional learning communities. Paper presented at the annual meeting of the American Educational Research Association, Chicago, IL.
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• Niemeyer, K. D. (2012). Data driven decision making in schools: The influence of professional development on educator perceptions. [Doctoral dissertation]. The University of Memphis.
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• Piro, J., & Hutchinson, C. (2014). Using a data chat to teach instructional interventions: student perceptions of data literacy in an assessment course. The New Educator, 10(2), 95-111. http://dx.doi.org/10.1080/1547688X.2014.898479
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• Reeves, T. D., & Honig, S. L. (2015). A classroom data literacy intervention for pre-service teachers. Teaching and Teacher Education, 50(1), 90-101. http://dx.doi.org/10.1016/j.tate.2015.05.007
• Rogers, M. A. (2015). A developmental study examining the value, effectiveness, and quality of a data literacy intervention. [Doctoral dissertation]. University of Iowa, Iowa.
• *Rotondi, M. (2017). Teacher perception of data-driven instruction and collective decision making. [Master thesis]. California State University, Fresno.
• Schildkamp, K., & Kuiper, W. (2010). Data-informed curriculum reform: Which data, what purposes, and promoting and hindering factors. Teaching and Teacher Education, 26(3), 482-496. http://dx.doi.org/10.1016/j.tate.2009.06.007
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