[4] Blackwell, R. D., Miniard, P. W., & Engel, J. F. (2006). Consumer behavior. Harcourt College Publishers.
[8] Brown, C. (2017).
Research learning communities: How the RLC approach enables teachers to use research to improve their practice and the benefits for students that occur as a result. Research for All, 1(2), 387-405. |
DOI 10.18546/RFA.01.2.14
[9] Burgess, P. W., Alderman, N., Evans, J. O. N.. Emslie, H., & Wilson, B. A. (1998).
The ecological validity of tests of executive function. Journal of the International Neuropsychological Society, 4(6), 547-558.
https://doi.org/10.1017/S1355617798466037 |
DOI 10.1017/S1355617798466037
[10] Burgess, S., Greaves, E., Vignoles, A., & Wilson, D. (2009). What parents want: schoolpreferences and school choice. CMPO.
[13] Cohen, L., Manion, L., & Morrison, K. (2017). Action research. In L. Cohen, L. Manion, & K. Morrison (Eds.), Research methods in education (8th ed., pp. 440-456). Routledge.
[14] Datnow, A., & Hubbard, L. (2015). Teachers' use of assessment data to inform instruction: Lessons from the past and prospects for the future. Teachers College Record, 117(A), 1—26.
[15] Datnow, A., Park, V., & Wohlstetter, P. (2007). Achieving with data. University of Southern California, Center on Educational Governance.
[16] De Maeyer, S., & Kavadias, D. (2007). Openleerpakket beschrijvende statistiek. Academia Press.
[17] Earl, L. M., & Katz, S. (Eds.). (2006). Leading schools in a data-rich world: Harnessing data for school improvement. Corwin Press.
[18] Earl, L., & Louis, K. S. (2013). Data use: Where to from here? In K. Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision makingin education: Challenges and opportunities (pp. 193-204). Springer,
[20] Eurydice. (2011). Grade retention during compulsory education in Europe: regulations and statistics. OECD.
[22] Field, A. (2009). Discovering statistics using SPSS. SAGE Publications Limited.
[23] Harteis, C , Koch, T., & Morgenthaler, B. (2008). How intuition contributes to high performance: An educational perspective. US-China Education Review, 5(1), 68-80.
[25] Hogarth, R. M. (2001). Educating intuition. University of Chicago Press.
[28] Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgment. In T. Gilovich, D. Griffin, & D. Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment (pp. 49-81). Cambridge University Press.
[30] Kaiser, J., Retelsdorf, J., Siidkamp, A., & Moller, J, (2013).
Achievement and engagement: How student characteristics influence teacher judgments. Learning and Instruction, 28, 73—84.
https://doi.Org/10.1016/j.learninstruc.2013.06.001 |
DOI 10.1016/j.learninstruc.2013.06.001
[32] Loehlin, J. C. (2004). Latent variable models: An introduction to factor, path, and structural equation analysis (4th ed.). Lawrence Erlbaum.
[34] Mandinach, E. B., Honey, M., & Light, D. (2006, April 9). A theoretical framework for data-driven decision making. Paper presented at the annual meeting of the American Educational Research Association, San Francisco, CA.
[35] Mintzberg, H., & Westley, F. (2001). It's not what you think. MIT Sloan Management Review, 42(3), 89-93.
[36] Rosseel, Y. (2012). Lavaan: An R package for structural equation modeling and more. Version 0.5-12 (BETA), journal ofStatisticalSoftware, 48(2), 1-36.
[38] Schildkamp, K., & Lai, M. K. (2013). Conclusions and a data use framework. In K. Schildkamp, M. K. Lai, & L. Earl (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 177—191). Springer.
[40] Strayhorn, T. L. (2009). Accessing and analyzing national databases. In T. Kowalski & T.J. Lasley (Eds.), Handbook of data-based decision making in education (pp. 121- 138). Routledge.
[46] Vanlommel, K., Van Gasse, R., Vanhoof, J., &c Van Petegem, P. (2018).
Teachers' high-stakes decision making. How teaching approaches affect rational and intuitive data collection. Teaching and Teacher Education, 7/(1), 108-119. |
DOI 10.1016/j.tate.2017.12.011