Abstract
We discuss some examples of direct or indirect involvement of mathematics education researchers in teacher evaluation and curriculum design; and point to hegemonic strategies of persuading sponsors and policy makers how to install “good mathematics teaching”. We illustrate how particular research approaches stabilise “good mathematics teaching” by structuring the meaning around interpretations of learning outcomes in the form of measurements, which are taken as symptoms of a range of social phenomena. Students’ scores on mathematics tests are interpreted as indicators of their potential to become skilled “knowledge workers”, citizens and consumers; teachers’ and schools’ effectiveness in producing gain scores as indicators of the quality of mathematics teaching for which they can be made accountable; and improvements in national measures as symptoms of innovative capacity that predicts relative competitive advantage. Our concern is the alliances researchers might seek in capitalising on the privileged status of mathematics that relies on the reiteration of those imaginations, in particular in contexts where funding of research favours “findings” that emerge from studies that identify “what works”.
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- 1.
For instance, the UK government has recently recruited proponents of randomised controlled trials for promoting their use in evaluating education and public policy, with the intention to identify interventions with large effects for low cost. One priority is “to increase understanding of ‘what works ’ in education” (DfE, 2014). A decade earlier, the U.S. National Research Council issued a report on “Scientific Research in Education” (Shavelson & Towne, 2002) and has set up a clearinghouse for “what works” in education (http://ies.ed.gov/ncee/wwc/).
- 2.
As to the PISA, Jablonka (2015) observed that mathematics is attributed a privileged position over science in the relation to the empirical and is expanded into a new version of “mathematicoscience ”. Mathematics is presented as directly formalising the empirical, as “mathematical concepts, procedures , facts and tools to describe, explain and predict phenomena” (OECD-PISA, 2014, p. 17, our emphasis), whilst the science test is only about drawing “evidence-based conclusions about science-related issues” (OECD-PISA, 2014, p. 28, our emphasis).
- 3.
Any concerns about reliability and validity , as well as the direction of any causal relationships, “can be satisfactorily answered once skills are correctly measured, and the basic growth relationships can support a detailed analysis of the economic implications of improving a nation’s knowledge capital ” (OECD, 2015, p. 26). The gains in GDP for all countries included in the study have been “estimated with an improved workforce over GDP with the existing workforce from 2015 until 2095” (p. 48).
- 4.
Wiliam (2010) points out that the distinction between norm-reference and criterion-reference is not a property of the test results but of the interpretations and inferences drawn.
- 5.
Policy studies have contributed with analyses of the workings of accountabilit y mechanisms that increase bureaucratic control of schooling, which are based on steering through indicators, or “governance through data” (Ozga, 2009) in a range of modes and settings, including national examinations , literacy and numeracy tests, school inspection policies, evaluation of graduate programmes, and university rankings (Ball & Goodson, 2015, Perryman, Ball, Maguire, & Braun, 2011). Piattoeva (2015), refers to “elastic numbers” in her analysis of the use of the results of the Unified State Exam in Russia, the different readings of which lead to merging the official and the popular. While accountability suggests the efficiency of state institutions can be ensured through monitoring by members of society , the evaluation is in the end produced by officials.
- 6.
- 7.
The most obvious example of a hegemonic struggle over good mathematics teaching is what has become known as the “math wars” in the USA .
- 8.
The construct of MKT (and similar formulations), conceptualised within the discourse of mathematicoscience , has an inbuilt potential of further differentiation into “sub-knowledges”, which might lead to the attraction of additional research resources. Thus, in Herbst and Kosko (2012) an instrument to measure mathematical knowledge for teaching high school geometry is developed, and Subramaniam (2014) investigates prospective teachers’ pedagogical knowledge for teaching the estimation of length measurements (see also Thanheiser and Browning, 2014).
- 9.
For quantifying the MQI score, in the study by Blazar (2015) “two certified and trained raters watched each lesson and scored teachers’ instruction on 13 items for each seven-and-a-half minute segment on a scale from Low(1) to High (3)” (p. 19).
- 10.
This does certainly not assist any argument against tracking .
- 11.
In the project, teachers received 13 days of professional development and then got access to a website with examples for teaching activities and some explanations.
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Acknowledgments
We would like to acknowledge the helpful critical comments to earlier versions of this paper by Nina Bohlmann, Tony Brown and the other participants at the DOME–Disorder of Mathematics Education meeting held at Freie Universität Berlin, 15–17 January 2015.
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Jablonka, E., Bergsten, C. (2017). Installing “Good Mathematics Teaching”: Hegemonic Strategies and Alliances of Researchers. In: Straehler-Pohl, H., Bohlmann, N., Pais, A. (eds) The Disorder of Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-319-34006-7_7
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