Educational Research - the Ethics and Aesthetics of Statistics

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138 U. Stadler-Altmann and E. Keiner collecting, exploiting and displaying data – a gargantuan enterprise to both crown enlightenment and finalise the pursuit of happiness and common welfare. ‘Good decisions are informed decisions’ is one of the great mantras of modern rationality. Social sciences and educational research are expected to significantly contribute to its realisation in the field of education, training and lifelong learning by providing reliable information, which, in close connection with educational planners, can be used for political decisions. The intended tight linkage between educational research and educational management and policy, however, is usually based on the implicit assumption that – reversing the phrase – ‘informed decisions are good decisions’. Furthermore, the assumption also implies that the quality of decisions increases with the amount of good information available. Statistics are one of the most important means to govern this direction and to convince people about the appropriateness of means and direction. The (written) presentation and use of statistics follows a pattern that combines a more rhetorical and a more epistemological aesthetics thus intertwining policy and research (Ozga 2007; Ozga, Seddon, & Popkewitz, 2006). However, the political or scientific reference, which is necessary to judge the validity and reliability of the statistical information presented, usually remains rather implicit and unclear. Economic, social and educational advancement as normative points of reference drive the demand of standardised and comparable research designs and so-called evidence-based educational research knowledge. At first glance, ‘knowledge’ seems to be used as an inclusive term covering all kinds of knowledge. However, if one takes a closer look at what is required knowledge is narrowly defined as ‘useful knowledge’. Institutions and organisations that govern career and life courses, define what counts as licensed (or not licensed), as useful (or less useful) knowledge. 9.2.1 Information, Knowledge and Social Contexts A core problem is the commonly homonymic use of the terms knowledge and information. To distinguish these terms, however, is very important, because it relativises and thus provides the means to criticise what is ‘given’. In addition, it makes it possible to qualify and to assign the aesthetic epistemological and rhetorical format of a given knowledge as dependent from the social contexts it is related to. Information, derived from the Latin verb ‘informare’ in the sense of ‘to give form to the mind’, lacks a precisely definable content. It is, one might say, rather decontextualised knowledge. Information is a phenomenon that does not undergo scrutiny, more a word than a term, more a cipher than a number. On the other hand, knowledge can be seen as information loaded up with particular meaning. This depends on the particular context it is embedded in. A good example of uploading and unloading, of transitions from knowledge to information and back again, is the book Education at a Glance, published every second year by the OECD. The very detailed appendix of this book shows the methodical conditions under which the figures presented are valid. This is not only
9 The Persuasive Power of Figures and the Aesthetics of the Dirty Backyards 139 a question of the ISCED classification, but also the categories used, the weights added to the figures and the conversions made. The appendix shows that Education at a Glance is made according to the standards of social science research, at least regarding its methodological (not necessarily to its theoretical) frame. Although the OECD as well as the European Commission try to make statistics more convincing by using well-designed tables, charts and cover pages, which aestheticise the messages based on figures, the methodological appendix constrains their coverage. This shows that the explanatory range and the degree of comparability of the data are very, very limited. It raises more questions, than answers. A short story: Some years ago I gave a seminar on methodology in educational research, and, what I did first was to read the methodological appendix of Education at a Glance with my university students. Following this, the students came to regard Education at a Glance as a worthless, meaningless collection of incomparable data. I therefore had to defend Education at a Glance as a weak, but nevertheless the best and most comprehensive collection of data that is currently available. In the second part of the seminar I read an article with my students about research on the degree of financial investment contributing to educational development in underdeveloped countries (indicated by the relationship between financial investment and degree of literacy). The article stated that roughly the cost of three American Pershing rockets (or the annual budget of Berlin!) would be enough to double the degree of literacy in one such country within 15 years. This article provoked a very intense and political debate on the necessity of development aid and bringing more investment to the educational systems of developing countries. All students agreed upon this goal. At the end of the session I asked the students to look at the statistical basis of the article. The statistics were mainly derived from Education at a Glance. It became clear that the validity of the information given depends not only on the methodological frame but also on the political intentions behind the use of information. What did the students do? First, they subtracted, separated, unloaded and peeled off the data (information) from the methodological knowledge frame that constituted their scientific validity. They then decontextualised research knowledge, bringing it down to the level of data. Second, they uploaded and added an alternative frame to the data – e.g. social desirability, ethical principles, political usefulness or economical viability – which constituted a new subject, new knowledge. The students recontextualised the data, thereby elevating it to the level of knowledge. This shows that the pattern of data and categories the data are embedded in serve as a kind of a puzzle picture, which displays similar, but slightly different shapes depending on the frame. The frame attributes the particular meaning to the data and categories converting them to structured and meaningful knowledge. From this point of view, truth and adequacy are not necessarily justified by scientific validity. This only counts as one truth inter alia. Truth turns out to be a question of power. Those who hold power are able to define the appropriate frame and merge it with statistical data so as to sell the construct as the truth. The variety of possible different contexts disappears and becomes superseded by a system’s principles of functioning, the authority or power of a social group, a speaker, an institution, political promises or the ‘Zeitgeist’. The aesthetics of
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Educational Research: The Ethics an
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Paul Smeyers · Marc Depaepe Editor
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Earlier Volumes in this Series Educ
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viii Contents 10 The Good, the Beau
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Chapter 2 The Lure of Statistics fo
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2 The Lure of Statistics for Educat
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28 M. Depaepe of the Leuven Catholi
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30 M. Depaepe Tan’s final verdict
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32 M. Depaepe of methodological bot
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34 M. Depaepe tapping other sources
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36 M. Depaepe In the context of dem
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38 M. Depaepe combination. Moreover
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40 M. Depaepe 4. See Pelleriaux (19
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42 M. Depaepe Schneider, J. (2010).
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44 J.J.H. Dekker (see Section 4.4).
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46 J.J.H. Dekker from their own par
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48 J.J.H. Dekker a cohort study tha
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50 J.J.H. Dekker child” (Van IJze
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52 J.J.H. Dekker USA resulted in ev
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54 J.J.H. Dekker of the problem”.
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56 J.J.H. Dekker Dekker. J. J. H.,
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188 I. Munday We might also note th
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190 R. Smith ‘Statisticism’, on
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192 R. Smith identify, and twice in
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194 R. Smith of the final sentence
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198 R. Smith 7 www.equalitytrust.or
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200 R. Smith It is an interesting q
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202 R. Smith self-esteem, happiness
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204 R. Smith Reeves, R. (2009, Apri
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206 P. Standish Some students’ no
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210 P. Standish Rice $1.73 1 / 2 Mo
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212 P. Standish research none of us
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214 P. Standish of the products but
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216 About the Authors co-editor-in-
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218 About the Authors voor Wetensch
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220 Author Index Elkins, G. R., 190
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222 Author Index Silverman, J. G.,
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224 Subject Index I Inequality, 29-
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