Empirical is only half of it

I am concerned about the UK Push’s emphasis on the empirical. While a focus on empiricism maybe understandable given contemporary proliferation of data (Behrens & DiCerbo, 2014), the historical tension between the empirical and rational is ignored by the UK Push; as it drifts away from reason into ideology.

There are many ways of characterising the rational side of science. Plato uses forms, Kant uses categories, Kuhn uses paradigms, Morgan (1997) uses metaphor, others use the concept of structures. Each of these different characterisations address different aspects of the rational in the rational-empirical divide. In this blog, I will use the term mental model drawn from Senge (1992).

Mental models frame how we conduct empirical activities, they frame how we collect and interpret data. This has traditionally been a chicken or the egg argument; does the mental model or the data come first. Contemporary approaches consider there to be dialectic between the two, where one informs the other. That is, mental models evolve with the awareness and availability of new data and evidence.

Mental models can frame how educational assessments are conducted. For example, TIMSS and PISA describe their mental models in respective frameworks. Each program uses a different mental model, and this results in different empirical data and claims. These claims can often be reconciled through further reasoning; as Wu (2009) does, for example, for mathematics achievement in TIMSS and PISA.

Different mental models sometimes exist for the same phenomenon. Light provides a good example.  In physics, light can be considered a particle studied using methods and equations used for the study of billiard balls. Light can also be considered a wave studied using methods for studying waves in a pond. The wave and particle model are equally valid with their use depending on purpose.

Sometimes new mental models supplant older ones that no longer fit. The movement of planets provides a classic example. Once the earth was considered stationary and at the centre of the cosmos. This led to complicated equations to describe the movement of planets. Copernicus came up with a better model that considered the sun as stationary. This led to less complicated equations and easier science. This is what Kuhn (1970) characterises as a paradigm shift.

An important feature of paradigm shifts, and better ways of knowing, is that it requires the development of a better model. Paradigm shifts cannot be created simply by criticising old ideas as is the want of the UK Push. The criticism from the UK Push is the kind that Galileo experienced from the Roman Inquisition when he first proposed that the sun be the centre of planetary motion.

Different mental models can be used for the same phenomena in different spheres of life. Music provides an excellent example. Sound can be studied through the science of physics to make technologies for creating music, special effects and so forth.  Performers of music on the other hand communicate differently using scales, chords, time signatures etc. The discipline of music can vary across cultures and is distinct from the discipline of physics. Then there is the aesthetic experience of enjoying music which is considerably subjective and can be oblivious to theories in both music and physics.

Mental models around social constructions – how people relate to each other – have been considerably challenged in the past decades. Major blind spots have been identified since Jefferson found it self-evident ”that all men are created equal” in 1776. That statement itself left out women leading to the feminist movement (for example Butler, 1990/2007; Irigaray, 1995). Former colonies felt marginalised leading to postcolonialism (for example Said, 1978/1994; Spivak, 1985/2010).  There is also Foucault (1990) who challenged traditional perceptions of sexuality and marginalisation. Crenshaw (1991) highlights how race, gender and other identity categories feed into politics and marginalise individuals. These forces challenge shared mental models in the social sciences.

Language is central to mental models and to how they work in the social sphere. For example, Butler (1990/2007, pp. 12-13) notes that social science refers to things like gender as a dimension of analysis, but gender can also be applied to a person, where language is used to create a person’s gender. Here Butler is drawing on the work of the British philosopher Austin (1962/1975) in How to Do Things With Words. Austin points out that not only can words be used describe things, words can also use to construct things like gender. In this way, mental models, as articulated through language, can be used to construct or reinforce the identity of individuals including students.

Empirical evidence is therefore only half of the scientific method. Scientific arguments also requires examination of the rationales, mental models, and language used. London based Driver, Newton, and Osborne (2000, p. 289), for example, argue that empirical work should not be portrayed as the basic procedural step of scientific practice. Instead, they consider empirical evidence as providing evidence for knowledge claims that can be tested using argument through models such as proposed by Toulmin (1958/2003).

With its fixation on empirical evidence the UK Push are oblivious to the mental models that furnish interpretations of data, evidence, and about what works. Conscious or unconscious ideologies underpinning their mental models remain hidden from scrutiny, argument and debate. That the UK Push’s focus is on debasing and ridiculing existing ideas, often drawn from the margins of the literature, points to a reductive and dangerous form of reasoning. Particularly in the absence of proffering new well-formed ideas. In not being able to create new ideas, all that is left is to import the ideas of others, such as the UK phonics check.

 

Austin, J. L. (1975). How to do things with words (J. O. Urmson & M. Sbisá Eds. 2nd ed.). Cambridge MA: Harvard University Press.  (Original work published 1962)

Behrens, J. T., & DiCerbo, K. E. (2014). Harnessing the Currents of the Digital Ocean. In J. A. Larusson & B. White (Eds.), Learning analytics: From research to practice (pp. 39-60). New York: Springer.

Butler, J. (2007). Gender trouble: Feminism and the subversion of identity. London: Routledge.  (Original work published 1990)

Crenshaw, K. (1991). Mapping the margins: Intersectionality, identity politics, and violence against women of color. Stanford law review, 43(6), 1241-1299.

Driver, R., Newton, P., & Osborne, J. (2000). Establishing the norms of scientific argumentation in classrooms. Science education, 84(3), 287-312.

Foucault, M. (1990). The history of sexuality: An introduction, volume I. Trans. Robert Hurley. New York: Vintage.

Irigaray, L. (1995). The question of the other (N. Guynn, Trans.). Yale French Studies(87), 7-19.

Kuhn, T. (1970). The structure of scientific revolutions (Second Enlarged ed.): The University of Chicago Press, Chicago.

Morgan, G. (1997). Images of Organization. California: SAGE Publications.

Said, E. W. (1994). Orientalism. New York: Vintage Books.  (Original work published 1978)

Senge, P. M. (1992). The fifth discipline: The art and practice of the learning organization. Milsons Point: Random House.

Spivak, G. C. (2010). Can the subaltern speak? In R. C. Morris (Ed.), Can the subaltern speak?: Reflections on the history of an idea (pp. 21-78). New York: Columbia University Press.  (Original work published 1985)

Toulmin, S. E. (2003). The uses of argument (Updated ed.). New York: Cambridge university press.  (Original work published 1958)

Wu, M. (2009). A comparison of PISA and TIMSS 2003 achievement results in mathematics. PROSPECTS, 39(1), 33-46.

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