Ed-Tech and Naive Realism

Cognitivist perspectives on education have excelled in contributing woolly thinking about the causal relationships between human development and educational resources. The models presented by the instructional designers demonstrate almost universally a functionalist reduction of human experience, producing in the name of 'science' what Christian Smith calls 'variables-based sociology' (see his "What is a person?"): that supposedly empirical process of identifying the dependent and independent variables of learning processes. With little critique or reflection, almost without exception, independent variables are identified with material educational interventions: books, webpages, online services, learning designs, etc. In psychology's desire to be treated like physics, this unquestioning physicalism is perhaps understandable: the objects of education are 'there' - we can all see them, and we can't see learning. Yet objects also constitute dependent variables: the work that students do, for example. But the possibility that this kind of 'variable-ism' might be deeply mistaken (as wiser heads in phenomenology like Merleau-Ponty would have told us) and that nothing is independent, remains invisible: the causal relationship between matter and the 'mattering' of education is unthinkable to many psychologists. Even if the appetite for instructionalist thinking with regard to learning resources and 'instructional design' has dissipated slightly (in the wake of emerging socio-material insights like Actor Network Theory or Orlikowski's work), attention shifts to new kinds of objects in education such as those produced through 'learning analytics'. Once again, it's the same problem: identifying the independent variables in the material analysis and then inspecting causal relationships.

So Instructionalism isn't dead. Why should it be? There is little doubt that some resources appear to be more successful in engaging learners than others, or that some pedagogical approaches are more successful than others, or even that data analytics are useful in speculating on what might be going on in learners' heads. However, it remains impossible to separate the 'powerful objects' of the learning process from the people involved in using those objects to teach. However wonderful a resource might appear to be, in the hands of a poor teacher, the educational results will be always be dreadful.

The issue gets confused with other cognitivist nonsense which has found its way into educational technology. 'Usability’, for example, has dominated thinking about the most effective configurations of tools. Like learning resources (which can be shown to demonstrate "usability"), some things appear more successful or 'usable' than others. For example, the use of a ‘Model a/Model b” approach to testing different user interfaces produces significant data (particularly if you are Google) as to which configuration of tools within the user interface might be most effectively deployed. Similarly the ‘best way’ to construct a web page can emerge out of usage data (like Google analytics), and when more than one model is available for testing, this can appear to reveal which model is preferable. However, there is a tendency to see educational technology like pharmacology: an intervention within education will ‘treat’ patients in ways that can be measured, and the most effective interventions can then be identified, and their distribution can be expanded. This is a different level of functionalism where the objective is not to identify those independent variables that bear upon learning processes, but those independent variables which bear upon the social conditioning of a population. The mistake is to confuse social conditioning for social advancement. The fact that we can condition people by constraints is not a surprise (if you attach electrodes to people's genitals, they will do what you want!). Conditioning is not a "successful outcome"; it is a question.

What's the question? Fundamentally, it's a question about 'mattter'. It's a question about the nature of objects and their causal powers. But more than that, it is a question about the two meanings of 'matter': as Karen Barad has pointed out (see her excellent "Meeting the Universe Halfway"), it is not just a semantic trick that 'matter' and 'mattering' appear to be related: what "matters" to us has a bearing on the way we think about "matter". When we see calls for educational technology to be ‘evidence-driven’ (by Ben Goldacre particularly - one the new champions of naive realism), the question we are faced with is the relationship between the causal efficacy of "matter" (our interventions) and "what matters". Like Google, Goldacre doesn't really want to think about what matters - indeed, what matters to him is that his methodological blindness about "matter" is applied by everyone - but the mattering of "what matters" is inescapable to anyone involved in education. Google think that what matters is that everyone uses their tools: but this isn't what matters to society. Learning analytics people think that "what matters" is that methods of analysis allow us to streamline 'support' for the production of 'successful' education outcomes. But what matters about a successful educational outcome? (see my previous post about learning outcomes).

Barad is right to focus on the relationship between matter and mattering (although I'm not convinced about her 'agential realism'). Goldacre should be thanked for his request for a more scientific approach to education, but his idea of science is shallow: he should read Barad! Education demands a deeper critical science. Just as the gender issues that Barad identifies in the physical sciences are inseparable from scientific knowledge, so education, which matters so much to all of us, turns scientific inquiry on its head: science must help us understand the nature of matter, but education is the science that leads us towards discovering the relationship between what matters to us as a society and the nature of world we share.