As this lifestream draws to an end and because we have been looking at learning analytics, I have been examining my own learning over the course of the last ten weeks and realised a number of things that wouldn’t have been made visible by quantitative metrics. One of these is that in my indecision over the pros and cons of LA I have sought to discover my tutors’ stance and found it difficult to determine. Why have I done this and not made up my own mind? The obvious answer is that I am the student and they the teachers from whom I am learning. There is also a wish for certainty, for the knowledge that I have got the answer ‘right’. This isn’t the heart of education which must be concerned with the development of my own critical abilities, together with an acknowledgement that most often there isn’t a right answer, certainly not easily deliverable on a dashboard. So although my instinctive wariness hasn’t left me, due mainly to concerns over power and privacy, I will try to keep an open mind in the hope that in full and equal partnership with the student, ie for the learner, Learning Analytics might foreground patterns of engagement allowing difficulties to be overcome and goals reached. More importantly, rejection is a missed opportunity to voice critical concern.
Jeremy Knox’s blog post entitled Abstracting Learning Analytics on codeactsineducation argues that what is important about LA is not simply whether it offers a faithful representation of ‘learning’ or the propitious conditions for it, but that it provides a view of what matters to the analyst and the norms and the values of the world she inhabits to create her depiction. As Knox contends that an abstract painting is ‘an account of the internal act of producing the painting’ so, too, he argues, learning analytics is concerned with the ‘immanent practices’ of producing analytics and all that is encoded in them.
Knox’s abstraction brings to mind situations and representations in which what counts is not always ‘mattered’ in front of our eyes in crisp authoritative images, more or less faithful to what it represents, but what is obscured, neglected or struggles for definition from behind other layers of meaning. Code acts in education often to promote ‘wider political, economic and societal’ influences, leaving its heart to be suggested by its absence like dark matter, the objects of symbolist poetry or the reverso of the negative image. The intangible and difficult-to-locate qualities of education and learning make them hard to reveal and to measure, leaving things open for other forces to substitute their own methods and metrics. Knox’s article calls for these to become less opaque so that we can properly compute their relevance and application for education.
From Jacques Derrida: Deconstruction by Catherine Turner, 27 May 2016, Critical Legal Thinking
However while the idea of exclusion suggest the absence of any presence of that which is excluded, in fact that which is instituted depends for its existence on what has been excluded. The two exist in a relationship of hierarchy in which one will always be dominant over the other. The dominant concept is the one that manages to legitimate itself as the reflection of the natural order thereby squeezing out competing interpretations that remain trapped as the excluded trace within the dominant meaning.
— Nigel Painting (@nigelchpainting) March 24, 2017
Studying different analytical tools allows us a better view of ‘the processes inherent to analysis itself‘ (Knox, 2015), allowing us to see what might be considered success under their terms.
Knox, J. (2014). Abstracting Learning Analytics. Code Acts in Education ESRC seminar series blog. http://codeactsineducation.wordpress.com/2014/09/26/abstracting-learning-analytics/
I watched a demonstration of this automated essay-improving software on YouTube and desperately want to try it out to see if it works. I thought it interesting that in these days of hypermedia one of the aims of OpenEssayist was to ensure student essays followed the traditional beginning, middle and end, showing how our narrative linear literacies have not been challenged here.
— Cathy Hills (@fleurhills) March 22, 2017
Predictive analytics – will it be used for nudging?
Bradbury et al declare the project of behavioural economics is
to model the essential irrationality of choosers, and in so doing to render the flaws in their choosing predictable … then be used to make claims as to how social and economic systems might be designed to counteract individuals’ tendencies to make ‘bad’ decisions and to stimulate ‘good’ decisions.
(Bradbury, McGimpsey and Santori, 2012, p.250)
The Educause article similarly relates the concept of the nudge as a
theory which centers on prompting individuals to modify their behavior in a predictable way (usually to make wiser decisions) without coercing them, forbidding actions, or changing consequences.
These descriptions point to how ‘irrational’ student behaviour may emerge from learning analytics data to be met with helpful and gentle attempts at ‘correction’ in the students’ best interests.
It sounds plausible and paternalistic, yet whilst making a point of neither forbidding nor coercing the individual, the ‘choice architect’ or ‘policy maker’ is concerned with constructing a situation in which the ‘correct’ course of action is not only implicit, but foundational and pervasive. It is a dynamic bias-in-action under the guise of neutrality and provision of choice. Disingenuous too, because it advertises human irrationality as undesirable whilst sloping the ground towards the one choice it deems appropriate.
Bradbury et al describe this ‘liberal paternalism’ as ‘the co-option of behavioural economics for the continuity of the neoliberal project’ (p.255), with economic reasons for adoption in education settings being cited by the Educause article,
The combination of automation and nudges is alluring to higher education institutions because it requires minimal human intervention. This means that there are greater possibilities for more interventions and nudges, which are likely to be much more cost- and time-effective.
Nudging and its more coercive or punitive variations, ‘shoving’ and ‘smacking’, carry the risk of inappropriate application through, for example, misinterpreting data or disregarding contextual detail excluded from it. Worse, the attempt to correct or eliminate irrationality is dangerous when the long-term effects of doing so are unknown, when what is considered ‘irrational’ is up for question and when it is subject to the substitution of only one option by a determinedly non-neutral party. An attempt to curb our freedom to choose what is regarded by one political project as ‘incorrect’ is an incursion of human rights and those rights, particularly as they belong to students already dominated by institutional or commercialised powers, should be protected. As the article concludes,
with new technologies, we need to know more about the intentions and remain vigilant so that the resulting practices don’t become abusive. The unintended consequences of automating, depersonalizing, and behavioral exploitation are real. We must think critically about what is most important: the means or the end.
Bradbury, A., McGimpsey, I., and Santori, D. (2012). Revising rationality: the use of ‘Nudge’ approaches in neoliberal education policy. Journal of Education Policy 28 (2), pp. 247-267.
Just Pinned to Education and Digital Cultures: Foucault’s dispositif http://ift.tt/2mQsRqI
I pinned this because I found it serendipitously whilst looking for the word diapositif or negative, (old-fashioned film slides) for a short post I was writing on Jeremy’s Abstracting Learning Analytics blog. Foucault’s dispositif seems to sum up the complex interrelation of elements making up the mechanism or apparatus behind Learning Analytics:
This requires some reading before I can properly decide if it’s relevant.
Thinking about quantifying the learning student made me reflect on time on task and whether, if an accurate measurement can be taken, more time on task would correlate to greater success (with the usual caveat about defining success). I don’t think it is always a foregone conclusion although mastery of a subject or skill is often characterised by the amount of time spent engaged in it. Time, here, is the amassed amount of hours, days or years needed to become a pianist, a professor or a potter. Is it possible to make creativity correlations? Pinheiro and Cruz (2014) itemise a series of tests to measure creativity but suggest
that the phenomenon of creativity cannot be described by any of these tests alone, but only through a battery of joint measures
Mapping Creativity: Creativity Measurements Network Analysis
from Diigo http://ift.tt/TXCD9V