Saturday 29 October 2016

E-learning as a job: The skills requirements of Universities today

There are significant differences of interpretation as to what "E-learning" or "Technology-enhanced learning" actually is - particularly when it comes to the expectations of employers and the capabilities of employees. Managers will often envisage online courses with videos, quizzes, etc and assume that this is what 'e-learning' is. As a result of this expectation, tools have been tailor-made to produce such online presentations (Articulate, Storyline, etc). Basically, they're "glorified Powerpoint", simply sequencing content, and unfortunately, whilst they produce nice-looking content, they are extremely limited in their capability to harness the full potential of technology in education. Sitting in front of a video, clicking on buttons in answer to quiz questions is a miserable educational experience (watch the wonderful computer scene in "I, Daniel Blake" to see precisely how miserable this stuff is)

Human learning, teaching, and more broadly, communicating is extremely complex and poorly understood. Technology can be a tremendous asset or a terrible hindrance. The difference between the two is the creative imagination, educational insight and technical capability of the educational technologist. In each of these categories, the commercial 'tooling' of e-learning - whether its the institutional VLE, presentation software, or commercial social software - together with the managerialism of education has had many negative effects. If creative imagination is restricted to the capabilities of the software, the results will all look the same. If the educational insight is missing, there will simply be a load of content (which may look lovely) that nobody will engage with. If the technical capability isn't there, then the educational technologists cannot step outside the box because their legs are tied together.

But this is what we see in the world of educational technology now (if you don't believe me, just look at the majority of submissions for ALT-C). Too many educational technologists simply do what they're told, produce Powerpoints (Storyline/Articulate) with voice-over (maybe a little bit of animation), a few quizzes, and stick the files on the VLE. It looks pretty (sometimes) - but there's no thought. Sometimes, being a bit more ambitious, they might facilitate teachers feeding back to students with audio or video - but that's about it. There's no consideration of what else might have been possible. There's no discussion with the academics whose content it is as to how what they want to communicate might be communicated differently, there's no consideration for the context or needs of the learners, or an insight into the sheer boredom of gazing at a screen for hours.

The irony is that the sequencing of content can be achieved in much richer ways by avoiding the 'professional' tools. E-learning standards like IMS Content Packaging can aggregate rich content including simulations, games, (and quizzes, etc) from all over, and when played through the VLE, display in just as slick a format as that produced with the likes of Storyline. Understanding the authoring of content packages, the different kinds of content which can be created, the mixing of javascript and html5... all of this 'techie' stuff is being lost because there's now a package that makes it all easy, whilst at the same time attenuating the technical possibilities. But it isn't difficult - even if a tool like Reload looks a bit daunting at first (see

But then, understanding what becomes possible with content sequencing opens up what is possible with the multitude of web programming tools we now have. Real-time conversation and collaboration with NodeJS, Rich 3D graphics with Threejs and WebGL, data visualisations with d3.js, Agent based modelling with Python Mesa and the web version of Netlogo, data analysis with Jupyter notebooks, artistic visualisation with processingjs... the list goes on. We can do amazing things with the appropriate technical skill and theoretical insight.

Having said all this, producing content is not a terribly productive or educationally useful thing to do. There is content everywhere - there's little need to produce more of the stuff. What we lack are effective tools with which people can engage one another in innovative kinds of learning conversation. I quite like the idea of merging tools with content, so that content (say a video) is itself part of a tool - perhaps a tool for producing an analytical diagram which can then be used as a spur for conversation. The tool/content boundaries can be blurred - they are effectively both forms of constraint on the learner.

Which brings me to the underlying theory of what educational technologists do. The theory of e-learning is a potpourri of ideas which do not hang together. The worst example is "Networked Learning" - a mix of Illichian radicalism, communities of practice theory, poorly thought-through Pask/Laurillard cybernetics mixed with even more poorly conceived connectivism (which is also cybernetic), bits of activity theory, design-research, etc (see . There is no convincing ontology and no coherent epistemology: the theory merely looks like a patchwork of topics from a course design (which indeed it is!). Where's the intellectual ambition? And indeed, where's the critique?

There appears to be no desire to really pull this apart. After all, why would you? If you can simply grab little bits of theory to defend the latest project (however thin), and it ticks the box of "theoretical foundation" or "research methodology". More disturbingly, academic managers like to consider themselves well-versed in "educational theory" so that they can dictate the educational practices they wish to see in their institutions. Effectively, this is to reify something which is essentially transcendental, and instead of authentic human interaction and organic learning, we have robotic process and technocracy. But all our educational theory is deficient, and yet none of it is explored for the precise ways in which it is deficient: there is no exploration of the constraint boundaries of theoretical explanation and prediction. That would be a much more effective research programme.

Our tools for getting to grips with understanding the constraint boundaries are going to involve data. But this is not the learning analytics or big data which has hypnotised everyone. It has to start with a deep question which is as inseparable from education as it is from technology: What is information?

We simply don't know, and since it appears that information rules our lives more and more, we urgently need to understand better what we are talking about. This is the proper academic territory of e-learning: it is the intellectual engagement which can fire up the truly radical and transformative experiments in the relations with human learning conversations and technologies.

The ultra-conservative spirit that afflicts our universities at the moment seems to suggest that technology is 'over' - or at least settled around the VLE, Turnitin, E-portfolio and classroom polling systems. What a miserable thing! But, in true Marxist spirit, it will collapse under the weight of its own ontological contradictions. There, perhaps, is the most important role for the educational technologist - to warn of the consequences of not thinking. 

Thursday 27 October 2016

The Information Science of Music - and the Future of Educational Technology

I've really enjoyed leading an online discussion on the future of scientific communication on the Foundations of Information Science list ( I've become frustrated that in debates about educational technology, emphasis has been placed on technology/practice x, y, z on the benefits to teaching and learning. As I've written (here: this is an indefensible metaphysical claim: nobody can see learning. Fundamentally, these arguments are all intended to serve the interests of the institution of education. But what matters more is science.

The embrace of new communications technology, new pedagogic practice, etc is much more important to the future of science than it is the future of universities. And Universities are institutions which fundamentally depend of science. It is the scientific arguments for the embrace of new ways of communicating which, in the end, will transform universities - just as the critique of Francis Bacon in 1605 (The advancement of learning) transformed the old curriculum of Aristotelian doctrine to a new empirical approach (it had all changed by 1700).

But there are questions about communication, and more deeply about information. These deep questions demand attention to be focused on different ways of communicating.

Musical communication is the most powerful form of communication I know. It also doesn't appear to work by the same rules as an academic paper. How does it work? What does it tell us about communication more generally? What does it tell us about the importance of embracing new media in scientific communication? These are questions of the philosophy of information.

I produced a final video for the FIS discussion here where I drew on a Bach Fugue as an example of information and communication (it's a bit crackly in places unfortunately).
At the root of my argument is a critical appraisal of the nature of 'counting' and probability in the way we think about communication. In Shannon's equations, probability plays an important role - but what does it mean? It appears to be something about "surprise" (Shannon measures the average "surprisingness" of a message) - but what's that?

John Maynard Keynes asked deep questions about probability (which sits behind Shannon) in the early 1920s as he was formulating the foundations of his General Theory of Employment, Interest and Money. His work on probability is more important in our world of big data, learning analytics, etc than the General Theory. The video concerns Keynes's idea of 'negative analogy' in the way that we understand and experience music. Deep down, he, and many other thinkers about information today, are pointing at the importance of the 'apophatic' (absence/the "not there") in thinking about information and communication.

It's a small idea - the "not there". But its the kind of small idea which can change everything.

Saturday 15 October 2016

Repetition and the Apophatic in Music: An Information Theoretical Approach

All analysis involves the application of constraint on experience. “Constraint” itself can be variously defined as background, absence or context – it is the domain of the “not there”. In Information Theory, it is measureable as Shannon’s ‘redundancy’, the inverse of information. Recent scholarship in Information Theory has borrowed a term from theology, labelling the broader domain of “not information” (beyond Shannon) as Apophatic.
At the heart of the Shannon notion of redundancy are concepts of repetition, similarity, identity and analogy. Since Hume, the identification of similarity and analogy has introduced questions about human reasoning which cast doubt on assumptions about expectation, induction, causation and probability. Hume famously considered the likeness of eggs, but the likeness of melodies, themes, harmonic patterns, rhythms and so forth is, I argue, more compelling because it carries with it the visceral dimension that is shared between musicians and intrigues analysts.
In considering Bach’s fugue in Ab major, I start from the perspective of an early champion of Shannon’s work, the cybernetician and psychiatrist Ross Ashby. Ashby argued that:
“The principle of analogy is founded upon the assumption that a degree of likeness between two objects in respect of their known qualities is some reason for expecting a degree of likeness between them in respect of their unknown qualities also, and that the probability with which unascertained similarities are to be expected depends upon the amount of likeness already known.”

The Bach fugue presents a variety descriptions of different aspects of the music, where each description considers the counting of and distribution of particular features (rhythm, melody, intervals, etc). For example, how is (a) the same as (b)? Each description exists in the context of other descriptions; each description constrains other descriptions (e.g. the description of rhythm is constrained by the description of dynamics or pitch). Moreover, the identification of similarity within each description entails assumptions about the degree of likeness in “unknown qualities”. As the music unfolds, some of these assumptions about unknown qualities will be revealed to be errors, causing continuous reassessment of what counts as the same and what doesn’t.

Friday 14 October 2016

Scientific Communication, Information and Music

In discussing the problems of scientific communication and the pathologies of education, there are three fundamental distinctions which are important to draw. They are:

  1. The distinction between IS and OUGHT in arguments about scientific communication 
  2. The distinction between an EXPLANATION and a DESCRIPTION 
  3. Issues about ONTOLOGY and INFORMATION 

I want to discuss each of these in turn, and then to draw on a musical example to illustrate the issues further.


I have begun to see the pathologies that we have in education and publishing as a direct consequence of failures in scientific communication. The challenge is to describe the ontological mechanisms. Essentially I aim to describe how scientific communication should be conducted in the light of what we know about our science. I do not want to say how it 'ought' to be.

Hume's famous passage in dealing with the dichotomy of "is" and "ought" is worth reflecting on:
"In every system of morality, which I have hitherto met with, I have always remarked, that the author proceeds for some time in the ordinary ways of reasoning, and establishes the being of a God, or makes observations concerning human affairs; when all of a sudden I am surprised to find, that instead of the usual copulations of propositions, is, and is not, I meet with no proposition that is not connected with an ought, or an ought not. This change is imperceptible; but is however, of the last consequence. For as this ought, or ought not, expresses some new relation or affirmation, 'tis necessary that it should be observed and explained; and at the same time that a reason should be given; for what seems altogether inconceivable, how this new relation can be a deduction from others, which are entirely different from it." 

His complaint is about slippage from "is" to "ought" (he does not deny the possibility of deriving an ought from an is - the logical positivists misrepresented him). In my argument about scientific publishing I have tried to be careful in avoiding 'oughts' and ground an argument for a richer embrace of technological expression on the basis of describing how today's science is. I'm arguing (not much differently from David Bohm whose work on communication is new to me) that the nature of the science entails the need for new practices of communication.

There is a critical dimension (which I don't think is an Ought - it's just a warning): if we continue to communicate in the way that we did in the 17th century, then our communication won't work because it works against the scientific ontology. I'm speculating that this pathology feeds into financialisation processes which produce social crisis. In Hume's argument, communication between scientists and an ontology of regularity were tied together; now we have have to admit multiple contingencies in our scientific practices, the communication cannot be unchanged - can it?


Universal explanation is a common trait of scientific endeavour. This is clearly a very deep issue, but it fundamentally concerns our conception of causation. What is causation? What is causal explanation? For Hume, causal explanations are constructs produced in discourse (i.e. communication) between scientists in the light of regular successions of events produced in experiments. However, it is also worth considering that Hume was deeply sceptical about the articulation of any rational foundation which could underpin the production of regularities in nature. That cast doubt on assumptions about inductive reasoning (and for anyone who would champion Peirce's 'abduction', I think it suffers from the same problem at a different level)

Scientists certainly produce totalising explanations, cosmologies, etc, and these can be very useful to organise discourse and scientific activity, and also creating a sense of hubristic excitement which moves things on. But whilst universalist claims will be made, all we can safely say is that it is a "description of understanding". Scientific communication occurs when different scientist's "descriptions of understanding" coincide. I prefer to think of this as a recognition between scientists that they operate within related or shared constraints. We should inquire into the conditions when this happens. To describe phenomena, and one's understanding of phenomena is to reveal one's constraints. Describing doubt is a very important part of this. Explanation is to attempt to remove doubt - not just of the explainer, but of those they wish to convince.


Loet spotted a constraint in my understanding about redundancy and made an intervention which has (this time - sorry for not getting it until now!) really clarified things, and also opened up a connection between ontology, information and redundancy. Essentially, to calculate the redundancy one must have the maximum entropy, and the maximum entropy can only be gained from what Loet calls the "specification of the system": that, in my understanding, is an agreed ontology of what the system IS. 

I think this makes the relationship between Shannon information and redundancy recursive. In order to agree the ontology of the system, one must communicate; in order to communicate we must agree the constraints; in order to apprehend constraints, we must identify the redundancy... which can be identified through the maximum entropy, which entails agreeing an ontology. And so on. This makes me think my intuition about the importance of Lou Kauffmann's work isn't wide of the mark. 

Information appears like a recursive version of Wittgenstein's duck-rabbit, where there is a smaller duck-rabbit inside the larger duck-rabbit.

Of course, it is impractical to go to these recursive depths. Shannon's equations constrain us to a simple empirically observable domain. But I think it is important to recognise that the recursion is there, and that we are effectively 'cutting into it' (or constraining it) It may be that the point hangs on the identification of analogy, or identity: of what is counted as "the same as" or "another one".


I'm preparing a video to explore this which uses a musical example. I'll try and explain in text what I want the video to explain (you will at least have two descriptions!): Music analysts identify those features in a score or some other record of performance which are "the same" and "another" and produce their analyses which show how different combinations of categories change over time. But when we listen to a piece of music for the first time, we know little of what is about to come, except that our expectations are shaped as the music unfolds. What emerges over time is a multiplicity of what might be called "descriptions" (although they need not be verbalised, they can be expressed analytically to some extent). These concern many different dimensions of what we hear, including:

  • the rhythmic patterns 
  • melodic patterns 
  • timbral patterns 
  • dynamics (loud and soft) 
  • phrasing 
  • pitch 
  • intervals... and so forth. 

Each description exists within constraints which are partly produced by the other descriptions, and by other factors (like, for example, one's familiarity with the style). As the music unfolds, new descriptions (about form, climactic moments, harmonic progressions, etc) emerge and whose constraints will interact with (and transform) existing constraints - even (most powerfully in music) our emotional constraints.

I mention music because it is a form of communication which is extremely powerful and which does not make any external reference. Yet it tells us something about how we communicate, but there is an analytical puzzle here. The specification of the system is beyond reach, yet we sense the patterns, the repetition, the redundancy without having a sophisticated way of calculating it. We also identify that what we might consider to be "the same" at one moment in one context, we might later count as being fundamentally "different" in another (e.g. perhaps the same melody with a different harmony). Moreover, I suggest that at these moments of seeing something to be different that we once thought to be "the same" are moments of gaining deeper insight into the meaning being conveyed. My deepened understanding of the relationship between redundancy and the "specification of the system" explained by Loet is an example.

This, it seems to me, is the essence of what happens when we really communicate. The process, I suggest, is an emergent interaction of constraints. It requires multiple descriptions. As long as we attempt to convey singular descriptions in academic papers alone, communication in this sense is going to be very difficult - if not impossible.