Purpose of this blog
This is the first of three blogs that examine some basic assumptions about technology and education, based on a review of three books: ‘THE TOWER AND THE CLOUD‘, ‘CATCHING THE KNOWLEDGE WAVE‘, AND ‘THE INTEGRATION OF INFORMATION AND COMMUNICATIONS TECHNOLOGIES IN THE UNIVERSITY‘. (Click on the titles to see the reviews).
In this blog, I wish to examine and to some extent challenge the following assumption:
‘Because of the development of information and communications technologies, the nature of knowledge is changing, and that affects not only what we teach, but also how we teach.’
I should warn you that this is probably not a particularly suitable topic for a blog – an academic paper might be more appropriate to do the subject full justice. I should also warn you that I am not a professional philosopher (part of whose job is to discuss the nature of knowledge) and despite this, I am taking on some pretty heavy hitters, so I hope that readers will participate in the discussion of this blog and put me right where I have gone wrong!
What is knowledge and is it changing?
Jane Gilbert’s book, ‘Catching the Knowledge Wave’, most directly addresses the assumption that the nature of knowledge is changing. Drawing on publications by Manuel Castells (2000) and Jean-François Lyotard (1984), she writes (p. 35):
- ‘Castells says that…knowledge is not an object but a series of networks and flows…the new knowledge is a process not a product…it is produced not in the minds of individuals but in the interactions between people…..
- According to Lyotard, the traditional idea that acquiring knowledge trains the mind would become obsolete, as would the idea of knowledge as a set of universal truths. Instead, there will be many truths, many knowledges and many forms of reason. As a result… the boundaries between traditional disciplines are dissolving, traditional methods of representing knowledge (books, academic papers, and so on) are becoming less important, and the role of traditional academics or experts are undergoing major change.’
All these authors agree that the ‘new’ knowledge in the knowledge society is about the commercialisation or commodification of knowledge: ‘it is defined not through what it is, but through what it can do.’ (Gilbert, p.35). ‘The capacity to own, buy and sell knowledge has contributed, in major ways, to the development of the new, knowledge-based societies.’ (p.39)
I have no argument with the point of view that knowledge is the driver of most modern economies, and that this represents a major shift from the ‘old’ industrial economy, where natural resources (coal, oil, iron), machinery and cheap manual labour were the predominant drivers. I do though challenge the idea that knowledge itself has undergone radical changes.
The difficulty I have with the broad generalisations about the changing nature of knowledge is that there have always been different kinds of knowledge. I am reminded of my first job in a brewery in the East End of London in 1959. I was one of several students hired during our summer vacation. One of my fellow student workers was a brilliant mathematician. Every lunch hour the regular brewery workers played cards (three card brag) for what seemed to us large sums of money, but they would never let us play. My student friend was desperate to get a game, and eventually, on our last week, they let him in. They promptly won all his wages. He knew the numbers and the odds, but there was still a lot of non-academic knowledge he didn’t know about playing cards for money. Gilbert’s point is that in education academic knowledge has always been more highly valued in education than ‘everyday’ knowledge. However, in the ‘real’ world, all kinds of knowledge are valued, depending on the context. Thus while values regarding what constitutes ‘important’ knowledge may be changing, this does not mean that knowledge itself is changing.
Knowledge as a commodity
In a knowledge-based society, knowledge that leads to innovation and commercial activity is now recognised as critical to economic development. Again, there is a tendency to argue that this kind of knowledge – ‘commercial’ knowledge – is different from academic knowledge. I would argue that sometimes it is and sometimes it isn’t.
Academic versus applied knowledge
Gilbert makes the distinction between academic knowledge and applied knowledge (p. 159), and argues that in a knowledge society, there has been a shift in valuing applied knowledge over academic knowledge in the broader society, but this has not been recognised or accepted in education (and particularly the school system). She sees academic knowledge as associated with narrow disciplines such as mathematics and philosophy, whereas applied knowledge is knowing how to do things, and hence by definition tends to be multi-disciplinary. Gilbert argues (p. 159-160) that academic knowledge is:
- ‘authoritative, objective, and universal knowledge. It is abstract, rigorous, timeless – and difficult. It is knowledge that goes beyond the here and now knowledge of everyday experience to a higher plane of understanding…..In contrast, applied knowledge is practical knowledge that is produced by putting academic knowledge into practice. It is gained through experience, by trying things out until they work in real-world situations.’
Other kinds of knowledge that don’t fit the definition of academic knowledge are those kinds built on experience, traditional crafts, trail-and-error, and quality improvement through continuous minor change built on front-line worker experience – not to mention how to win at three card brag.
I agree that academic knowledge is different from everyday knowledge, but I challenge the view that academic knowledge is ‘pure’, not applied. It is too narrow a definition, because it thus excludes all the professional schools and disciplines, such as engineering, medicine, law, business, education that ‘apply’ academic knowledge. These are just as accepted and ‘valued’ parts of universities and colleges as the ‘pure’ disciplines of humanities and science, and their activities meet all the criteria for academic knowledge set out by Gilbert.
The relevance of academic knowledge in the knowledge society
My other quibble is that ‘academic knowledge’ is implicitly seen in these arguments as not relevant to the knowledge society – it is only applied knowledge now that matters. However – and this is the critical point – it has been the explosion in academic knowledge that has formed the basis of the knowledge society. It was academic development in sciences, medicine and engineering that led to the development of the Internet, biotechnology, digital financial services, computer software and telecommunication, etc. Indeed, it is no co-incidence that those countries most advanced in knowledge-based industries were those that have the highest participation rates in university education.
Again, though, I don’t want to downplay also the importance of non-academic knowledge in the growth of knowledge-based industries. These other forms of knowledge have proved just as valuable, and there is a significant shift in business in trying to manage the every-day knowledge of employees within a company through better internal communication, encouraging external networking, and rewards for collaboration and participation in improving products and services.
Education and knowledge
My argument here is that trying to distinguish between academic and applied knowledge misses the real point about the kind of education needed in a knowledge society. It is not just knowledge – both pure and applied – that is important, but also IT literacy, skills associated with lifelong learning, and attitudes/ethics and social behaviour. Gilbert surprisingly plays down the importance of both developing learning skills and the role of ICTs in teaching and learning (in the latter case, arguing that they are not properly integrated into teaching. Again, I don’t disagree that this is often a problem, but integrating ICTs into the curriculum needs to be part of the solution).
My point is that it is not sufficient just to teach academic content (applied or not). It is equally important also to enable students to develop the ability to know how to find, analyse, organise and apply information/content within their professional and personal activities, to take responsibility for their own learning, and to be flexible and adaptable in developing new knowledge and skills. All this is needed because of the explosion in the quantity of knowledge in any professional field that makes it impossible to memorise or even be aware of all the developments that are happening in the field, and the need to keep up-to-date within the field after graduating.
To do this learners must have access to appropriate and relevant content, know how to find it, and must have opportunities to apply and practice what they have learned. Thus learning has to be a combination of content, skills and attitudes, and increasingly this needs to apply to all areas of study. This does not mean that there is no room to search for universal truths, or fundamental laws or principles, but this needs to be embedded within a broader learning environment. This should include the ability to use ICTs as an integral part of their learning, but tied to appropriate content and skills within their area of study.
These skills and attitudes may also be seen as knowledge, although I would prefer to distinguish between knowledge and education, and I would see these changes more as changes in education. What is changing then is not necessarily knowledge itself, but our views on what educators need to do to ‘deliver’ knowledge in ways that better serve the needs of society. We need then to broaden our understanding of how best to help students acquire knowledge in ways that will be useful for them, but that does not necessarily mean rejecting academic knowledge as being now irrelevant.
Implications for teaching
The real change then is not to do with valuing academic or applied ‘knowledge’, but with moving away from a focus on teaching content, and instead on creating learning environments that enable learners to develop skills and networks within their area of study. Content is still crucial, and academic values even more so, but they are only part of the requirements now for preparing people for the 21st century. Of course, such a change has major implications for how we teach in universities, but it does not mean abandoning ‘academic knowledge’.
Why academic knowledge remains important
Indeed, more than ever, we need to sustain the elements of academic knowledge, such as rigour, abstraction and generalisation, empirical evidence, and rationalism. It is these elements of education that have enabled the rapid economic growth both in the industrial and the knowledge societies. The difference now is that these elements alone are not enough; they need to be combined with new approaches to teaching and learning.
I make this point because I am deeply skeptical of claims made about ‘new’ knowledge resulting from the use of the Internet. Chris Anderson, the editor of Wired Magazine, has argued (2007) that massive meta-data correlations can replace ‘traditional’ scientific approaches to creating new knowledge:
- ‘Google’s founding philosophy is that we don’t know why this page is better than that one: If the statistics of incoming links say it is, that’s good enough. No semantic or causal analysis is required. …This is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear. Out with every theory of human behavior, from linguistics to sociology. Forget taxonomy, ontology, and psychology. Who knows why people do what they do? The point is they do it, and we can track and measure it with unprecedented fidelity. With enough data, the numbers speak for themselves.
- The big target here isn’t advertising, though. It’s science. The scientific method is built around testable hypotheses. These models, for the most part, are systems visualized in the minds of scientists. The models are then tested, and experiments confirm or falsify theoretical models of how the world works. This is the way science has worked for hundreds of years. Scientists are trained to recognize that correlation is not causation, that no conclusions should be drawn simply on the basis of correlation between X and Y (it could just be a coincidence). Instead, you must understand the underlying mechanisms that connect the two. Once you have a model, you can connect the data sets with confidence. Data without a model is just noise. But faced with massive data, this approach to science — hypothesize, model, test — is becoming obsolete.’ (It should be noted this was written before derivative-based investments caused financial markets to collapse).’
Siemens (2004) argues that: ‘Connectivism presents a model of learning that acknowledges the tectonic shifts in society where learning is no longer an internal, individualistic activity….The pipe is more important than the content within the pipe.’ Downes (2006) has argued that new technologies now allow for the de-institutionalisation of learning. James Surowiecki (2004) in his book, ‘The Wisdom of Crowds’, argues that the aggregation of information in groups through diverse collections of independently-deciding individuals can result in decisions that are often better than could have been made by any single member of the group.
All these methods or approaches may help create new knowledge, and should be considered carefully in terms of their implications for teaching and learning, but in my view they are still dependent on the individuals contributing to such aggregated data being educated in rationalistic, evidence-based decision-making, which requires some form of academic education. The danger is that if knowledge is created by the actions of people without such an education, the world becomes a slave to irrationality, prejudice and ignorance.
To summarise then: the answer, as always with philosophical questions, is that it all depends. In particular it depends on our definition of knowledge. If it is believed that the only ‘true’ knowledge is academic knowledge based on pure science and absolute truths, then yes, knowledge is changing. However, I suggest that this is a straw man. There has always been a range of different types of knowledge, and their value depends on the context in which the knowledge is used. This is true even in universities, where applied and pure knowledge usually exist comfortably side by side.
In a knowledge-based society, particular emphasis is placed on the utility of knowledge for commercial purposes. This may result in putting more emphasis on certain types of immediately practical knowledge over longer term research, for instance, but because of the strong relationship between pure and applied knowledge, this would probably be a mistake, even in terms of economic development. The issue is not so much the nature of knowledge, but how students or learners come to acquire that knowledge and learn how it can be used. This requires a movement away from a focus on merely teaching content, and more emphasis on developing learning skills of how best to apply knowledge. Since knowledge is dynamic, expanding and constantly changing, learners need to develop the skills and learn to use the tools that will enable them to continue to learn.
In a knowledge-based society, ICTs are essential for the development of lifelong learning and therefore need to be embedded within the knowledge base of a particular area of study. Academic knowledge though will remain important because of the utility of such knowledge for creating and supporting knowledge-based industries (and, incidentally but equally importantly, for enabling learners to participate fully personally and socially within a knowledge-based society.) However, it is not, and never has been, the only form of knowledge valuable for economic or social development.
As I said, a blog is probably not the best way to address this issue (does this mean that new technologies such as blogs, and Twitter, with its limit of 140 characters, undermine academic knowledge?)
However, as I said at the beginning, I am not a specialist in the nature of knowledge, and I will be interested in your comments, corrections or spin on this topic.
See also: Information rich and attention poor
Anderson, C. (2007) The End of Theory: The Data Deluge Makes the Scientific Method Obsolete Wired Magazine, 16:07
Castells, M. (2000) The Rise of the Network Society Oxford: Blackwell
Lyotard, J-F, (1984) The Post-Modern Condition: A Report on Knowledge Manchester: Manchester University Press
Siemens, G. (2004) ‘Connectivism: a theory for the digital age’ eLearningSpace, December 12, accessed on 11 March 2009 at: http://www.elearnspace.org/Articles/connectivism.htm
Surowiecki, J. (2004) The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations New York: Random House