2.7 Is the nature of knowledge changing?

A.W. (Tony) Bates; Darin Jerke

18

Figure 2.8 academic knowledge is a second-order form of knowledge that seeks abstractions and generalizations based on reasoning and evidence Image: © Wallpoper/Wikipedia — Figure 2.7 Academic knowledge is a second-order form of knowledge that seeks abstractions and generalizations based on reasoning and evidence Image: © Wallpoper/Wikipedia

2.7.1 Knowledge and technology

Before moving on to the more pragmatic elements of teaching in a digital age, it is necessary to address the question of whether the development of digital technologies has actually changed the nature of knowledge, because if that is the case, then this will influence strongly what needs to be taught as well as how it will be taught.

Connectivists such as Siemens and Downes argue that the Internet has changed the nature of knowledge. They argue that “important” or “valid” knowledge now is different from prior forms of knowledge, particularly academic knowledge. Downes (2007) argues that new technologies allow for the de-institutionalization of learning. Chris Anderson, the editor of Wired Magazine and now Curator of Ted Talks, suggests (2008) 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, mainly because those using them did not understand the underlying logic that created the data).

Jane Gilbert’s book, ‘Catching the Knowledge Wave’ (2005), directly addresses the assumption that the nature of knowledge is changing. Drawing on publications by Manuel Castells (2009) 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.’

Back in the 1960s Marshall McLuhan (1964) argued that the medium is the message; the way information is represented and transmitted is changed and so is our focus and understanding as information moves between and within different media. If information and knowledge are now represented and more significantly now flow differently, how does that affect educational processes such as teaching and learning?

One way knowledge is certainly changing is in the way it is represented. It should be remembered that Socrates (according to Plato) criticized writing because it could not lead to “true” knowledge which came only from verbal dialogue and oratory. Writing however is important because it provides a permanent record of knowledge. The printing press was important because it enabled the written word to spread to many more people. As a consequence, scholars could challenge and better interpret, through reflection, what others had written, and more accurately and carefully argue their own positions. Many scholars believe that one consequence of the development of mass printing was the Renaissance and the age of enlightenment, and modern academia consequently came to depend very heavily on the print medium.

Now we have other ways to record and transmit knowledge that can be studied and reflected upon, such as video, audio, animations, and graphics, and the Internet does expand enormously the speed and range by which these representations of knowledge can be transmitted. We shall also see in Chapter 8 and Chapter 9 that that media are not neutral, but represent meaning in different ways.

2.7.2 Knowledge as a commodity

All the above authors agree that the “new” knowledge in the knowledge society is about the commercialization 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).

In a knowledge-based society, particular emphasis is placed on the utility of knowledge for commercial purposes. As a result, there is 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 is probably 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. As I argued in Chapter 1, this requires more emphasis on developing and learning skills of how best to apply knowledge, rather than a focus on merely teaching content. Also, it will be argued later in the book that students have many more sources of information besides the teacher or instructor and that a key educational issue is the management of vast amounts of 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.

But does this mean that knowledge itself is now different? I will argue that in a digital age, some aspects of knowledge do change considerably, but others do not, at least in essence. In particular, I argue that academic knowledge, in terms of its values and goals, does not and should not change a great deal, but the way it is represented and applied will and should change.

2.7.3 The nature of academic knowledge

Academic knowledge is a specific form of knowledge that has characteristics that differentiate it from other kinds of knowledge, and particularly from knowledge or beliefs based solely on direct personal experience. In summary, academic knowledge is a second-order form of knowledge that seeks abstractions and generalizations based on reasoning and evidence.

Fundamental components of academic knowledge are

transparency,
codification,
reproduction, and
communicability.

Transparency means that the source of the knowledge can be traced and verified. Codification means that the knowledge can be consistently represented in some form (words, symbols, video) that enables interpretation by someone other than the originator. Knowledge can be reproduced or have multiple copies. Lastly, knowledge must be in a form such that it can be communicated and challenged by others.

Laurillard (2001) recognizes the importance of relating the student’s direct experience of the world to an understanding of academic concepts and processes, but she argues that teaching at a university level must go beyond direct experience to reflection, analysis, and explanations of those direct experiences. Because every academic discipline has a specific set of conventions and assumptions about the nature of knowledge within its discipline, students in higher education need to change the perspectives of their everyday experience to match those of the subject domain.

As a result, Laurillard argues that university teaching is “essentially a rhetorical activity, persuading students to change the way they experience the world” (p.28). Laurillard then goes on to make the point that because academic knowledge has this second-order character, it relies heavily on symbolic representation, such as language, mathematical symbols, “or any symbol system that can represent a description of the world, and requires interpretation” (p.27) to enable this mediation to take place.

If academic knowledge requires mediation, then this has major significance for the use of technology. Language (i.e. reading and speaking) is only one channel for mediating knowledge. Media such as video, audio, and computing can also provide teachers with alternative channels of mediation.

Laurillard’s reflections on the nature of academic knowledge are a counter-balance to the view that students can automatically construct knowledge through argument and discussion with their peers, self-directed study, or the wisdom of the crowd. For academic knowledge, the role of the teacher is to help students understand not just the facts or concepts in a subject discipline, but the rules and conventions for acquiring and validating knowledge within that subject discipline. Academic knowledge shares common values or criteria, making academic knowledge itself a particular epistemological approach.

2.7.4 Academic versus applied knowledge

In a knowledge-based society, knowledge that leads to innovation and commercial activity is now recognized 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 is not.

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 labor were the predominant drivers. I do though challenge the idea that the nature of knowledge has undergone radical changes.

The difficulty I have with the broad generalizations about the changing nature of knowledge is that there have always been different kinds of knowledge. One of my first jobs was 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 with them. 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 did not know about playing cards for money, especially against a group of friends playing together rather than against each other. Gilbert’s point is that 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 beliefs about what constitutes “important” knowledge may be changing, this does not mean that the nature of academic knowledge is changing.

Gilbert 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 recognized 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 do not fit the definition of academic knowledge are those kinds built on experience, traditional crafts, trial-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.

Making a distinction between academic and applied knowledge misses the real point about the kind of education needed in a knowledge society and a digital age. It is not just knowledge – both pure and applied – that is important, but also digital literacy, skills associated with lifelong learning, attitudes/ethics, and social behavior.

Knowledge is not just ‘stuff’, or fixed content, but it is dynamic. Knowledge is also not just ‘flow’. Content or ‘stuff’ does matter as well as the discussions or interpretations we have about content. Where does the ‘stuff’ come from that ebbs and flows over the discussions on the internet? It may not originate or end in the heads of individuals, but it certainly flows through them, where it is interpreted and transformed. Knowledge may be dynamic and changing, but at some point each person does settle, if only for a brief time, on what they think knowledge to be, even if over time that knowledge changes, develops or becomes more deeply understood. Thus ‘stuff’ or content does matter, though knowing (a) how to acquire content and (b) what to do with content we have acquired, is even more important.

Thus 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, analyze, organize 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 memorize 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 digital technologies as an integral part of learning, but tied to appropriate content and skills within their area of study.

Also, the importance of non-academic knowledge in the growth of knowledge-based industries should not be ignored. These other forms of knowledge have proved just as valuable. For instance, it is important within a company to manage the every-day knowledge of employees through better internal communication, encouraging external networking, and rewards for collaboration and participation in improving products and services.

2.7.5 The relevance of academic knowledge in the knowledge society

An over-emphasis on the functionality of knowledge will result in “academic knowledge” being implicitly seen as irrelevant to the knowledge society. However, 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 telecommunications. Indeed, it is no coincidence that those countries most advanced in knowledge-based industries were those that have the highest participation rates in university education.

Thus while academic knowledge is not “pure” or timeless or objectively “true,” it is the principles or values that drive academic knowledge that are important. Although it often falls short, the goal of academic studies is to reach for deep understanding, general principles, empirically-based theories, timelessness, etc., even if knowledge is dynamic, changing, and constantly evolving. Academic knowledge is not perfect, but does have value because of the standards it requires. Nor have academic knowledge or methods run out of steam. There is evidence all around us: academic knowledge is generating new drug treatments, new understandings of climate change, better technology, and certainly new knowledge generation.

Indeed, more than ever, we need to sustain the elements of academic knowledge, such as rigor, abstraction, evidence-based generalization, empirical evidence, rationalism, and academic independence. 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.

2.7.6 Academic knowledge and other forms of knowledge

As mentioned earlier, there are many other forms of knowledge that are useful or valued besides academic knowledge. There is increasing emphasis from government and business on the development of vocational or trades skills. Teachers or instructors are responsible for developing these areas of knowledge as well. In particular, skills that require manual dexterity, performance skills in music or drama, production skills in entertainment, skills in sport or sports management, are all examples of forms of knowledge that have not traditionally been considered “academic.”

However, one feature of a digital society is that increasingly these vocational skills are now requiring a much higher proportion of academic knowledge or intellectual and conceptual knowledge as well as performance skills. For example, higher levels of ability in math and/or science are now demanded of many trades and professions such as network engineers, power engineers, auto mechanics, nurses, and other health professionals. The “knowledge” component of their work has increased over recent years.

The nature of the job is also changing. For instance, auto mechanics are now increasingly focused on diagnosis and problem-solving as the value component of vehicles becomes increasingly digitally based and components are replaced rather than repaired. Nurse practitioners now are undertaking areas of work previously done by doctors or medical specialists. Many workers now also need strong interpersonal skills, especially if they are in front-line contact with the public. At the same time, as we saw in Chapter 1, more traditionally academic areas are needing to focus more on skills development, so the somewhat artificial boundaries between pure and applied knowledge are beginning to break down.

In summary, a majority of jobs now require both academic and skills-based knowledge. Academic and skills-based knowledge also need to be integrated and contextualized. As a result, the demands on those responsible for teaching and instruction have increased, but above all, these new demands of teachers in a digital age mean that their own skills level needs to be increased to cope with these demands.

Activity 2.7 Epistemology and academic knowledge

1. Can you state the epistemological position that drives your teaching? Does it fit with any of the epistemological positions described in this chapter? How does that work out in practice in terms of what you do?

2. Can you justify the role of “teacher” in a digital society where individuals can find all they need on the Internet and from friends or even strangers? How do you think that the role of the teacher might, could, or should change as a result of the development of a digital society? Or are there “constants” that will remain?

3. Briefly define the subject area or specialty in which you are teaching. Do you agree that academic knowledge is different from everyday knowledge? If so, to what extent is academic knowledge important for your learners? Is its importance growing or diminishing? Why? If it is diminishing, what is it being replaced with – or what should replace it?

Feedback to come