Mirjam Neelen & Paul A. Kirschner
It’s a popular thing to say nowadays: Human knowledge is no longer really important because with Google we have the world in our smartphones. It really makes sense, doesn’t it? Why would we need to know anything if we can look it all up so easily?
This blog explores to what extent Google® allows us to stop building knowledge and focus our attention on more interesting, fascinating, and engaging things. Whatever these may be.
Knowledge Transfer and Rote Knowledge
There are quite a number of misconceptions on what knowledge is so let’s start with a simple definition. The Oxford Dictionary online defines knowledge as “facts, information, and skills acquired through experience or education; the theoretical or practical understanding of a subject.”
The ‘we no longer need human knowledge’ proponents usually justify this standpoint with criticism of the educational system. They argue that there’s too much knowledge transfer (e.g. Nick Shackleton-Jones’ post here) and rote knowledge (e.g. this article in the Independent[1]) taught in the classroom.
First, let’s reveal a deep-kept secret. Knowledge transfer as in ‘transferring knowledge from one individual to another’ doesn’t exist. The term is generally used in organisational theory. For example, Linda Argote and Paul Ingram define it as the process through which one unit (for example, a group, department, or division) in an organisation is affected by the experience of another. The term is also used in cognitive psychology. In this context it doesn’t mean transferring knowledge from one individual to another but rather refers to how knowledge acquired in one situation applies (or fails to apply) to another. More specifically, it refers to how individuals use prior knowledge to solve novel problems (Nokes-Malach & Richey, 2015). In other words, as knowledge transfer doesn’t exist, it really can’t be a very valid argument.
Rote knowledge is the other bogeyman of education. Dan Willingham informally defines rote knowledge as “memorising in the absence of meaning” in here. Rote knowledge, however, is “essential for meaningful learning and problem solving when that knowledge is used in more complex tasks” (Mayer, 2002, p. 228). For example, some things, such as the alphabet and multiplication tables need to be automated in order to be able to complete more complex tasks such as reading and maths. However, Willingham explains that the term rote knowledge is very much ‘overused’. In fact, what a lot of people perceive as rote knowledge actually is inflexible knowledge. Inflexible knowledge differs from rote knowledge in that while it’s meaningful it’s also narrow. This narrowness comes from the fact that it’s tied to a concept’s surface structure only. So, an individual might be able to explain a concept, recognise an example, or apply it in certain contexts. What’s critical to get your head around is that although flexible knowledge might be the ultimate desirable goal, it’s not easy to achieve. To apply old knowledge to new situations, one must both recognise the “truth” in the concepts at hand and then successfully map the new problem to the familiar problem. Knowledge is often inflexible because people tend to store it in terms of surface features. Maybe it’s just the case that those who claim that knowledge is no longer important because of Google have stored the term “knowledge” as a surface structure in their brains and not as a deep structure, and thus really don’t understand it.
It’s normal that knowledge is inflexible when first learned. When you continue to ‘use’ the knowledge, you gain expertise and the knowledge will be organised around deep structures (cognitive schemata). Now, because the majority of people is not an expert in any given field, we need to acknowledge that most people are in the space of inflexible knowledge. The question is, what kind of knowledge does Google have to offer?
Google’s knowledge at our fingertips?
A popular saying, as for example expressed in Erika Andersen’s blog is that “all the knowledge of the world and all of man’s creation is at our fingertips.” First, it’s incorrect and second it’s dangerous to believe.
Why is it incorrect? The examples that people use to make their point are usually similar to Erika Andersen’s example of when she was knitting a skirt and needed to use a certain technique that she hadn’t used before. To remedy this, she went online, found a YouTube® video and finished up her skirt. Of course it’s great that she found a way to achieve her goal by using the Internet, but is it knowledge? Actually, it isn’t. She uses information. In other words, she has a heck of a lot of information at her fingertips, but NO knowledge. Figure 1 illustrates the difference.
The Differences between Data, Information, and Knowledge (Image Source)
The knitting technique that she found, is captured data (information). And she could only find it and make use of it BECAUSE she had a certain amount of knowledge about knitting while the reason that she could use it is because she apparently also had some skill in knitting. Without that knowledge and skill, nothing could be looked up, found, and applied. Also, in this case, it’s just one example of how to apply the knitting technique captured on video. There might be better, more efficient ways that perhaps she will discover over time, if she applies the technique multiple times. She might start to put certain pieces of the puzzle together and create her own knowledge on how to best apply the technique. In short, after you process information, you must assign meaning to it, and tie it into pre-existing knowledge (i.e., the already existing schemata in your long term memory).
Neil Ingebrigtsen explains:
You can’t currently store knowledge in anything other than a brain, because a brain connects it all together. Everything is inter-connected in the brain. Computers are not artificial brains. They don’t understand what they are processing, and can’t make independent decisions based upon what you tell them.
Second, the claim that the Internet gives us all the word’s knowledge at our fingertips is dangerous to believe. If we accept that we no longer need to memorise facts because we can rely on the Internet (see for example Sasha Pleasance’s recent article), this will automatically impact the way we teach our children. Why teach them facts that they can find in a heartbeat? The reason to teach those facts is because, as Willingham explained, it’s not just about memorising facts (rote knowledge), it’s about inflexible knowledge first and when we’re becoming more advanced, about flexible knowledge next. Without this you get presidential candidates like Michelle Bachmann who mistake John Wayne for John Wayne Gacy.
Willingham explains in here why knowledge is absolutely critical. It makes learning easier in the way that over time knowledge doesn’t just accumulate, rather it grows exponentially. In addition, factual knowledge enhances cognitive processes like problem solving and reasoning. First, knowledge helps us to take in more information, evaluate the new information as to its veracity and usefulness, think about new information, and remember new information. Second, it helps us solve problems by freeing up space in our working memory and it helps us circumvent thinking because we have access to a ready supply of things we’ve already thought about.
Research on human expertise confirms Willingham’s explanation. Timothy Nokes and colleagues conclude that both declarative[2] and procedural[3] knowledge is critical to solve complex problems. For example, an expert’s prior knowledge ensures that (s)he’s better able to recognise and recall relevant patterns or chunks of information. Micheline Chi and her colleagues explain in their 1981 article how this helps to solve problems by looking at the difference between novices and experts when they solve physics problems. Experts analyse the problem before they move on to possible appropriate solutions. The idea is that the early phase of problem solving involves the activation and confirmation of an appropriate knowledge structure (or schema). When the schema is confirmed, it directs the expert to the best solution. Novices do this completely differently using a means-ends analysis (a weak problem solving method) in which they search forward, selecting partial solutions reduce the distance to the solution bringing them just one step further at a time. Although both novices and experts deal with “unknowns” when solving complex problems, the expert is much better in determining appropriate solutions quicker because their initial analysis, based on their knowledge, restricts possible solutions more effectively and more efficiently.
All this leads us to conclude that if we don’t have knowledge and only depend on the information in the cloud, what will happen is what William Poundstone articulates in the Guardian: The cloud will make us mega-ignorant: unaware of what we don’t know. No matter how you slice or dice it, Google® can’t and shouldn’t replace individual human knowledge. In order to be able to learn, we still need to acquire knowledge in our own individual brains and we’re (not really) sorry to say that even Google can’t change that.
Resources
Andersen, E., (2012). All the Knowledge of the World At Your Fingertips [Blog post]. Retrieved from http://erikaandersen.com/2012/07/all-the-knowledge-of-the-world-at-your-fingertips.html
Chi, M. T. H., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science. 5(2), 121–152
Ingebrigtsen, N., (n.d.) The Differences Between Data, Information, and Knowledge [Blog post]. Retrieved from http://www.infogineering.net/data-information-knowledge.htm
Mayer, R. E., (2002). Rote versus meaningful learning. Theory Into Practice, 41, 226-232. Retrieved from http://web.mit.edu/jrankin/www/teach_transfer/rote_v_meaning.pdf
Nokes-Malach, T. J. & Richey, J. E., (2015). Knowledge Transfer. In R. Scott, & S. Kosslyn (Eds.), Emerging Trends in the Social and Behavioral Sciences. John Wiley & Sons, Inc. Available from http://www.lrdc.pitt.edu/BOV/documents/Nokes-Malach%20&%20Richey,%202015.pdf
Nokes, T. J., Schunn, C. D., & Chi, M. T. H., (2010). Problem solving and human expertise. International Encyclopedia of Education, 5, 265-272. Available at http://www.lrdc.pitt.edu/schunn/papers/Nokes,%20Schunn,%20&%20Chi,%202010.pdf
Pleasance, S., (2017, February 9). New GCSEs are not qualifications for the 21st century. Retrieved on https://www.tes.com/news/further-education/breaking-views/new-gcses-are-not-qualifications-21st-century
Willingham, D. T, (2002). Inflexible knowledge: The first step to expertise. American Educator, 26(4), p 31-33. Retrieved from http://www.aft.org/periodical/american-educator/winter-2002/ask-cognitive-scientist
Willingham, D. T., (2006). How knowledge helps. American Educator, Spring, 30-37.Retrieved from http://www.aft.org/periodical/american-educator/spring-2006/how-knowledge-helps
[1] Because you have to sign up to be able to read this article, I’ve copied the critical quote here: “We are introducing much needed changes to the Junior Cycle which will liberate students, and yes, their teachers, from the tyranny of teaching to the test, rote learning and a narrowly focused terminal exam.”
[2] Declarative knowledge consists of descriptions about the world including facts, strategies, and principles, and is commonly referred to as knowing that.
[3] Procedural knowledge is information for how to perform particular actions to accomplish task goals, and is commonly referred to as knowing how.
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Reblogged this on onderwijs_2032 science check.
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Hi Mirjam, Hi Paul! Thanks for this article, and for engaging in debate. I think you make a number of errors and logical mis-steps in this piece. If I point them out one by one please do not mistake my intent, which is friendly!
You start with a definition of knowledge which implies the transfer of knowledge from one person to another (since this is typically what happens in education, i.e. from teacher to student) then go on to say it doesn’t really exist.
Your grounds for saying it doesn’t exist seem to be that the term is used in organisational theory – which is a criticism of the term, not the activity. Clearly it is silly to come up with a counter-intuitive definition of a term and then say ‘so the argument is not valid’. This is like saying ‘Martians define cars as violent offenders, so clearly they are not inanimate objects.’
Your argument against rote learning is weak. You say we need to memorise multiplication tables in order to do maths. This is patently false. Quoting Mayer (2002) does not make it true. You attempt to make a distinction between inflexible and flexible knowledge. You say that it is normal that knowledge is inflexible when it is first learned. Are you saying that if I burn my hand on a fire, it will take many more trials before I can generalise this learning to other situations? It does seem like an idea worthy of further explanation – but you are not very convincing here.
Your central argument however is hopelessly circular. In a nutshell you are saying ‘Something can only be knowledge if it’s in your head; so by definition Google can’t be knowledge.’ You even have a diagram to say the same thing. This is just sophistry and not a constructive contribution to the debate in my view.
You do make a valid point that you need a certain amount of knowledge to access knowledge – but this is where my argument picks up: you need far less to use an iPad (which comes with no manuals) than a 1990s minicomputer (where you need to learn to program). How far can we reduce this knowledge required? People who talk about a ‘zero learning curve OS (see the TED talk) think we might be able to reduce it to (almost) zero.
I agree that brains are not computers (indeed this is the thrust of the affective context model) but the argument sounds dangerously like the familiar ‘computers can never be conscious because only brains can be conscious’ argument – i.e. you dodge the real debate by playing with definitions.
You make some wild claims about factual knowledge ‘growing exponentially’ and ‘enhancing cognitive processing’ – I have also seen claims that the educational system makes people less creative in problem-solving.
The working memory argument is silly: we don’t ‘free up’ working memory by memorising facts, since working memory holds whatever we are thinking about at a given point in time regardless of whether or not it is stored in long-term memory (i.e. it would be just as effective to write things down or look them up).
Finally, there is something about deep expertise and schema which we lose as we externalise knowledge. I agree. I share your nostalgia, but we will all have to get over it. Nobody is going to learn how to use slide rules anymore. When translation becomes reliable and automated no doubt people will weep over the demise of language learning.
Your conclusion doesn’t follow from your arguments. People will make mistakes when they look things up on Google. SatNav sometimes sends us the wrong way. But it is getting much, much better and we are more likely to get lost with a map. We might not like the way things are headed, but I’d rather be facing forward.
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Hi Nick, thanks for taking (a lot of!) time to respond to our blog and of course thank you for the friendly intent :).
First of all, to me the definitions actually are critical because if we don’t agree on the definition we’re speaking a different language and that is never helpful.
I have said to you before that I think your view on education is actually offensive to experts in that field. If I were a teacher I would gasp in response to your statements that teachers “typically transfer knowledge”. I therefore strongly disagree that the definition that we use in our blog is implying ‘transfer’ in any way. That is your interpretation based on your view on education.
You’re also saying that the reasoning is circular. It’s not circular, it’s simple. Claim A. Knowledge can only be stored in your brain (definition of knowledge and explanation of how knowledge develops follows to underpin claim A) and thus, B. what Google gives us is not knowledge, it’s information.
All the rest… I’m not sure what to say. Your example of the burnt hand is silly. Of course we remember some things after only one time but many things we need to repeat and practise until we drop. And yes, some of these things might be taken over by computers as you say (e.g. language learning, navigation, and well, endless more things).
Your understanding of working memory is fundamentally flawed. We don’t always ‘hold whatever we are thinking about at a given point in time regardless of whether or not it is stored in LTM’. The more expertise you have the less you need to ‘hold’ stuff in your working memory because you build mental models that you’re relying on. We actually DO ‘free up’ working memory as you say as we’re using it more efficiently when we have more knowledge on a topic, e.g. we quickly recognise patterns because we have schemas that we have access to. I would strongly recommend to read research on expertise and the different ways experts learn compared to novices.
Last but not least, I’m not nostalgic (I’m not that old! ;)). I acknowledge and accept that some things are changing rapidly. What I don’t accept is that expertise will be perceived as ‘no longer needed’, which I strongly believe will lead to dangerous situations. Ignorant people who are completely unaware how unaware they are. And that is a concern.
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Anyone who has been either a student or an educator (I have been both) will know there comes a point where in order to pass you need to memorise some information. In the case of history this might be names or dates, for example. Students will therefore ‘cram’ for exams – highlighting passages from textbooks, or revising the notes that they have written down as we talked. Of course, as educators, we hope that there is more to their learning than the regurgitation of facts. As a psychology lecturer I hoped that students would develop a deeper appreciation of human differences, an enquiringly mind and a desire to look deeper – but whilst these may be the enduring value of education they are not easy to test. As Einstein remarked ‘not all that can be measured matters, and not all that matters can be measured’. It is regrettable that in the rush to prepare students for tests of knowledge we squander time that might be spent doing something more valuable. We can rename the problem if you like – but I am really more interested in how we tackle it.
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Nick,
Two things:
1. Knowledge is the basis of all handling. Application, discussion, creativity and even enquiry without having knowledge of what you apply, discuss, invent, or what to look for when enquiring is virtually if not completely worthless.
2. Please get your quotes straight. William Bruce Cameron said what you are attributing to Albert Einstein. Cameron’s 1963 text “Informal Sociology: A Casual Introduction to Sociological Thinking” contained the following passage (thanks to my previous knowledge of the many quotes falsely attributed to Einstein) which I now document thanks to Quote Investigator:
It would be nice if all of the data which sociologists require could be enumerated because then we could run them through IBM machines and draw charts as the economists do. However, not everything that can be counted counts, and not everything that counts can be counted.
paul
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I disagree, Nick. Learning curve and understanding/application are not the same. In many cases, a learning curve helps understanding. Especially when metacognitive processes are in place. This is part of what grows expertise. You might argue that expertise isn’t needed or won’t be needed in the future. I would argue it will be needed more than ever.
You say, “learning is the process by which people attach emotional (or affective) sense to information.” That may be true in some circumstances, especially when there is enough prior knowledge to put it into context. But it’s an overly narrow definition. A better definition needs to include the ability to use knowledge for desired purposes. Otherwise, information is inert and of little use.
We can agree to disagree.
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I’ve noticed that critics of rote memorization love to trot out this stuff about memorizing names and dates to pass an exam. In reality, we couldn’t carry out even the most basic of tasks without relying on a huge baseline of memorized facts.
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How true!
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