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) 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 and procedural 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.
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
 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.”
 Declarative knowledge consists of descriptions about the world including facts, strategies, and principles, and is commonly referred to as knowing that.
 Procedural knowledge is information for how to perform particular actions to accomplish task goals, and is commonly referred to as knowing how.