GUEST POST: Learning is Multidimensional -- Embrace the Complexity!

GUEST POST: Learning is Multidimensional -- Embrace the Complexity!

By James Mannion

James Mannion is a final year PhD student at the University of Cambridge, and an Associate of the University College London Institute of Education. He is also the Director of Rethinking Education, and the founder of Praxis Teacher Research. He blogs at www.rethinking-ed.org/blog, and is @rethinking_ed on Twitter.

Here are 5 statements about learning that I have come across in the last year:

  • “Learning is what happens when you think hard.” Prof. Rob Coe (1)
  • “Learning is impossible without extended practice.” Joe Kirby (Pragmatic Education Blog)
  • “Learning is acquiring knowledge and skills and having them readily available from memory so you can make sense of future problems and opportunities.” Prof. Henry L. Roediger (The E-Learning Coach Podcast)
  • “If nothing has changed in long-term memory, nothing has been learned.” Prof. Kirschner (2, p77)
  • “Learning and memory are closely related concepts. Learning is the acquisition of skill or knowledge, while memory is the expression of what you’ve acquired. Another difference is the speed with which the two things happen. If you acquire the new skill or knowledge slowly and laboriously, that’s learning. If acquisition occurs instantly, that’s making a memory.” (3)

Each of these statements are made with a strong sense of certainty: “Learning is X”. But what if learning is more than just *a thing* which can be defined in a single sentence? What if learning is… multidimensional?

Image from Wikimedia.org

Image from Wikimedia.org

Nine dimensions of learning

Here, I have outlined 9 possible dimensions of learning – some of which feature in the statements above, most of which do not. Please note that this is not intended as an exhaustive list – it is presented as a conversation-starter about the many facets of learning that exist in the literature.

1: Learning as retention

To the extent that learning is synonymous with retention of information in memory, the spectrum almost writes itself. At one end, we have stuff that is immediately forgotten. At the other, we have things that are learned to the point of automaticity: your name, where you live, the fact that socks go on your feet.

But even within the realm of memory, there are more things to consider than mere retention. Here are 3 dimensions of learning related to aspects of memory:

2: Implicit vs explicit memory

Implicit memory is sometimes referred to as automatic or unconscious memory, which may be expressed in the absence of deliberate recollection: the ability to ride a bike, button a shirt, play the piano (4). These particular examples are also examples of procedural memory; however, implicit memory does not have to be procedural. For example, a student "guessing" the answer to a question because they do actually know the answer but they don't realize that they know it would also be classified as implicit memory. Implicit memory can also include behaviors such as locking the door as you leave the house, or associations such as those related to smells. Explicit memory (also known as declarative memory or direct memory), on the other hand, involves the conscious, intentional remembering of information. Remembering your bank details is an example of explicit memory.

 3: Semantic vs episodic

Explicit (declarative, direct) memory is divided into two further types. Semantic memory is the recall of general facts, while episodic memory is recall of personal experiences. Remembering the capitals of countries is an example of semantic memory, whereas being able to recall what happened on the way to school is an example of episodic memory. Episodic memory necessarily involves the ability to perform mental time-travel (5).

4: Recall vs recognition

Psychologists distinguish between two types of memory retrieval. Recognition refers to our ability to, umm, recognize an event or piece of information as having been experienced in the past. This is the kind of memory that students are required to use in a multiple choice test. Recall, on the other hand, requires the production of information. The educational equivalent of this would be writing an essay. Recall is generally considered to require a greater depth of information processing, storage, and retrieval than recognition; however, this may not always be the case (5).

However, memory is not the only game in town as far as learning is concerned. Here are 5 more dimensions of learning:

5: Naturally occurring vs. elicited data

Some things we learn can be considered naturally occurring data: your siblings’ names, say, or the names for common foods. Other things we learn are elicited: you go out of your way to learn it. This is something often considered by social scientists - e.g. whether to use naturally occurring or elicited data when researching schools, or a combination of the two. As well as simply describing data, this can be seen as a kind of continuum that overlaps to some extent with what schools often refer to as ‘attitude to learning’. At the ‘elicited’ end of the spectrum, we find the autodidact. At the opposite end, the incurious drifter who takes life as it comes. In the UK, some schools require teachers to enter a grade for ‘attitude to learning’ alongside attainment data. It is an entirely spurious rating (often on a scale from 1 to 6) and highly problematic – some schools even publish the scores in corridors to “name and shame” disruptive pupils.

6: Intrinsic vs extrinsic motivation

Compare these two statements: “I am learning to solve a Rubik’s cube because I enjoy the challenge.” “I am learning to solve a Rubik’s cube so I can show off to my friends.” Each of these motivations may be strong or weak. We also may hold several such positions simultaneously. Teachers might increase intrinsic motivation (and, consequently, learning) by explaining the real-world significance of a task (6), or by setting multidimensional tasks such as project-based learning (7).

Image from freepngimages.com

Image from freepngimages.com

7: Classical vs operant conditioning

Classical conditioning is defined as “a learning process that occurs when two stimuli are repeatedly paired: a response which is at first elicited by the second stimulus is eventually elicited by the first stimulus alone” (Oxford English Dictionary). Classical conditioning forms the basis of much animal training, where treats are used to elicit desirable behaviors. However, classical conditioning may also feature in certain types of school-based learning, such as training students to tidy up by playing a particular piece of music, which is common practice in schools. Operant conditioning is defined as “a type of learning in which a behavior is strengthened (meaning, it will occur more frequently) when it's followed by reinforcement, and weakened (will happen less frequently) when followed by punishment” (Oxford English Dictionary). This idea underpins many schools' behavior management systems.

8: Inductive vs deductive reasoning (8)

Inductive reasoning is essentially a “bottom up” approach to learning. For example, students may be presented with several examples of a phenomenon (e.g. photographs with examples of specific animal adaptations) and they are required to identify general patterns or “rules” (e.g. camouflage, body size, ear shape).

Deductive reasoning is a “top-down” approach to learning. In the example above, students may be taught types of adaptations types of adaptations first, and then these “rules” are tested with particular examples (e.g. the photos of animal adaptations).

9: Significant vs less significant learning

Carl Rogers once wrote: “It seems to me that anything that can be taught to another is relatively inconsequential and has little or no significant influence on behaviour. I realize increasingly that I am only interested in learnings which significantly influence behaviour.” (9)

It is worth noting that Rogers was a psychotherapist, and not a teacher. Also, significance is rather a subjective notion. Nevertheless, since almost all students ask the question “Why do I need to learn this?” at some point or other in their school career – understandably, some might say – the question of significance remains worthy of reflection.

In summary: Let’s embrace the complexity!

Image from Wikimedia.org

Image from Wikimedia.org

Reflecting upon all of the above, I can only conclude that as far as educators are concerned, the word ‘learning’ is so broad as to be essentially meaningless. We might think of 'learning' as an umbrella term at best, taken to mean something like "the thing we want students to do". Beyond that, we really need to roll our sleeves up and start talking about the specific kinds and features of learning that we're interested in.

With this in mind, I have proposed a glossary of 225 learning terms. It is by no means an exhaustive list, and I would welcome any suggestions for how it might be improved. But as an attempt to embrace learning in all its complexity, it’s a start.


References:

 (1) Coe, R. (2013) Improving Education: A triumph of hope over experience. Inaugural Lecture of Professor Robert Coe, Durham University, 18 June 2013. Available at http://www.cem.org/attachments/publications/ImprovingEducation2013.pdf.

(2) Kirschner, P., Sweller, J. & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41, 75–86.

(3) Kazdin, A. E. (2000). Encyclopedia of Psychology.

(4) Roediger, H. L. (1990). Implicit memory: Retention without remembering. American Psychologist, 45, 1043-1056.

(5) Tulving, E. (2002). Episodic memory: From mind to brain. Annual Review of Psychology, 53, 1-25.

(6) Mitchell, M. (1993). Situational Interest: Its multifaceted structure in the secondary school mathematics classroom. Journal of Educational Psychology, 85, 424–436.

(7) Blumenfeld, P. C., Soloway, E., Marx, R., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating Project-Based Learning: Sustaining the Doing, Supporting the Learning. Educational Psychologist, 26, 369-398.

(8) Heit, E., & Rotello, C. M. (2010). Relations between inductive reasoning and deductive reasoning. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36, 805-812.

(9) Rogers, C. (1969). Freedom to learn: A view of what education might become. Columbus, OH, Charles E. Merrill.

An earlier version of this article appeared at www.rethinking-ed.org/blog

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