Five Principles of Effective Encoding
A summary of scientific findings on how to retain information better.
Recently I thought long and hard about what really makes learning effective.
Having finished both my undergraduate and postgraduate study, I have more room to deeply reflect on my learning journey. Not saying that before I didn’t reflect. But when I was doing my degrees, reflections served to adapt my learning strategies to beating tests and getting good grades.
As my learning journey enters a new phase of less structure and more flexibility, I care less about chasing after the outcomes, and more about how I could learn to truly benefit myself.
One of the topics I deeply care about is how to make information sticks.
Sometimes it seems to me that, regardless of the amount of time and effort I put into studying, information goes in and out of my brain just like water goes in and out of a leaked bucket.
Now, as any desperate person would do, I watch a bunch of YouTube videos, listen to podcasts, and read different materials - both light reading and hard-core scientific papers - that discuss learning and memory.
What I found is that, what is often forgotten or not thoroughly discussed about popular learning techniques on mainstream media is the important overarching principles on which these techniques operate. I, too, did not know about these principles, until I dig into the literature of cognitive psychology and learning science (and a bit of Dr. Andrew Huberman’s podcast).
Before sharing with you what I have learned about learning, I would like to provide a quick (yet by-no-mean-exhaustive) explanation of how learning as a process occurs on a cognitive level. I hope doing so would give you (or re-introduce, in case you have come across this knowledge) some basic understanding before you proceed to the rest of the essay.
Two building blocks of learning
A widely used model in cognitive psychology to account for the process of learning is the standard model of memory (1). In this model, learning is conceptualized as a dual process of registering information in the long-term memory and retrieving that registered information.
Basically, what can be considered as true learning is facilitated by the two following actions:
Encoding: aka getting things in your long-term memory and making them stay (or in my case, BEGGING them to stay). The effectiveness of encoding depends on the volume and difficulty of learning contents, a myriad of internal and external factors influencing your learning, and essentially your own encoding skills. There are two common types of encoding: semantic, or deep encoding, and non-semantic, or shallow encoding (2).
Retrieval: aka taking things out and polish them once in a while. How often you polish your knowledge will depend on how well you encode information.
In this essay, let’s discuss encoding first, because if it is done well enough, the follow-up retrieval will be much less work for you to do.
Principles of effective encoding
As I mentioned above, there are important principles underlying effective learning. By understanding these principles, I firmly believe that anyone can leverage them to learn things faster and better, irrespective of the chosen method:
Reflective: Introspect what is known and relate with what will be learned
Elaborative: Add details to the target information
Associative: Connect the dots
Selective: Inhibit irrelevant knowledge
Combine cognitive, motor, and verbal skills for more effortful and deeper information processing
Reflective encoding
To retain and develop a deeper understanding of learning contents, it is important for learners to reflect on their prior experience and relate that to new information (3, 4). Additionally, learners can also practice reflection immediately or a short while after learning, in order to actively think about what they just learned.
According to Fleck & Fitzpatrick (2010, 5), three types of reflection that bring the most benefits to learners are:
Dialogic reflection: reflect on different points of views and relationships between pieces of information;
Transformative reflection: challenge existing assumptions and beliefs;
Critical reflection: go beyond the immediate learning situation, and look at knowledge within broader socio-historical, politico-cultural, moral and ethical contexts.
By engaging in reflection, learners have the opportunity to critically look back on previously acquired knowledge, make new updates by connecting the past and present, and gain revelation based on that past-present connection (6).
Elaborative encoding
Over time, the amount and complexity of knowledge increases, and learning naturally gets harder. Imagine within a single subject, there are hundreds of concepts that you need to learn. How do you make sure each of them is distinct and memorable enough for you to remember?
One way is to elaborate on those concepts.
To effectively handle a large, complex amount of knowledge, it is recommended that learners should elaborate as many details about a particular learning target as possible. The elaborated details then function as “traces” or “cues” that allow the brain to distinguish different pieces of information and remember them better (1, 7, 8, 9, 10, 11).
Elaboration could be done by:
asking questions;
note down personal thoughts, opinions, evaluations;
discussing and debating the information presented in those materials with other people.
Elaborative encoding is thus opposite to merely repeating what’s being learned.
To engage in elaboration is like to put on tags on different books: You have millions of books in your knowledge library, and it might be easier to find the book you need by tagging or using some sort of labeling system.
Associative encoding
Learning is more effective when learners integrate units of information into broader, interrelated conceptual systems (12).
Similarly, when encoding information, try to find associations between pieces of information. Look for patterns among what you learn and tie them together. Connect the dots. Weave them into a larger network of knowledge.
Encoding techniques that often leverage this principle of association include concept mapping and mind mapping.
Concept mapping in particular has been proven to benefit learners across disciplines more than other commonly used methods, such as reading texts, listening to lectures, writing summaries (all of which by the way are either passive consumption or repetition of information) (12).
By engaging in concept mapping, learners not only leverage the principle of association (by identifying relationships between concepts and link them together), but also reflection (by integrating previously learned concepts into the map), elaboration (simply by extending the map as much as possible), and the fifth principle of combining mental and motor skills when encoding (which will be introduced later).
Selective encoding
Interestingly, while learning, your brain can “conjure up” irrelevant, distracting knowledge (14).
One way to inhibit the so-called “distractor” knowledge is by setting out what target information you expect to attain, before going into learning (15).
For example, I sometimes create checklists and note down specifically what information I look for in a learning session. I find this particularly helpful when doing reading assignments. Since many of the readings are long and full of complex ideas, having an anchor point allows me to pull myself back and remind me of exactly what I want to get out of the readings.
It is also equally important to activate only concepts that are relevant to the ones being learned, and avoid wandering too far from the initial learning subject. When I first studied psychology, I constantly reminded myself of the traumas I had in the past, which not only didn’t help me understand the learning materials any better but also distracted me from more important things I need to remember.
Basically, to encode the right information, you should inhibit extraneous ones.
Encoding that combines cognitive, motor, and verbal skills
Learning becomes more effective when learners leverage different skills to retain information, including:
Mental and perceptual encoding: for example – mapping out information in your mind, visualizing and immersing yourself in deep imagery related to what you have learned;
Motor encoding: for example – taking notes, drawing things out, making diagrams, maps or flowcharts to connect concepts;
Verbal encoding: for example – generating and articulating aloud your understanding of the materials, engaging in verbal discussions or debates with other learners.
By combining mental, motor, and verbal forms of encoding, the learning process becomes more complex, effortful and allows for deeper processing of information, as opposed to being easy and shallow (9, 10, 11, 16, 17).
Here, allow me to be cliche for a moment and quote Theodore Roosevelt:
“Nothing in the world is worth having or worth doing unless it means effort, pain, difficulty.”
The same applies to encoding knowledge.
Final thoughts
To summarize, effective encoding is not about WHAT technique to use. But rather it’s about having an understanding of WHY that technique works in the first place, so you leverage that understanding in every learning situation.
I must, however, emphasize with a cautionary note that there is no one-size-fits-all solution to encoding, as well as to learning in general. Learning is supposed to vary across individuals and settings, which I believe is also something not mentioned often enough.
What I intend to suggest is that effective learning begins with recognizing the ingredients that make it work, and that there is more than one way to learn. Effective learning, I believe, begins with opening yourself up to different possibilities of how you can learn things.
Learning becomes ineffective when you think that there is no better way to learn than your current way of doing it.
References
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Demb, J., Desmond, J., Wagner, A., Vaidya, C., Glover, G., & Gabrieli, J. (1995). Semantic encoding and retrieval in the left inferior prefrontal cortex: a functional MRI study of task difficulty and process specificity. The Journal of Neuroscience, 15(9), 5870–5878. https://doi.org/10.1523/jneurosci.15-09-05870.1995
Witherby, A. E., & Carpenter, S. K. (2021). The rich-get-richer effect: Prior Knowledge predicts new learning of domain-relevant information. Journal of Experimental Psychology: Learning, Memory, and Cognition, 48(4), 483-498. https://doi.org/10.1037/xlm0000996
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1. Great writing and illustration!!! I learned a lot!
2. What's the difference between reflection and self-elaborated knowledge? I didn't quite get that distinction yet.
3. When we encode selectively, do we face the risk of confirmation bias?
p/s: so when is your Learn How to Learn cohort starting? :))