Learning in the brain
Introducing Long Term Memory and Working Memory:
o Key features
o How do they interact during learning to build (and use) the memory base.
o Guidelines to aligning teaching and learning strategies with learning stages.
Basic brain function
The function of the brain, in very general terms, is to receive signals from the environment, processes them and respond effectively to support the well-being and survival of the organism. The information about what may be effective in a given situation is retrieved from the Long-Term Memory system that stores information from past scenarios.
How is the information stored in long-term Memory?
It is widely accepted on the basis of scientific findings that information is stored in neuronal patterns. Neurons are the basic functional unit of the brain, they communicate with each other by sending and receiving signals. By activating each other they form pathways and networks of synchronous activity. This is the basic mechanism of how the brain works. The information that we remember is stored in specific patterns of neuronal activity.
The specific patterns are created during learning, stabilized and stored in long-term memory, and potentially, reactivated upon recollection. To illustrate with a simplified model of nodes (neurons) and connectors (synapses): the concept "Tiger" is represented as a group of neurons that are simultaneously active (turquoise rectangle in the figure). This neural activity (representing the tiger) is associated through connections to other neuronal patterns (representing for example “Zoo”, "Predator", "Jungle", “Danger”, etc.) that together encompass what we know about tigers. To execute an effective response, the relevant information should be accessed, combined with stimuli coming from the outside world and manipulated. These actions are performed in a mental space called Working Memory.
Working Memory is where all the mental processing takes place: real-time thinking: combining incoming information with retrieved information from long-term memory, manipulating them to create an output, usually in the form of a decision or action.
The most prominent feature of the working memory system is its limited capacity: it is possible to handle only a small number of items simultaneously. Many are familiar with the 7±2 items limit (i.e. the normal range of items held in working memory is 5 to 9 items), but the capacity may be even lower and closer to just 4 isolated and unfamiliar items. Using this demo you can experience the limited working memory capacity and explore how it decreases when it is required to handle unfamiliar items (undefined shapes) compared with familiar ones (digits).
Working Memory key features:
1. It is where thinking takes place: connecting incoming new information with prior knowledge, and where both are manipulated.
2. It has a limited capacity.
3. Overload leads to information loss – either incoming information will not be processed, or an “in-process” item will be dropped for a new one.
4. Processing in working memory is essential for long-term storage: it is the information’s “entry ticket” to the long term memory storage.
This last point emphasizes a crucial part in the interaction between Working memory and Long-term memory, Daniel Willingham depicted it in the now famous quote:
“Memory is the residue of the thought”1. In other words: Long-term representations of information may be formed only as a consequence of manipulation in working memory.
So processing in working memory is essential for long-term storage, but do we remember everything that is manipulated in working memory?
The answer is obviously NO. So, what else is important to consider?
What kind of processing in working memory supports storage in long-term memory?
if "memory is the residue of the thought", then the 'thought' should process the information in a way that can be "read" by the memory store.
Think of working memory as the reception counter to a big archive. The incoming information must be labeled and stored according to the standard system of organization, otherwise it cannot be stored systematically and it would never be found.
It follows that it would be useful to understand the principle of long-term memory organization in order to process the information in a similar way, so:
How is knowledge organized in the long-term memory store?
According to "Levels of Processing Model of Memory"6, when information is processed deeply and meaningfully, it will be better remembered than if processed on the basis of its shallow characteristics like shape, color or sound. (read more about the model and the classical experiments).
Deep processing involves meaning or semantics: the ability to understand a new concept in terms of already familiar concepts and already familiar connections between them. Hence, deep , content-related, meaningful processing in Working-Memory at the time of learning would allow the new information to be connected to existing piece of knowledge in ways that would allow it to be accessible for future use.
To summarize, working memory resources are highly limited, and yet meaningful processing is essential for storage in long-term memory. It is therefore important to use these resources effectively when teaching. There are many known effective teaching strategies, but a question that often comes up is when to apply each strategy for the best results?
Understanding the the principal characteristics of the the two major memory systems that are involved, their limitations, and importantly the interaction between them, is suggested to support wise decisions regarding the use of strategies.
To do that, we complete the picture by describing a model of knowledge representation in long-term memory. What are the stages of learning any new concept? how it is represented in the brain? and what kind of behavior it may support?
The model include 4 levels: Knowing, Understanding, Using and Mastering.
A model of building long-term memory representations
The first stage of learning any concept is the initial encounter: when a learner first sees or hears a completely new concept (word, object, etc.) that was never encountered before, and is therefore not represented in the brain in any way (left panel). Following the first encounter, the new concept may be represented in the brain (right panel): connections (edges in turquoise) are formed between neurons to create a network. If this happens, the learner may be able to recognize this concept in the near future when it is explicitly presented again. It is possible to say that the learner knows this concept, but since it is a very low level of representation it may allow potential recognition but not much more.
Next, the now recognizable concept is explained, becomes meaningful. Meaning is generated when the new concept (Turquoise) is associated with other concepts (words, objects, procedures, etc.) that the learner is already familiar with (Dark Grey), in a way that makes sense to the learner. The learner now understands the meaning of the new concept. When we understand, we start to have a sense of how the concept may be useful...
Next, it is crucial to practice what was learned to establish accessibility and function. The goal is to build pathways that will enable recalling the concept when needed, ideally over time, changing environment and various retrieval cues. Distributed and varied retrieval practice is the way to achieve that: when trying to recall the information, access pathways are built and maintained. When a network of related concepts is established, the learner is able to USE the stored knowledge.
When using the new concpet is repeated over time, in various contexts and ways, we eventually get to a state of MASTERY: the former learner is able to use it easily and quickly, even automatically. This state of concept representation is described as a “Schema” (very well cnnected and practiced network of concepts).
How much effort does it take?
This four-stage model allows us to complete the working-memory long-term memory interactions picture: the level of representation in long-term memory determines how much mental effort is required to manipulate any "piece of knowledge" in working memory (e.g. when learning something new):
When a learner knows the concept, the only possible manipulation is recognizing it when presented. This is not very demanding (but also not very productive). An example is when we hear or read a new word that was recently learned and we don't know what it means (new vocabulary item, or a absolutely new concept).
When a concept is understood (e.g. when the meaning is attached to the new word), then we can start to manipulate and use it, however to do so we need to continuously hold it in working memory, along with its meaning. This stage is quite demanding in terms of mental effort (cognitive load). For example, when we try to understand a complex sentence or set of instructions that include a new concept that we have just grasped, sometimes the cognitive load forces us to move to sequential processing - decipher the new concept first, then the instructions - if any additional information is supplied in the meantime , we experience cognitive overload!
With effective practice (e.g. practicing the use of a new vocabulary word in sentences) it becomes easier to use the concept in practiced situations, and the load on working memory is reduced. The concept becomes useful.
Once the concept is mastered (e.g. when a word is fully integrated into everyday vocabulary), using it becomes effortless and automatic. It requires fewer working memory resources. In such situation, the available resources can be used for deciphering incoming information, even when it is complex. The overlaod is relieved.
Long-term memory and working memory interactions
It becomes clear how long-term memory and working memory interact when learning. The depth of processing in working memory influences the future potential representations in long-term memory and the levels of representation in long-term memory affects the working-memory capacity to handle additional information. When learners encounter a new concept, they must process it meaningfully in relation to already familiar concepts. However, the level of representation of these familiar concepts determines greatly how much resources are left for deep processing. The more established the knowledge is, the fewer processing resources are required, and the easier it is to process it deeply. Research shows that learning new information based on a well-established schema is quicker and easier 4.
Teaching with learning and memory in mind
The model can help us select the most appropriate teaching (and learning) strategies for each phase, while considering:
A) What is the teaching goal in terms of forming Long-Term Memory (LTM) representations (e.g: to establish understating or to establish retrieval pathways)
B) How limited the Working Memory (WM) resources are, and how WM can be used to attain the goal defined in A?
This illustration attempts to depict the relevant LTM and WM considerations, and lists effective strategies aligned with the stage of learning:
In the initial learning phase focus should be on creating meaningful connections to prior knowledge: explain clearly, discuss 'How' and "Why', give concrete examples. In this stage, just holding the learned information in mind may require most of WM resources, hence attempts to introduce more complex activities, may result in working-memory overload. Applying the concepts from the Cognitive Load Theory5 that emphasize ways to reduce undesirable load would be recommended.
& see Ref #7 bellow
In the Practice phase focus on using the information, building retrieval pathways to make it accessible for future use. In this phase it is recommended to focus on effective practice methods like retrieval practice (trying to answer questions, rather than reviewing answers) and distribute the practice over time, to make it more effortful. The effort is a big part of the reason these strategies are effective, it is also the reason they should be applied following the establishment of the knowledge in the previous stage.
& see Ref #8 bellow
This illustration stands for every level of learning: from simple concepts like words to more complex concepts that comprise any domain of knowledge. So this is actually a learning spiral: the process is repeated for every level, and if done effectively, then this level serve as a solid basis (well interconnected and easily retrieved) for higher-order learning. In this blog by science teacher Damian Benney you can see a practical example of how these ideas come to life in the high-school chemistry classroom, and here is the interpretation of Physics teacher Ben Rogers.
1. Willingham, D. T. (2008). What will improve a student’s memory. American Educator, 32(4), 17-25. [PDF]
2. Craik, F.I.M., & Tulving, E. (1975). Depth of processing and the retention of words in episodic memory. Journal of Experimental Psychology: General, 104, 268-294.
3. Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal behavior, 11, 671-684.
4. Shing, Y. L., & Brod, G. (2016). Effects of prior knowledge on memory: Implications for education. Mind, Brain, and Education, 10(3), 153-161.
5. Cognitive load theory: Research that teachers really need to understand (2017) by the Centre for Education Statistics and Evaluation, State of New South Wales (Department of Education) [PDF]
6. McLeod, S. A. (2007). Levels of processing. Retrieved from www.simplypsychology.org/levelsofprocessing.html
7. Willingham, D. T. (2009). Why don't students like school?: A cognitive scientist answers questions about how the mind works and what it means for the classroom. John Wiley & Sons.
This book is based on research and written especially for teachers, includes clear explanation, compelling examples and demonstrations, and classroom applications. Specifically relevant for the discussion here are the following chapters:
Chapter 1: sub-section "How Thinking Works" for introduction of working memory and long term memory, and their functions.
Chapter 3: “Memory is the Residue if the thought”. on the importance of meaningful processing and ways to do it.
Chapter 5: "It is virtually impossible to become proficient at a mental task without extended practice"
8. Brown, Roediger and McDaniel (2014) “Make it Stick: The Science of successful Learning” Harvard University Press
A very readable and eye-opening book about research-based effective practice strategies. Stories and examples from real lives and real classrooms, guidelines for teachers and for learners.
Applying Efrat Furst’s Model of Building Long-Term Memory Representations by Ben Rogers [Link to blog]
April 2018, updated: Jan2021