Long-Term Memory: How Knowledge Sticks in Teaching

When a learner walks into your classroom in September, they bring everything they have ever learned. That prior knowledge, stored in long-term memory, is the raw material your teaching builds on. Understanding how long-term memory works, and how to strengthen it, is one of the most useful things a teacher can know.

Long-term memory is the mental system that stores, organises, and retrieves information over long periods. It includes explicit knowledge, such as facts and events. It also includes implicit knowledge, such as skills, habits, and learned emotional responses.

For a practical overview of how these ideas apply in lessons, see our guide to working memory in the classroom.

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Long-Term Memory in Learning

Long-term memory is the brain's permanent storage system. Working memory can only hold a few items for a short time. Use it as a starting point for professional discussion: identify the learner's current need, record evidence from more than one lesson, and agree the next classroom adjustment with the SENCO or family.

Long-term memory has no known limit on how much it can store, or for how long. For example, a Year 10 learner who learnt the water cycle in Year 5 can still recall it years later, if it was learnt well and reviewed regularly.

Squire (1992) split long-term memory into two types. Declarative memory means conscious knowledge of facts and events. Non-declarative memory covers skills and habits.

Tulving (1972) stated that declarative memory includes semantic memory. It also includes episodic memory, which means personal events. Semantic memory is especially important for classroom learning.

For teachers, the practical significance is this: what learners know now shapes what they can learn next. A learner with a rich store of prior knowledge in science can connect new material to existing concepts, encode it faster, and retain it longer. A learner with thin prior knowledge faces a much steeper climb. Building long-term memory is not a luxury; it is the central task of teaching.

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Types of Long-Term Memory: A Classroom Overview

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How Memories Move from Short-Term to Long-Term Storage

Bjork (1994) showed that spaced repetition helps learners encode, or take in, information. Baddeley (2000) said the episodic buffer links new memories with old ones. Anderson (1983) found that this short-term area also helps store information.

Synaptic consolidation happens quickly after learning (Dudai, 2004). Systems consolidation is slower and moves memories to the cortex over time (Squire & Wixted, 2011). This is why learners need to revisit topics more than once. Repeated revisits help knowledge last (Murre & Dros, 2015).

Teachers can support long-term learning with proven techniques. Spaced repetition, effortful retrieval, and links between ideas work well (Ebbinghaus, 1885; Karpicke, 2008). "Do Now" activities help because learners recall ideas from previous lessons. This active recall helps consolidate their understanding.

Elaborative encoding boosts memory by making learners think about meaning. Learners build stronger memories when they explain ideas (Craik & Lockhart, 1972). Linking new information to prior knowledge also helps (Bartlett, 1932).

For example, asking learners to explain natural selection, such as cheetah speed, aids recall (Anderson, 1983). This method helps memories last.

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Schema Theory and Knowledge Organisation

Cognitive psychologists use the term 'schema' to describe the mental frameworks through which we organise knowledge. Bartlett's important 1932 studies showed that people don't store memories like photographs. Instead, they rebuild them using existing schemas and fill gaps with what they expect. A learner with rich knowledge about World War II will absorb a new lesson about the Blitz more easily than someone with no background knowledge.

Schemas link related knowledge into a mental network. New facts connect to schemas and join that network (Anderson, 1977).

Isolated facts are easily forgotten. Vocabulary instruction matters because it builds concept scaffolding, which gives learners a structure for ideas (Bransford et al, 2000). This helps learners connect and retain new knowledge (Bartlett, 1932).

The link with cognitive load theory is direct. Expert teachers do not see a lesson as many separate facts. Their well-developed schemas help them treat large chunks of information as single units, which leaves mental space for new material.

Learners are still building those schemas, so each new part needs separate thought and adds to working memory load. Good teaching builds schemas step by step by linking new ideas to what learners already know. This works with the structure of memory, not against it. Reading more about schemas in education gives a fuller picture of how this works in practice.

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Encoding Strategies That Build Durable Memory

Weinstein, Sumeracki, and Caviglioli (2018) showed some study methods help learners more. Re-reading and highlighting don't encode memories well. Active recall makes stronger memories that last (Brown, Roediger, and McDaniel, 2014).

Retrieval practice is the best-evidenced strategy for long-term retention. Roediger and Butler (2011) showed that testing leads to better long-term retention than restudying the same material, even when the tests are low-stakes. In class, this means asking learners to write down everything they remember about a topic before you revisit it.

You can use short quizzes at the start of lessons. You can also ask learners to answer questions without looking at their notes. The act of retrieval strengthens the memory trace. Full guidance on implementing this is available in the guide to retrieval practice for teachers.

Spaced practice spreads learning over time, not just one session. Learners remember topics better when taught in stages (Cepeda et al., 2008). Reviewing material aids retention more than intensive cramming (Rohrer, 2009). Teachers can easily integrate the spacing effect (Ebbinghaus, 1885) using quick recall tasks.

Elaborative interrogation asks learners to explain why facts are true. For example, they might explain how coastal erosion forms headlands and bays. They also explain why hard rock resists erosion, which helps build stronger memory. This kind of understanding helps learners remember because it makes connections (Craik & Lockhart, 1972; Anderson, 1983).

Dual coding links words and images to support learning. Paivio (Paivio, 1986)'s research shows that this improves memory.

A French Revolution timeline uses dates and pictures. Water cycle diagrams pair labels and visuals. Use dual coding resources in the classroom, grounded in Paivio's work on imagery and verbal processes (Paivio, 1971).

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Why Learners Forget (and What You Can Do About It)

Ebbinghaus (1885) mapped what he called the 'forgetting curve': a steep decline in retention that begins within hours of learning and flattens out over time. His data, collected through self-experimentation with nonsense syllables, showed that roughly half of new material is forgotten within a day without review. By the end of a week, much of what remains has degraded further.

Anderson (2000) showed that interference can make learners forget similar information. Ebbinghaus (1885) found that unused memories fade over time. Tulving (1974) explained that learners can sometimes fail to retrieve knowledge they have stored. Godden and Baddeley (1975) showed that mismatched revision and exam cues can hinder learners.

Use these research methods to help learners. Rohrer (2012) suggests interleaving topics, rather than blocking them. Cepeda et al. (2008) show spaced retrieval improves memory. Carvalho & Goldstone (2014) found varied practice builds flexible memory.

Metacognition helps learners succeed by thinking about their own learning. When learners know why they forget, they can see gaps in knowledge (Dunlosky & Metcalfe, 2009).

Learners can then pick stronger study skills. Show Ebbinghaus' (1885) forgetting curve to build learner awareness. Explain that retrieval beats rereading, even though rereading feels good (Karpicke & Roediger, 2008).

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Automaticity: When Knowledge Becomes Effortless

Logan (1988) found automaticity means learners use skills without much thought. Fluent readers recognise words quickly, aiding understanding. LaBerge and Samuels (1974) & Schneider and Shiffrin (1977) noted times tables knowledge lets learners problem-solve better.

Sweller (1988) found that learning stops when working memory is overloaded. Learners need basic facts to become automatic before they tackle algebra. If arithmetic is not automatic, it takes up the capacity they need for harder thinking. Higher-order thought depends on knowledge stored in memory.

Spaced practice builds automaticity, so drill times tables and vocab. This helps learners, according to research (Anderson, 1983). It frees up brain power for complex thought. Teachers build cognitive pathways, as suggested by Sweller (1988).

Automaticity means learners can recall ideas with little effort. This lowers cognitive load when they use knowledge in new situations (Rosenshine (Rosenshine, 2012), 2012).

Because key ideas come to mind quickly, learners can focus on what is unfamiliar. Rosenshine's principles call for guided practice until learners become fluent. Teachers should secure existing knowledge before teaching new material, or new learning can be weakened (Rosenshine, 2012).

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Connecting New Learning to Existing Schemas

The most efficient way to build durable memory is to attach new knowledge to what learners already know. Ausubel (1968) made this principle that still holds today: "If I had to reduce all of educational psychology to just one principle, I would say this: the most important single factor affecting learning is what the learner already knows." Prior knowledge is not just background. It is the scaffolding on which new learning is built.

Researchers such as Bartlett (1932) showed recalling old knowledge helps learning. Before plate tectonics, ask learners about earthquakes or volcanoes. Before poetry, check knowledge of metaphor and rhythm. Anderson and Pichert (1978) showed these memory tasks link to new content.

Using analogies is powerful for this reason. When a chemistry teacher compares electron shells to theatre seats (front row fills first), they link existing knowledge to new ideas. A learner with no comparison for an abstract concept must store it alone.

The learner with the theatre comparison has somewhere to connect it. Scaffolding in teaching works on this principle: give learners the structure that links familiar ideas to unfamiliar ones. Then gradually remove support as the new understanding grows.

Learners with wrong ideas may struggle to learn new things. If learners think heavier objects fall faster, correct them directly and ask them to compare the misconception with evidence or a worked example. Facts alone are rarely enough: challenge the reasoning, surface the conflict and help learners rebuild their understanding. Direct instruction helps bust misconceptions when it is precise and followed by practice.

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Classroom Strategies for Long-Term Retention

Cognitive science research informs these classroom strategies. They do not need fancy resources, and they fit existing lessons. Use it as a starting point for professional discussion: identify the learner's current need, record evidence from more than one lesson, and agree the next classroom adjustment with the SENCO or family.

Brown et al. (2014) and Weinstein et al. (2018) showed their value. Willingham (2009) and Soderstrom & Bjork (2015) echo this. These researchers make simple, effective teaching easier.

Spaced starters. Begin each lesson with a short retrieval activity. It should cover material from one week ago, one month ago, and one term ago. A five-minute 'Do Now' asks learners to answer three to five questions from memory, without notes.

This activates prior knowledge, shows gaps, and strengthens memories of older material. Keep a record of the topics you have revisited. This makes sure spacing is spread out, rather than grouped around topics you find easiest to re-test.

Interleaved practice sets. When setting practice tasks, mix topics instead of keeping each topic in one block. A maths teacher can set ten questions covering algebra, fractions, and geometry. This is different from setting ten algebra questions followed by ten fractions questions.

In the short term, learners find this harder and may feel less confident. In the long term, it leads to much stronger retention and better transfer. Explain this to learners so they understand why the practice feels difficult.

The brain dump. At any point in a lesson, ask learners to close their notes and write down everything they can remember about the topic. This is freeform retrieval, with no structure, no prompts, and only recall. After two minutes, learners compare their lists with a partner and add anything they missed.

This mix of individual recall and peer comparison strengthens memory and reveals misconceptions. It also gives you quick feedback about what learners have and have not remembered. A deeper look at memorisation techniques shows how this fits into a wider toolkit.

Concept maps show how learners link ideas in a visual way. Gaps in a map show missing links, while incorrect links show errors (Novak & Cañas, 2006).

Mapping also strengthens learning (Jonassen et al., 1997). Use it for quick formative assessment because it shows understanding, not just copying (Wandersee, 1990).

Cumulative review works well. Assessments should test knowledge from the whole year, not just recent topics.

This helps learners remember everything (Rohrer, 2006). Learners need to keep knowledge accessible for later use, such as in exams (Brown et al., 2014). It is challenging but useful.

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Limitations and Critiques

Long-term memory research gives teachers useful principles, but it should not be treated as a complete theory of classroom learning. One criticism is ecological validity. Much early memory work, including Ebbinghaus's studies of nonsense syllables, used tightly controlled tasks that differ from noisy classrooms, rich texts, group talk, and mixed prior knowledge. The EEF review of cognitive science approaches in the classroom also warned that promising lab effects do not always transfer cleanly into school practice (Firth et al., 2021).

A second concern is circularity in some accounts of depth of processing. Craik and Lockhart's framework helped move attention beyond simple rehearsal, but critics argued that “deep” processing can be defined by the very memory performance it is meant to explain (Craik & Lockhart, 1972). Later work on transfer-appropriate processing suggests that memory depends not only on depth, but on whether practice matches the later use of knowledge (Morris, Bransford, & Franks, 1977).

There are also cultural limits. Schema theory can make prior knowledge sound neutral, yet learners do not arrive with equal access to the same vocabulary, texts, experiences, or cultural references. Working-class learners and EAL learners may be misread as having weak memory when the real issue is unfamiliar context.

Finally, retrieval practice can be narrowed into quiz culture. Bjork and Bjork (1992) showed the value of desirable difficulties, but poorly designed recall tasks can produce brittle knowledge. Even so, long-term memory remains central to teaching because learners need stored, connected knowledge to reason, read, solve problems, and judge new information.

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References

Brown, A. (1987). Metacognition, executive control, self-regulation, and other more mysterious mechanisms.

Karpicke, J. (2008). The critical importance of retrieval for learning.

Paivio, A. (1986). Mental representations: A dual coding approach.

Rosenshine, B. (2012). Principles of instruction.

Sweller, J. (1988). Cognitive load during problem solving.

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Further Reading: Key Papers on Memory and Learning