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December 29, 2025
Discover how encoding strategies transform fleeting classroom experiences into lasting memories, with practical techniques teachers can use to help students process information more deeply.
Why do students forget so much of what we teach them? Often, the problem begins before forgetting even happens. Information that isn't encoded effectively in the first place has little chance of surviving in long-term memory, regardless of how many times students review it.
Encoding is the process of transforming experiences into memory traces. It's the gateway to learning: without effective encoding, there's nothing to retrieve later. Yet much classroom practice focuses on exposure to information rather than active processing of it. Students read, listen, and highlight, but these passive activities often produce weak encoding that leads to rapid forgetting. Without techniques like spaced practice, even well-encoded information may not transfer effectively to long-term memory.
The good news is that decades of cognitive science research have identified evidence-based memory strategies that reliably produce stronger, more durable memories. These aren't mysterious techniques; they're practical approaches that teachers can embed into everyday instruction, often supporting self-regulated learning in the process.
Encoding refers to the initial processing of information that creates a memory trace. When you pay attention to something, your brain converts that experience into neural patterns that can be stored and later retrieved. The nature of this processing determines how well the information will be remembered.
Think of encoding as translation. Your experiences exist in the external world; encoding translates them into the internal language of your neural networks. Poor translation produces garbled messages that are hard to understand later. Good translation produces clear representations that remain accessible over time.
Research on working memory limitations helps explain encoding constraints. Working memory can hold only a limited amount of information at once, so encoding must be selective. What receives attention gets encoded; what doesn't is lost before it reaches long-term storage. This highlights the importance of metacognitive awareness in helping students direct their attention effectively.
In 1972, Fergus Craik and Robert Lockhart proposed the levels of processing framework, which remains influential for understanding encoding.
Shallow processing focuses on surface features of information: what it looks like, what it sounds like. Reading words without thinking about their meaning constitutes shallow processing. So does noting that a fact appeared on page 47 without engaging with what the fact means.
Shallow processing produces weak, easily forgotten memories. It's fast and requires little effort, which is why students often default to it. But the speed comes at a cost to retention.
Deep processing engages with meaning and connections. When you think about what something means, how it relates to what you already know, or why it matters, you're processing deeply. This semantic processing creates richer, more elaborate memory traces.
Deep processing takes more effort than shallow processing, but the investment pays off in better retention. Students who spend five minutes processing deeply often remember more than students who spend twenty minutes processing shallowly.
Much traditional instruction inadvertently encourages shallow processing. Copying notes from a board, reading passages without discussion, and reviewing flashcards without explaining relationships all constitute shallow processing.
Teachers can shift toward deep processing by asking students to explain meaning, generate connections, and apply information to new situations. Any activity that requires thinking about what something means, rather than just what it looks like, promotes deep encoding.
Research has identified several encoding strategies that reliably produce strong memories. These strategies can be taught explicitly and embedded into classroom routines.
Elaboration involves adding meaning and connections to new information. Rather than storing isolated facts, elaboration links new learning to existing knowledge, creating multiple retrieval pathways.
Elaboration takes many forms:
Elaborative interrogation is a specific technique that prompts students to explain why facts are true. When students generate explanations, they create elaborated memory traces that persist longer than unelaborated information.
In the classroom, build elaboration into instruction by regularly pausing to ask: "Why is this the case?" "How does this connect to what we learned last week?" "Can you think of an example from your own experience?"
Organisation involves imposing structure on information. Organised information is easier to encode and retrieve than scattered, disorganised content.
Effective organisation strategies include:
Organisation works partly by chunking information. Rather than encoding many separate items, learners encode a smaller number of organised chunks. Each chunk serves as a retrieval cue for its contents.
Teachers can support organisational encoding by making structure explicit. Don't just present information; show how it's organised. Use consistent structures across lessons so students can fit new information into familiar frameworks.
Visualisation creates mental images of information. Visual memories are distinct from verbal memories, and encoding information in both forms produces stronger retention than either alone.
Dual coding theory, developed by Allan Paivio, explains this advantage. Information encoded both verbally and visually benefits from two independent memory traces. If one trace fades, the other may remain accessible.
Visualisation strategies include:
Encourage students to create mental pictures as they learn. Ask: "Can you picture this?" "What would this look like?" "Draw what you're imagining."
Information connected to ourselves is encoded more strongly than impersonal information. This self-reference effect provides a powerful encoding strategy.
When students relate new learning to their own experiences, opinions, or goals, they process it more deeply and remember it better. The personal connection creates elaboration and emotional engagement that strengthen encoding.
Classroom applications include:
This explains why personalised examples often produce better learning than generic ones. Asking "How does this apply to your life?" produces stronger encoding than presenting the same information in decontextualised form.
Distinctive information stands out in memory. When encoding produces a unique, differentiated representation, retrieval becomes easier because the memory is less likely to be confused with similar information.
Strategies promoting distinctiveness:
When teaching similar concepts, emphasise what distinguishes them. This distinctive encoding reduces confusion and interference at retrieval.
Encoding requires attention. Information that doesn't receive attention cannot be encoded, no matter how long it's presented. This makes attention the gateway to all learning.
Classrooms present multiple stimuli competing for attention. Students must selectively attend to relevant information while ignoring distractions. Teachers can support selective attention by clearly signalling what's important and reducing competing stimuli.
Learning requires maintaining attention over time. Attention naturally fluctuates, with most students showing declining focus after 10-20 minutes. Varying instructional activities, building in movement, and strategic timing of key content helps maintain attention throughout lessons.
When attention is divided between multiple demanding tasks, encoding of each task suffers. Students who check their phones during instruction encode less than those who focus completely. Similarly, overly complex instruction that demands attention to multiple elements simultaneously can overwhelm attention capacity.
Research on cognitive load theory addresses how instructional design affects attention and encoding. Managing cognitive load ensures sufficient attention remains available for encoding target content.
Working memory is the cognitive system that holds and manipulates information during encoding. It serves as the workspace where new information is processed before entering long-term memory.
Working memory has severe capacity limitations. Most people can hold only 3-5 chunks of information simultaneously. When encoding demands exceed working memory capacity, some information is lost.
Teachers can support encoding by breaking content into manageable chunks. Present a few ideas at a time, allow processing before moving on, and don't overload working memory with unnecessary complexity.
Deep processing requires working memory resources. If working memory is overwhelmed by too much information, students default to shallow processing because they lack the capacity for deeper engagement.
Reduce extraneous cognitive load to free resources for encoding. Eliminate unnecessary complexity, ensure materials are well-designed, and provide scaffolds that reduce working memory burden.
Students with relevant prior knowledge can encode new information more efficiently because they can chunk it into existing schemas. This is why activating prior knowledge at the start of lessons supports encoding: it prepares mental structures to receive new information.
Encoding and retrieval are intimately connected. The conditions at encoding shape what retrieval cues will be effective later. This principle, called encoding specificity, has important implications for learning.
Information is encoded along with context: where you learned it, what you were thinking, what was happening around you. These contextual elements become linked to the memory and can serve as retrieval cues.
This explains why students sometimes perform better in the room where they learned material, or why returning to a topic can trigger recall of related information. The context provides cues that access the encoded memory.
Retrieval is most successful when it matches the type of processing used during encoding. If you encoded information by thinking about its meaning, tests that require meaning-based retrieval will succeed. If you encoded by rote repetition, meaning-based questions may fail even though the information is stored.
This principle suggests that encoding should match anticipated retrieval. If students will need to apply concepts to novel problems, they should practise application during encoding. If they will need to recall factual details, they should encode those details specifically.
Effective encoding strategies vary somewhat across subject areas, reflecting different knowledge structures and learning goals.
Science encoding benefits from:
Visual encoding is particularly important in science, where processes, structures, and relationships benefit from diagrammatic representation.
Mathematical encoding benefits from:
Mathematics requires encoding both procedures and the concepts that underpin them. Encoding procedures without understanding leads to fragile, inflexible knowledge.
Historical encoding benefits from:
Historical understanding requires encoding events within causal narratives, not as isolated facts.
Language encoding benefits from:
Vocabulary instruction is most effective when words are encoded through meaningful use rather than isolated memorisation.
Helping students understand encoding supports metacognition and independent learning. Students who understand how memory works can adopt more effective study strategies.
Students often rely on shallow processing (re-reading, highlighting) because it feels productive. Teaching the distinction between shallow and deep processing helps students understand why these strategies often fail.
Demonstrate encoding strategies explicitly. Show students how to elaborate, organise, and visualise. Think aloud while encoding to make these processes visible.
Give students structured opportunities to practise encoding strategies with feedback. Initially scaffold the strategies, then gradually release responsibility as students develop competence.
Use prompts that encourage students to monitor their encoding:
Embedding encoding strategies in classroom routines ensures consistent application.
Begin lessons by activating prior knowledge relevant to new content. This prepares schemas for encoding and creates connection points for new information.
Pause regularly to prompt encoding. After presenting key concepts, ask students to explain, visualise, connect, or apply. These encoding activities take minimal time but substantially improve retention.
End lessons with activities that consolidate encoding. Summarisation, connection-making, and retrieval practice all strengthen the memories formed during the lesson.
Encoding is necessary but not sufficient for lasting learning. Strong encoding provides the foundation, but consolidation and retrieval practice are also required for durable retention.
A complete approach to memory combines:
Teachers who address all three processes maximise their impact on long-term learning.
Begin improving encoding in your classroom with these manageable changes.
Ask "why" and "how" questions that require explanation rather than recognition. Every lesson should include moments where students must explain concepts in their own words.
Use graphic organisers to support organisational encoding. Maps, webs, and hierarchies help students see and encode structure.
Connect to prior knowledge explicitly at lesson beginnings. Activating relevant schemas prepares the cognitive context for new encoding.
Reduce cognitive load by chunking information and eliminating unnecessary complexity. What remains should receive full processing attention.
Build encoding pauses into instruction. After presenting key content, stop and prompt encoding activity before moving on.
These strategies don't require additional time. They redirect existing instructional time toward activities that produce genuine learning rather than the illusion of understanding.
The following papers provide deeper exploration of encoding and its educational applications.
This foundational paper introduced the levels of processing framework that transformed memory research. The authors argued that memory depends on depth of processing during encoding, with semantic processing producing superior retention. The paper launched extensive research on how encoding strategies affect learning.
This research established elaborative interrogation as an effective encoding strategy. The authors found that prompting students to explain why facts are true substantially improved memory for those facts. The technique works by generating elaborated connections between new and existing knowledge.
This comprehensive review evaluated ten learning techniques including several encoding strategies. Elaborative interrogation and self-explanation received positive ratings, while commonly used strategies like highlighting and re-reading were rated as less effective.
Allan Paivio explains dual coding theory and its educational implications. The paper describes how combining verbal and visual encoding produces stronger memories than either alone, supporting the use of diagrams, imagery, and multimedia in instruction.
While focused on retrieval, this paper demonstrates how encoding and retrieval interact. The research shows that retrieval practice produces better retention than elaborative studying, highlighting the importance of active processing over passive review.
Why do students forget so much of what we teach them? Often, the problem begins before forgetting even happens. Information that isn't encoded effectively in the first place has little chance of surviving in long-term memory, regardless of how many times students review it.
Encoding is the process of transforming experiences into memory traces. It's the gateway to learning: without effective encoding, there's nothing to retrieve later. Yet much classroom practice focuses on exposure to information rather than active processing of it. Students read, listen, and highlight, but these passive activities often produce weak encoding that leads to rapid forgetting. Without techniques like spaced practice, even well-encoded information may not transfer effectively to long-term memory.
The good news is that decades of cognitive science research have identified evidence-based memory strategies that reliably produce stronger, more durable memories. These aren't mysterious techniques; they're practical approaches that teachers can embed into everyday instruction, often supporting self-regulated learning in the process.
Encoding refers to the initial processing of information that creates a memory trace. When you pay attention to something, your brain converts that experience into neural patterns that can be stored and later retrieved. The nature of this processing determines how well the information will be remembered.
Think of encoding as translation. Your experiences exist in the external world; encoding translates them into the internal language of your neural networks. Poor translation produces garbled messages that are hard to understand later. Good translation produces clear representations that remain accessible over time.
Research on working memory limitations helps explain encoding constraints. Working memory can hold only a limited amount of information at once, so encoding must be selective. What receives attention gets encoded; what doesn't is lost before it reaches long-term storage. This highlights the importance of metacognitive awareness in helping students direct their attention effectively.
In 1972, Fergus Craik and Robert Lockhart proposed the levels of processing framework, which remains influential for understanding encoding.
Shallow processing focuses on surface features of information: what it looks like, what it sounds like. Reading words without thinking about their meaning constitutes shallow processing. So does noting that a fact appeared on page 47 without engaging with what the fact means.
Shallow processing produces weak, easily forgotten memories. It's fast and requires little effort, which is why students often default to it. But the speed comes at a cost to retention.
Deep processing engages with meaning and connections. When you think about what something means, how it relates to what you already know, or why it matters, you're processing deeply. This semantic processing creates richer, more elaborate memory traces.
Deep processing takes more effort than shallow processing, but the investment pays off in better retention. Students who spend five minutes processing deeply often remember more than students who spend twenty minutes processing shallowly.
Much traditional instruction inadvertently encourages shallow processing. Copying notes from a board, reading passages without discussion, and reviewing flashcards without explaining relationships all constitute shallow processing.
Teachers can shift toward deep processing by asking students to explain meaning, generate connections, and apply information to new situations. Any activity that requires thinking about what something means, rather than just what it looks like, promotes deep encoding.
Research has identified several encoding strategies that reliably produce strong memories. These strategies can be taught explicitly and embedded into classroom routines.
Elaboration involves adding meaning and connections to new information. Rather than storing isolated facts, elaboration links new learning to existing knowledge, creating multiple retrieval pathways.
Elaboration takes many forms:
Elaborative interrogation is a specific technique that prompts students to explain why facts are true. When students generate explanations, they create elaborated memory traces that persist longer than unelaborated information.
In the classroom, build elaboration into instruction by regularly pausing to ask: "Why is this the case?" "How does this connect to what we learned last week?" "Can you think of an example from your own experience?"
Organisation involves imposing structure on information. Organised information is easier to encode and retrieve than scattered, disorganised content.
Effective organisation strategies include:
Organisation works partly by chunking information. Rather than encoding many separate items, learners encode a smaller number of organised chunks. Each chunk serves as a retrieval cue for its contents.
Teachers can support organisational encoding by making structure explicit. Don't just present information; show how it's organised. Use consistent structures across lessons so students can fit new information into familiar frameworks.
Visualisation creates mental images of information. Visual memories are distinct from verbal memories, and encoding information in both forms produces stronger retention than either alone.
Dual coding theory, developed by Allan Paivio, explains this advantage. Information encoded both verbally and visually benefits from two independent memory traces. If one trace fades, the other may remain accessible.
Visualisation strategies include:
Encourage students to create mental pictures as they learn. Ask: "Can you picture this?" "What would this look like?" "Draw what you're imagining."
Information connected to ourselves is encoded more strongly than impersonal information. This self-reference effect provides a powerful encoding strategy.
When students relate new learning to their own experiences, opinions, or goals, they process it more deeply and remember it better. The personal connection creates elaboration and emotional engagement that strengthen encoding.
Classroom applications include:
This explains why personalised examples often produce better learning than generic ones. Asking "How does this apply to your life?" produces stronger encoding than presenting the same information in decontextualised form.
Distinctive information stands out in memory. When encoding produces a unique, differentiated representation, retrieval becomes easier because the memory is less likely to be confused with similar information.
Strategies promoting distinctiveness:
When teaching similar concepts, emphasise what distinguishes them. This distinctive encoding reduces confusion and interference at retrieval.
Encoding requires attention. Information that doesn't receive attention cannot be encoded, no matter how long it's presented. This makes attention the gateway to all learning.
Classrooms present multiple stimuli competing for attention. Students must selectively attend to relevant information while ignoring distractions. Teachers can support selective attention by clearly signalling what's important and reducing competing stimuli.
Learning requires maintaining attention over time. Attention naturally fluctuates, with most students showing declining focus after 10-20 minutes. Varying instructional activities, building in movement, and strategic timing of key content helps maintain attention throughout lessons.
When attention is divided between multiple demanding tasks, encoding of each task suffers. Students who check their phones during instruction encode less than those who focus completely. Similarly, overly complex instruction that demands attention to multiple elements simultaneously can overwhelm attention capacity.
Research on cognitive load theory addresses how instructional design affects attention and encoding. Managing cognitive load ensures sufficient attention remains available for encoding target content.
Working memory is the cognitive system that holds and manipulates information during encoding. It serves as the workspace where new information is processed before entering long-term memory.
Working memory has severe capacity limitations. Most people can hold only 3-5 chunks of information simultaneously. When encoding demands exceed working memory capacity, some information is lost.
Teachers can support encoding by breaking content into manageable chunks. Present a few ideas at a time, allow processing before moving on, and don't overload working memory with unnecessary complexity.
Deep processing requires working memory resources. If working memory is overwhelmed by too much information, students default to shallow processing because they lack the capacity for deeper engagement.
Reduce extraneous cognitive load to free resources for encoding. Eliminate unnecessary complexity, ensure materials are well-designed, and provide scaffolds that reduce working memory burden.
Students with relevant prior knowledge can encode new information more efficiently because they can chunk it into existing schemas. This is why activating prior knowledge at the start of lessons supports encoding: it prepares mental structures to receive new information.
Encoding and retrieval are intimately connected. The conditions at encoding shape what retrieval cues will be effective later. This principle, called encoding specificity, has important implications for learning.
Information is encoded along with context: where you learned it, what you were thinking, what was happening around you. These contextual elements become linked to the memory and can serve as retrieval cues.
This explains why students sometimes perform better in the room where they learned material, or why returning to a topic can trigger recall of related information. The context provides cues that access the encoded memory.
Retrieval is most successful when it matches the type of processing used during encoding. If you encoded information by thinking about its meaning, tests that require meaning-based retrieval will succeed. If you encoded by rote repetition, meaning-based questions may fail even though the information is stored.
This principle suggests that encoding should match anticipated retrieval. If students will need to apply concepts to novel problems, they should practise application during encoding. If they will need to recall factual details, they should encode those details specifically.
Effective encoding strategies vary somewhat across subject areas, reflecting different knowledge structures and learning goals.
Science encoding benefits from:
Visual encoding is particularly important in science, where processes, structures, and relationships benefit from diagrammatic representation.
Mathematical encoding benefits from:
Mathematics requires encoding both procedures and the concepts that underpin them. Encoding procedures without understanding leads to fragile, inflexible knowledge.
Historical encoding benefits from:
Historical understanding requires encoding events within causal narratives, not as isolated facts.
Language encoding benefits from:
Vocabulary instruction is most effective when words are encoded through meaningful use rather than isolated memorisation.
Helping students understand encoding supports metacognition and independent learning. Students who understand how memory works can adopt more effective study strategies.
Students often rely on shallow processing (re-reading, highlighting) because it feels productive. Teaching the distinction between shallow and deep processing helps students understand why these strategies often fail.
Demonstrate encoding strategies explicitly. Show students how to elaborate, organise, and visualise. Think aloud while encoding to make these processes visible.
Give students structured opportunities to practise encoding strategies with feedback. Initially scaffold the strategies, then gradually release responsibility as students develop competence.
Use prompts that encourage students to monitor their encoding:
Embedding encoding strategies in classroom routines ensures consistent application.
Begin lessons by activating prior knowledge relevant to new content. This prepares schemas for encoding and creates connection points for new information.
Pause regularly to prompt encoding. After presenting key concepts, ask students to explain, visualise, connect, or apply. These encoding activities take minimal time but substantially improve retention.
End lessons with activities that consolidate encoding. Summarisation, connection-making, and retrieval practice all strengthen the memories formed during the lesson.
Encoding is necessary but not sufficient for lasting learning. Strong encoding provides the foundation, but consolidation and retrieval practice are also required for durable retention.
A complete approach to memory combines:
Teachers who address all three processes maximise their impact on long-term learning.
Begin improving encoding in your classroom with these manageable changes.
Ask "why" and "how" questions that require explanation rather than recognition. Every lesson should include moments where students must explain concepts in their own words.
Use graphic organisers to support organisational encoding. Maps, webs, and hierarchies help students see and encode structure.
Connect to prior knowledge explicitly at lesson beginnings. Activating relevant schemas prepares the cognitive context for new encoding.
Reduce cognitive load by chunking information and eliminating unnecessary complexity. What remains should receive full processing attention.
Build encoding pauses into instruction. After presenting key content, stop and prompt encoding activity before moving on.
These strategies don't require additional time. They redirect existing instructional time toward activities that produce genuine learning rather than the illusion of understanding.
The following papers provide deeper exploration of encoding and its educational applications.
This foundational paper introduced the levels of processing framework that transformed memory research. The authors argued that memory depends on depth of processing during encoding, with semantic processing producing superior retention. The paper launched extensive research on how encoding strategies affect learning.
This research established elaborative interrogation as an effective encoding strategy. The authors found that prompting students to explain why facts are true substantially improved memory for those facts. The technique works by generating elaborated connections between new and existing knowledge.
This comprehensive review evaluated ten learning techniques including several encoding strategies. Elaborative interrogation and self-explanation received positive ratings, while commonly used strategies like highlighting and re-reading were rated as less effective.
Allan Paivio explains dual coding theory and its educational implications. The paper describes how combining verbal and visual encoding produces stronger memories than either alone, supporting the use of diagrams, imagery, and multimedia in instruction.
While focused on retrieval, this paper demonstrates how encoding and retrieval interact. The research shows that retrieval practice produces better retention than elaborative studying, highlighting the importance of active processing over passive review.
