Evidence-Based Learning Strategies

15 min read

Evidence-Based Learning Strategies

Study techniques whose effectiveness is confirmed by controlled experiments in cognitive psychology — as opposed to popular strategies that merely feel productive.

What is it?

For decades, students have relied on a familiar toolkit: re-reading notes, highlighting textbooks, and writing summaries. These strategies feel productive because they keep you busy and the material looks familiar afterwards. But a landmark review by Dunlosky et al. (2013), which evaluated ten common study techniques against the experimental literature, rated highlighting, re-reading, and summarisation as having low utility — they produce minimal gains in durable learning compared to the effort they require.1 The problem is not that students are lazy; it is that the strategies they default to exploit the wrong cognitive mechanisms.

In response, cognitive scientists — most notably Yana Weinstein, Megan Sumeracki, and illustrator Oliver Caviglioli, working as The Learning Scientists — synthesised the research into six strategies with the strongest experimental support: retrieval practice, spaced practice (spaced repetition), interleaving, elaboration, concrete examples, and dual coding.2 These are not study tips discovered by trial and error. Each one is grounded in how human memory actually encodes, stores, and retrieves information. Their book Understanding How We Learn: A Visual Guide (2018) and their accompanying website translated this research into accessible, teacher-friendly materials.3

The critical distinction is that these strategies are cognitive mechanisms, not productivity hacks. Re-reading feels effective because it creates a sense of fluency — the text looks familiar, so you assume you know it. Retrieval practice feels harder because you are forcing your brain to reconstruct information from memory rather than simply recognising it on the page. This is the paradox at the heart of desirable-difficulties: the strategies that produce the best long-term learning are often the ones that feel the most effortful and least productive in the moment.4

What unifies all six strategies is a single principle from Robert Bjork’s research: desirable difficulties. Conditions that make initial learning harder — spacing out sessions, mixing topics, testing yourself instead of re-reading — force the brain to work harder during retrieval, which strengthens the memory trace.4 The six strategies are, in effect, six different ways of introducing desirable difficulty into the learning process.

In plain terms

Imagine two people training for a marathon. One runs the same flat route every day and feels great about their pace. The other runs hills, varies the terrain, and adds interval sprints — it hurts more, but come race day, they are far better prepared. Evidence-based learning strategies are the hills and sprints of studying: harder in the moment, dramatically more effective in the long run.

At a glance

How does it work?

1. Retrieval practice — learning by remembering

Retrieval practice means actively pulling information out of memory rather than passively reviewing it. Flashcards, practice tests, free recall (closing the book and writing everything you remember) — all are forms of retrieval practice. The key finding, demonstrated by Roediger and Karpicke (2006), is that the act of retrieving a memory changes that memory, making it stronger and more accessible in the future. Students who studied a passage once and then took three recall tests remembered significantly more after one week than students who studied the passage four times.5

Think of it like...

A path through a forest. Every time you walk the path, it becomes clearer and easier to find. Re-reading is like looking at a map of the path. Retrieval practice is actually walking it — and each walk makes the next one easier.

Concept to explore

See retrieval-practice for the full mechanism, including the testing effect, retrieval-induced forgetting, and how to design effective retrieval practice.

2. Spaced practice — distributing study over time

Spaced practice (also called distributed practice or spaced-repetition) means spreading study sessions across multiple days rather than cramming everything into one long session. The spacing effect — one of the most robust findings in psychology — shows that the same total study time produces dramatically better retention when distributed over time.6 Cepeda et al. (2006) found optimal spacing intervals depend on the retention interval: if you need to remember something for a month, spacing sessions about a week apart is more effective than spacing them a day apart.6

Concept to explore

See spaced-repetition for the spacing effect, optimal intervals, and how spaced repetition systems (SRS) like Anki automate this process.

3. Interleaving — mixing topics during practice

Interleaving means alternating between different types of problems or topics during a study session, rather than practising one type exhaustively before moving to the next (which is called blocking). For example, instead of doing 20 addition problems, then 20 subtraction problems, you mix them: addition, subtraction, addition, subtraction. Interleaving forces the learner to identify which strategy applies to each problem, not just execute a strategy they already know is correct.2

Rohrer and Taylor (2007) demonstrated that interleaved practice produced significantly better test performance than blocked practice, even though students perceived blocked practice as more effective.7 This mismatch between perceived and actual effectiveness is a hallmark of desirable difficulties.

Think of it like...

A chef who practises making only omelettes for a week, then only soups, then only salads. Compare that to a chef who practises all three dishes each day, randomly. The second chef has to recall different recipes and switch techniques constantly — harder in practice, but far more realistic preparation for a real kitchen where orders come in any sequence.

4. Elaboration — explaining why and how

Elaboration means generating explanations for facts rather than simply memorising them. “Why does this make sense?” “How does this connect to something I already know?” “Why is this true rather than something else?” By elaborating, you create additional retrieval routes to the information in memory — more connections mean more ways to find the memory later.2

Weinstein, Madan, and Sumeracki (2018) describe elaborative interrogation as one of the most accessible strategies: students simply ask “why?” after each key fact and attempt to answer the question from their existing knowledge.3

5. Concrete examples — anchoring abstractions

Abstract concepts become much easier to understand and remember when paired with specific, concrete examples. This is not merely a teaching convenience — it reflects a fundamental property of human cognition. We evolved to reason about concrete objects and events; abstract reasoning is a later, harder cognitive operation.3

The key practice is to generate your own examples, not just read ones provided by the textbook. When a student creates a concrete example of an abstract principle, they must understand the principle well enough to apply it — which is itself a form of retrieval practice and elaboration.2

Think of it like...

The difference between reading a definition of “gravity” and dropping a ball. The definition is abstract and forgettable. The ball dropping is concrete, visual, and memorable. Good examples are dropped balls — they make the abstract visible.

6. Dual coding — combining words and visuals

Dual coding means representing information in both verbal and visual formats. When you read a description of the water cycle and also study a diagram of it, you create two independent memory traces — one linguistic, one visual. Allan Paivio’s dual coding theory (1971) demonstrated that information stored in two formats is more likely to be retrieved than information stored in only one.8

This is not the same as “learning styles” (the debunked claim that some people are “visual learners” and others are “auditory learners”). Dual coding benefits everyone because it creates redundant representations in memory. If you cannot retrieve the verbal description, you may still retrieve the image, and vice versa.3

Concept to explore

Dual coding connects to cognitive-load-theory — well-designed visuals reduce extraneous load by offloading spatial relationships from verbal working memory to visual working memory.

Dunlosky et al. (2013) rated ten study techniques on their utility for learning. Three of the most popular strategies received the lowest ratings:1

StrategyUtility ratingWhy it fails
Highlighting/underliningLowMarks text but does not generate retrieval; creates illusion of familiarity
Re-readingLowIncreases fluency but not durable memory; each re-read produces diminishing returns
SummarisationLowCan work if done well, but most students summarise poorly; copying without transforming

The common thread: all three are passive or recognition-based. They keep information in front of your eyes rather than forcing you to reconstruct it from memory. They exploit the fluency heuristic — the tendency to mistake ease of processing for depth of understanding.9 After re-reading a chapter twice, the text feels familiar, and the student concludes they “know” it. But familiarity is not the same as the ability to retrieve, apply, or transfer knowledge under exam conditions.

Key distinction

Effective strategies make learning feel harder in the moment. Ineffective strategies make learning feel easier. This mismatch between subjective experience and objective outcome is why students consistently prefer the worst strategies and resist the best ones.

Why do we use it?

Key reasons

1. Durability. Evidence-based strategies produce learning that lasts weeks and months, not just hours. The difference between cramming and spaced retrieval practice is not a marginal improvement — it is often a doubling or tripling of long-term retention.6

2. Transfer. Strategies like interleaving and elaboration do not just help you remember facts — they help you apply knowledge in new contexts. Interleaving forces discrimination between problem types; elaboration builds connections that support flexible reasoning.7

3. Efficiency. These strategies produce more learning per hour of study. Students who use retrieval practice and spacing can study less total time and still outperform students who cram for longer periods.5

4. Metacognitive calibration. Using these strategies teaches you what you actually know versus what you think you know. A failed retrieval attempt is immediate, honest feedback — far more useful than the false confidence of a fluent re-read.9

When do we use it?

  • When studying for any exam or assessment where you need to retain information beyond the next 24 hours
  • When designing a curriculum and choosing how to sequence and space topics
  • When teaching or tutoring and selecting activities that maximise student learning rather than student comfort
  • When self-directing learning in any domain — languages, programming, music, medicine
  • When building a study schedule and deciding how to allocate limited time across subjects
  • When evaluating study advice from peers, apps, or online resources — asking “is this backed by evidence or just popular?”

Rule of thumb

If a study strategy feels easy and comfortable, it is probably not working very hard. The strategies that feel effortful and slightly frustrating are usually the ones producing the deepest learning.

How can I think about it?

The gym analogy

Evidence-based learning strategies are to studying what a proper training programme is to fitness. Walking on a treadmill while watching TV feels like exercise, and you do burn some calories — just as re-reading notes feels like studying, and you do absorb something. But a structured programme with progressive overload, varied exercises, and planned rest days produces fundamentally different results.

  • Re-reading = walking on the treadmill (comfortable, minimal adaptation)
  • Retrieval practice = lifting weights (effortful, forces adaptation)
  • Spacing = rest days (recovery allows consolidation and growth)
  • Interleaving = circuit training (mixing exercises forces different muscle groups to activate)
  • Elaboration = a coach explaining why each exercise matters (understanding builds motivation and technique)
  • Dual coding = watching a demonstration and reading the instructions (two channels reinforce each other)

Nobody gets strong by reading about weightlifting. Nobody learns deeply by re-reading notes.

The kitchen analogy

Imagine learning to cook. One approach: read the recipe five times, highlight the key steps, then attempt the dish for the first time at a dinner party. Another approach: attempt the dish from memory after one read (retrieval practice), try it on three different days (spacing), alternate between this recipe and two others (interleaving), explain to a friend why each ingredient matters (elaboration), and watch a video of the technique while reading the steps (dual coding).

  • The first cook “studied” more but learned less
  • The second cook made more mistakes in practice but was far more prepared when it counted
  • The first cook felt confident; the second cook felt challenged — but confidence is not competence

The kitchen does not care how many times you read the recipe. It cares whether you can execute under pressure.

Concepts to explore next

ConceptWhat it coversStatus
desirable-difficultiesBjork’s unifying framework: why harder learning leads to better retentioncomplete
retrieval-practiceThe testing effect, retrieval-induced forgetting, and designing effective recall practicestub
spaced-repetitionThe spacing effect, optimal intervals, and spaced repetition systems like Ankistub
deliberate-practiceEricsson’s framework for structured, feedback-driven skill developmentstub

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Where this concept fits

Position in the knowledge graph 

graph TD
    LP[Learning Paradigms] --> EBLS[Evidence-Based Learning Strategies]
    EBLS --> DD[Desirable Difficulties]
    EBLS --> RP[Retrieval Practice]
    EBLS --> SR[Spaced Repetition]
    EBLS --> DP[Deliberate Practice]
    style EBLS fill:#4a9ede,color:#fff

Related concepts:

  • knowledge-types — different types of knowledge (declarative, procedural, conditional) respond differently to each strategy
  • knowledge-granularity — the level of decomposition affects which strategies are most appropriate; atomic facts suit retrieval practice, while conceptual understanding suits elaboration
  • claims-and-propositions — evidence-based strategies are grounded in testable claims from cognitive psychology, not anecdotal wisdom

Sources

Further reading

Resources

Footnotes

  1. Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving Students’ Learning With Effective Learning Techniques. Psychological Science in the Public Interest, 14(1), 4-58. ↩ ↩2

  2. Weinstein, Y. & Sumeracki, M. (2016). Six Strategies for Effective Learning. The Learning Scientists. ↩ ↩2 ↩3 ↩4

  3. Weinstein, Y., Madan, C. R., & Sumeracki, M. A. (2018). Teaching the Science of Learning. Cognitive Research: Principles and Implications, 3(2). ↩ ↩2 ↩3 ↩4

  4. Bjork, R. A. & Bjork, E. L. (2011). Making Things Hard on Yourself, But in a Good Way: Creating Desirable Difficulties to Enhance Learning. In M. A. Gernsbacher et al. (Eds.), Psychology and the Real World. Worth Publishers. ↩ ↩2

  5. Roediger, H. L. & Karpicke, J. D. (2006). Test-Enhanced Learning: Taking Memory Tests Improves Long-Term Retention. Psychological Science, 17(3), 249-255. ↩ ↩2

  6. Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed Practice in Verbal Recall Tasks: A Review and Quantitative Synthesis. Psychological Bulletin, 132(3), 354-380. ↩ ↩2 ↩3 ↩4

  7. Rohrer, D. & Taylor, K. (2007). The Shuffling of Mathematics Problems Improves Learning. Instructional Science, 35(6), 481-498. ↩ ↩2

  8. Paivio, A. (1971). Imagery and Verbal Processes. Holt, Rinehart, and Winston. ↩

  9. Koriat, A. & Bjork, R. A. (2005). Illusions of Competence in Monitoring One’s Knowledge During Study. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(2), 187-194. ↩ ↩2

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