Summary
Most people learn in the wrong ways. Rereading, highlighting, and cramming — the most popular study strategies — are among the least effective. The strategies that actually work (retrieval practice, spacing, interleaving) feel harder, slower, and less productive, which is precisely why learners avoid them. This page distils the cognitive psychology research compiled in Make It Stick (Brown, Roediger & McDaniel, 2014) into the core principles and strategies that produce durable learning.
This page is intentionally separate from the game design wiki. Where connections to game design exist (e.g., fun-as-learning, interaction-loops), they are noted but not developed here.
The core strategies
1. Retrieval practice (the testing effect)
Recalling facts, concepts, or procedures from memory — rather than rereading them — is the single most powerful learning strategy. Every act of retrieval strengthens the memory and interrupts forgetting.
Key evidence:
- A single quiz after reading a passage produces ~50% better retention a week later than no quiz
- Columbia Middle School study: students averaged A- on quizzed material vs C+ on material studied three times but never quizzed
- 1917 study: children who spent 60% of study time reciting (retrieving) retained the most
- 1939 Iowa study (3,000 sixth-graders): once a student had taken a test, forgetting nearly stopped
- Multiple retrieval sessions are better than one; three tests “immunised” against forgetting
Practical forms: Low-stakes quizzes, flashcards, self-testing, practice problems, writing from memory, explaining concepts aloud without notes.
Why it works: Retrieval reconstructs learning from long-term memory (not short-term), strengthening neural pathways and creating multiple retrieval routes. It also provides accurate feedback about what you know and don’t know.
2. Spaced practice
Distributing study over time — with enough gap for some forgetting to set in — produces stronger and more durable learning than massed practice (cramming).
Key evidence:
- Crammers forgot 50% within two days; spaced retrievers forgot only 13%
- Sleep plays a large role in memory consolidation — practice with at least a day between sessions is beneficial
- The optimal interval: enough that retrieval requires effort, but not so much that you’re relearning from scratch
Practical implementation: the Leitner box. Four boxes of flashcards. Box 1 (most errors) is practised most frequently. When you get a card right, it moves to a less-frequent box. When you get it wrong, it moves to a more-frequent box. The better your mastery, the less frequent the practice — but it never disappears entirely.
Key insight: Cramming produces fast visible improvement (“momentary strength”) that feels like learning but is transitory. Spacing produces slower visible improvement but builds “underlying habit strength” — the kind of learning that lasts.
3. Interleaving
Mixing the practice of different skills, problem types, or subjects within a single session — rather than practising one type exhaustively before moving to the next (blocked practice).
Key evidence:
- Cal Poly baseball: players who practised on randomly interleaved pitches (fastball/curveball/changeup mixed) significantly outperformed those who practised 15 of each type in sequence — despite feeling less proficient during practice
- Interleaving the identification of bird types or oil painters improves both the ability to learn unifying attributes within a type and to discriminate between types
- Computing volumes of different geometric solids: interleaved practice produced better performance on later tests with random solids
Why it works: Interleaving forces you to discriminate between problem types and select the right solution strategy — exactly the skill you need in real situations where problems arrive unpredictably. Blocked practice lets you coast on short-term memory without developing discrimination.
4. Desirable difficulties (Bjork & Bjork)
Short-term impediments that slow apparent learning but make it stronger, more precise, and more enduring. The term was coined by psychologists Elizabeth and Robert Bjork.
The core desirable difficulties are:
- Spacing — letting some forgetting occur between practice sessions
- Interleaving — mixing different types within a session
- Generation — attempting to solve a problem before being taught the solution
- Variation — practising in different contexts and conditions
The generation effect: Attempting to produce an answer before seeing it — even if you get it wrong — leads to better learning than passively reading the answer. Example: filling in foot-s_ _e produces better retention of “shoe” than reading foot-shoe.
The paradox: The strategies that feel most productive (massed, blocked, repetitive practice) produce the least durable learning. The strategies that feel least productive (spaced, interleaved, generative practice) produce the most.
5. Elaboration
Giving new material meaning by expressing it in your own words and connecting it with what you already know.
- There is no known limit to how much you can learn through elaboration (unlike rote memorisation, which quickly hits capacity)
- The more connections you create between new learning and prior knowledge, the more retrieval cues you have later
- Examples: relating heat transfer principles to warming your hands on a cup of cocoa (conduction), sun pooling in a room (radiation), air conditioning blast (convection)
Practical forms: Explaining concepts in your own words, finding real-world examples, connecting new material to personal experience, asking “how does this relate to what I already know?“
6. Reflection
Reflection is a form of retrieval practice combined with elaboration: What happened? What did I do? How did it work out? What would I do differently?
The neurosurgeon Mike Ebersold describes how he would go home after a difficult surgery and think through what happened, what he could improve, and mentally rehearse modifications — then try them the next day. This cycle of reflection → mental rehearsal → application built novel techniques that became reflexive under pressure.
How learning works: encoding → consolidation → retrieval
Encoding: Sensory perceptions are converted into mental representations (memory traces) in short-term memory. Think of notes jotted on a scratchpad.
Consolidation: The brain reorganises and stabilises memory traces for long-term storage. This involves deep processing: replaying the learning, filling in gaps, making connections to prior knowledge. Sleep plays a significant role. The process takes hours to days. An analogy: writing an essay draft, setting it aside, then revising with greater clarity.
Retrieval: Calling up learning from long-term memory. Each successful retrieval strengthens the memory traces and makes them modifiable again (reconsolidation), allowing them to connect to newer learning. This is why retrieval practice is so powerful — it doesn’t just test learning, it changes learning.
Key implication: If you practice something over and over in rapid succession, you’re leaning on short-term memory and very little consolidation or reconsolidation occurs. The visible improvement is real but temporary. When you space practice and allow some forgetting, retrieval requires reconstruction from long-term memory, which triggers reconsolidation and produces durable learning.
What doesn’t work (and why people do it anyway)
Rereading
The #1 study strategy of college students (80%+ in some surveys). Three strikes against it:
- Time-consuming
- Doesn’t result in durable memory
- Creates an illusion of knowing — growing familiarity with the text feels like mastery of the content
Massed practice (cramming)
“Practice-practice-practice” of a single skill or topic. Produces fast visible gains that are gratifying but transitory. Likened to “binge-and-purge eating — a lot goes in, but most of it comes right back out.”
Highlighting and underlining
Passive engagement with surface features of text. No retrieval, no elaboration, no generation. Feels productive; accomplishes little.
Illusions of knowing and metacognition
Metacognition is what we know about what we know. Accurate metacognition is critical for effective learning — you need to know what you don’t know in order to focus your effort.
The fluency illusion: Rereading a text creates fluency (ease of processing) that is mistaken for mastery of the underlying concepts. Students who can repeat phrases from a lecture often cannot apply the ideas in a new context.
The Dunning-Kruger effect: Incompetent performers overestimate their competence and — critically — lack the skills to recognise their own incompetence. Studies showed that students scoring at the 12th percentile believed their logical reasoning was at the 68th percentile. However, when these students were taught the skills to evaluate logical reasoning, their self-assessment became dramatically more accurate.
Kahneman’s System 1 and System 2: System 1 (fast, automatic, intuitive) is powerful but susceptible to illusion. System 2 (slow, deliberate, analytical) is needed to check System 1’s conclusions. Pilots trained to trust instruments over vestibular sensation are applying System 2 to override System 1. The China Airlines Flight 006 incident (1985) is a dramatic example of what happens when System 1 overrides instrument readings.
Calibration: The remedy for illusions of knowing is regular self-testing. Testing doesn’t just measure learning — it reveals gaps. The military concept of “shooting an azimuth” (climbing to a height to check your heading) is an apt metaphor for using practice tests to recalibrate understanding.
Learning styles: the myth
The claim that people learn better when instruction matches their preferred style (visual, auditory, kinesthetic) is not supported by empirical research. While people do have preferences, and there are indeed multiple forms of intelligence, the evidence shows that learners benefit most from “going wide” — drawing on all their aptitudes rather than limiting instruction to one modality.
What does matter is matching the nature of the content to the appropriate modality: learning geography benefits from maps (visual); learning a language benefits from speaking and listening (auditory); learning surgery benefits from practice with hands (kinesthetic). This is about the content, not the learner.
Growth mindset and neuroplasticity
The fixed mindset fallacy: Many people believe intellectual ability is hardwired from birth, and failure is an indictment of native ability.
The evidence: The brain physically changes with learning. Neurons sprout axons that connect to dendrites of other neurons, forming synapses. Myelin sheaths develop around well-used pathways, speeding signal transmission. The fine structure of neural networks is shaped by experience and is capable of substantial modification throughout life.
Implication: Failure is a “badge of effort and a source of useful information — the need to dig deeper or to try a different strategy.” Struggle is not a sign that learning is failing; it is a sign that learning is happening. This aligns with the desirable difficulties principle: when learning feels hard, you’re doing the most important work.
Connections to game design
These connections are noted briefly for cross-reference; the learning science stands on its own.
- fun-as-learning — Koster’s theory that fun = pattern recognition/learning is empirically supported by the retrieval practice and mental model research. Games that force players to recognise patterns and retrieve solutions under pressure are doing exactly what cognitive science recommends.
- interaction-loops — The LDARF loop (Learn/Decide/Action/Rules/Feedback) mirrors the retrieval-feedback cycle. Each game challenge is effectively a retrieval test with immediate feedback.
- flow — Desirable difficulties must be calibrated to the learner’s skill level — too easy and no effortful retrieval occurs; too hard and retrieval fails entirely. This is the same challenge/skill calibration that produces flow.
- meaningful-decisions — The generation effect (attempting to solve before being taught) maps directly to games that present problems before tutorials.
- Games as natural learning environments — Games inherently provide retrieval practice (challenges), spacing (between sessions), interleaving (mixed enemy types, varied puzzles), generation (puzzles before solutions), and immediate feedback on performance. This may explain why game-based learning can be effective when it works.
Evidence
Content drawn from Brown, Roediger & McDaniel, Make It Stick (Harvard, 2014). Key studies cited: Tulving (1967) on repetition and learning; Roediger & Karpicke (2006) on testing vs rereading; McDaniel, Agarwal et al. (2011) on the Columbia Middle School classroom study; Bjork & Bjork on desirable difficulties; Kahneman (2011) System 1/System 2; Dunning & Kruger (1999); Dweck on growth mindset; Doidge (2007) on neuroplasticity. The research programme was funded by the James S. McDonnell Foundation and Washington University’s Center for Integrative Research in Learning and Memory.
Related
- fun-as-learning — Koster’s game design theory of fun as pattern learning; empirically supported by this research
- interaction-loops — The LDARF loop parallels retrieval-feedback cycles
- flow — Desirable difficulty calibration parallels challenge/skill balance
- source-make-it-stick