Source metadata
- Type: Popular science / pedagogy
- Authors: Peter C. Brown (writer), Henry L. Roediger III & Mark A. McDaniel (cognitive psychologists, Washington University in St. Louis)
- Publisher: The Belknap Press of Harvard University Press, 2014
- Scope: 328 pages, 8 chapters. Translates 125 years of cognitive psychology research on learning and memory into practical strategies. Roediger and McDaniel led a 10-year McDonnell Foundation research programme applying cognitive science to education. Brown provides narrative and case studies (pilots, surgeons, athletes, military).
Key takeaways
- Retrieval practice (the testing effect): Recalling information from memory is far more effective than rereading. A single quiz after reading produces ~50% better retention a week later. Students averaged A- on quizzed material vs C+ on non-quizzed material in a controlled classroom study (Columbia Middle School, Illinois).
- Spaced practice: Distributing study over time, with some forgetting between sessions, produces stronger and more durable learning than massed practice (cramming). Sleep aids memory consolidation. The Leitner box system is a practical implementation.
- Interleaving: Mixing the practice of different skills or problem types produces better discrimination and transfer than blocked practice of one type at a time. Cal Poly baseball players who practiced on randomly interleaved pitches significantly outperformed those who practiced one pitch type at a time.
- Desirable difficulties (Bjork & Bjork): Short-term impediments that slow apparent learning — spacing, interleaving, generation, variation — make learning stronger, more precise, and more enduring. The key insight: performance during practice is not a reliable indicator of durable learning.
- Generation effect: Attempting to solve a problem before being taught the solution leads to better learning, even when errors are made. Filling in a missing word (foot-s_ _e) produces better recall than reading the complete pair (foot-shoe).
- Elaboration: Giving new material meaning by expressing it in your own words and connecting it to what you already know. There is no known limit to how much you can learn through elaboration, unlike rote memorisation.
- Mental models: Experts organise knowledge into bundled procedures (like apps) that can be deployed automatically. These are built through varied retrieval practice, not repetitive drilling. Experts sort problems by underlying principles; novices sort by surface features.
- Illusions of knowing: Fluency with a text (from rereading) is mistaken for mastery of content. Students are poor judges of their own learning. The Dunning-Kruger effect: incompetent performers overestimate their competence and see no need to improve.
- Learning styles debunked: No empirical evidence supports the claim that matching instruction to a student’s preferred learning style (visual/auditory/kinesthetic) improves outcomes. People learn better when they “go wide,” drawing on all aptitudes.
- Growth mindset / neuroplasticity: Intellectual ability is not fixed. The brain physically changes with learning (myelination, synaptogenesis). Effort and struggle are signals of productive learning, not failure. Failure is a “badge of effort and a source of useful information.”
Notable claims
“Learning is deeper and more durable when it’s effortful. Learning that’s easy is like writing in sand, here today and gone tomorrow.”
“Rereading text and massed practice of a skill or new knowledge are by far the preferred study strategies of learners of all stripes, but they’re also among the least productive.”
“The most effective learning strategies are not intuitive.”
“The popular notion that you learn better when you receive instruction in a form consistent with your preferred learning style… is not supported by the empirical research.”
“Performance during the acquisition phase of a skill is ‘momentary strength’ — the very techniques that build ‘underlying habit strength,’ like spacing, interleaving, and variation, slow visible acquisition.”
Relevance
This source primarily informs:
- Evidence-based learning — Creates an entirely new Learning Science section in the wiki, separate from Game Design
- Fun-as-learning — Koster’s theory (fun = pattern learning) receives empirical support from the retrieval practice, desirable difficulties, and mental model research
- Teaching practice — Directly relevant for university lecturers designing courses and assessments
Open questions raised
- If the most effective learning strategies feel unproductive (desirable difficulties), how do you keep students motivated through the discomfort?
- The book was written in 2014. Has the learning styles myth lost traction in education, or does it persist?
- How do game-based learning environments map onto these strategies? Games naturally provide retrieval practice (challenges), spacing (levels), interleaving (mixed enemy types), and generation (puzzle solving before tutorials).
Links
- evidence-based-learning — created from this source
- fun-as-learning — Koster’s pattern-learning theory connects to retrieval practice and mental models
- interaction-loops — the LDARF loop mirrors the retrieval-feedback cycle described here