How Learning Actually Works According to Science

In 2006, psychologists Henry Roediger and Jeffrey Karpicke conducted an elegant experiment that upended conventional wisdom about learning. They gave students a prose passage to learn and divided them into groups with different study strategies.

Group 1: Read the passage four times

Group 2: Read the passage three times, then tried to recall everything without looking (retrieval practice)

Group 3: Read once, then practiced retrieval three times

When tested five minutes later, Group 1 performed best. They'd seen the material most recently; it felt most familiar. Most students predicted Group 1 would retain information best long-term.

The five-minute test was misleading. When tested one week later, results reversed dramatically:

  • Group 1 (four readings): 40% retention
  • Group 2 (three readings + one retrieval): 53% retention
  • Group 3 (one reading + three retrievals): 61% retention

The students' intuitions about their own learning were systematically wrong. Re-reading felt productive—the material became increasingly familiar—but familiarity isn't learning. Retrieval practice felt harder and less effective, yet produced dramatically superior retention.

This metacognitive illusion—misjudging what helps you learn—is pervasive. Students favor strategies that feel easy (highlighting, re-reading, cramming) while avoiding strategies that feel difficult (self-testing, spacing, elaboration). Comfort correlates negatively with learning effectiveness.

Understanding how learning actually works requires examining cognitive science research, not intuitions. The mechanisms are well-established but counterintuitive. This article explains the science comprehensively: how memory forms, what strengthens retention, why common study techniques fail, which evidence-based techniques work, how to accelerate learning, the role of forgetting, individual differences, and practical implementation.

The Neuroscience of Learning: How Memory Forms

Learning is physical: it changes your brain's structure. Understanding these mechanisms clarifies why some techniques work while others fail.

The Three Stages of Memory Formation

Stage 1: Encoding (Registering Information)

Information enters through senses. Attention determines what gets encoded. The brain receives enormous sensory input every second—encoding happens only for information receiving focused attention.

Key insight: You can't learn what you don't attend to. Multitasking during learning divides attention, degrading encoding. "Background learning" while distracted is largely ineffective.

Encoding strength depends on:

  • Depth of processing: Semantic (meaning-based) encoding creates stronger memories than superficial (appearance-based) encoding
  • Elaboration: Connecting new information to existing knowledge
  • Distinctiveness: Information that stands out encodes better
  • Emotional salience: Emotionally significant information encodes preferentially

Stage 2: Consolidation (Stabilizing Memory)

Encoded information remains fragile. Consolidation strengthens and stabilizes neural connections representing memories.

Two types:

  • Synaptic consolidation: Happens within hours, strengthens connections between neurons
  • Systems consolidation: Happens over days/weeks/months, reorganizes memories and integrates them into long-term knowledge networks

Sleep plays crucial role: Memory consolidation happens preferentially during sleep, particularly REM and slow-wave sleep. This explains why pulling all-nighters before exams is counterproductive—you sacrifice the biological process cementing memories.

Interference: New learning can disrupt consolidation of recently learned material if topics are similar and learning happens in rapid succession without breaks.

Stage 3: Retrieval (Accessing Memory)

Retrieval strengthens memories—this is the key insight most people miss. Retrieval isn't just assessment; it's a learning event.

Mechanisms:

  • Retrieval practice strengthens accessed pathways: Neural pathways activated during recall become stronger
  • Elaborative retrieval adds connections: Attempting to recall forces brain to search associative networks, creating additional retrieval paths
  • Retrieval updates memories: Each recall slightly modifies memory, integrating current context

"Desirable difficulties" (Robert Bjork): Harder retrieval (with effort) strengthens memory more than easy retrieval. This is why modest forgetting between practice sessions benefits long-term retention—retrieval becomes more effortful, producing stronger learning.

Why Common Study Techniques Fail

Most students use ineffective techniques. Understanding why they fail illuminates what works.

Technique 1: Re-reading (Low Effectiveness)

What students do: Read textbook or notes multiple times

Why it feels effective: Material becomes increasingly familiar; recognition improves

Why it fails: Fluency is not mastery. Re-reading creates illusion of learning through increased familiarity, but doesn't strengthen ability to retrieve information independently. Recognition (seeing material and feeling you know it) is much easier than recall (retrieving from memory without cues)—but exams test recall.

Research evidence: Multiple studies show re-reading produces minimal retention benefits beyond initial reading. Karpicke & Roediger (2008) found re-reading four times produced worse retention than reading once plus retrieval practice.

When re-reading helps: Only if substantial forgetting occurred between readings, forcing genuine cognitive effort to reconstruct meaning.

Technique 2: Highlighting and Underlining (Low Effectiveness)

What students do: Highlight "important" passages while reading

Why it feels effective: Creates visual organization; feels active

Why it fails: Highlighting is passive processing. Students often highlight excessively without deep processing. Creates illusion of engagement without encoding mechanisms that build memory.

Research evidence: Dunlosky et al. (2013) systematic review rated highlighting as low utility. No consistent benefits found.

Exception: Highlighting can help if followed by active processing—using highlights as basis for self-testing, summarization, or elaboration.

Technique 3: Cramming (Low Long-Term Effectiveness)

What students do: Mass studying immediately before exam

Why it feels effective: Can boost performance on immediate tests

Why it fails for long-term learning: Massed practice (studying repeatedly in short period) produces rapid initial gains but poor retention. Information enters short-term memory but doesn't consolidate well into long-term memory.

Research evidence: Classic Bahrick & Phelps (1987) study showed spaced learning (distributed over time) produced 150% better retention at long delays compared to massed learning, despite equal total study time.

When cramming "works": Only for immediate tests where retention beyond exam is unnecessary. Terrible for building lasting knowledge.

Technique 4: Passive Listening/Watching (Low Effectiveness)

What students do: Attend lectures or watch videos passively, assuming exposure equals learning

Why it feels effective: Feels effortless; information seems to "go in"

Why it fails: Encoding requires active cognitive processing, not passive reception. Listening creates temporary activation but doesn't build retrieval structures.

Research evidence: Active learning consistently outperforms passive learning across hundreds of studies. Freeman et al. (2014) meta-analysis of 225 studies found active learning increased exam performance and reduced failure rates in STEM courses.

How to fix: Take notes (ideally reorganizing/summarizing rather than transcribing), ask questions, test yourself on material, explain to others.

Technique 5: Learning Styles Matching (Ineffective)

Myth: People learn best through preferred "learning style" (visual, auditory, kinesthetic); instruction should match style

Why it persists: Intuitive; people do have preferences

Why it's wrong: No credible evidence supports learning styles theory. Pashler et al. (2008) reviewed literature, found zero studies demonstrating that matching instruction to learning style improves outcomes.

What does work: Using multiple modalities (visual + verbal, etc.) benefits everyone by providing multiple retrieval paths. Problem is matching content to modality that best suits it, not matching to learner preferences.

Evidence-Based Learning Techniques That Actually Work

Decades of cognitive science research identify techniques with robust effectiveness.

Technique 1: Retrieval Practice (High Effectiveness)

Method: Testing yourself on material without looking at answers

Why it works:

  • Strengthens memory retrieval pathways
  • Identifies gaps in knowledge
  • Consolidates learning
  • Slows forgetting

Research support: Roediger & Karpicke (2006) is canonical, but hundreds of studies confirm testing effect—testing produces better retention than studying.

How to implement:

  • Flashcards: But must test recall before flipping (no passive reviewing)
  • Practice problems: Work without looking at solutions
  • Free recall: Write everything you remember about topic
  • Past exams: Practice with old test questions
  • Self-quizzing: Create questions while studying, answer later

Key principles:

  • Retrieval must be effortful (not too easy)
  • Immediate feedback improves learning (check answers)
  • Multiple retrieval attempts (not one-and-done)
  • Retrieval should be varied (different question types, contexts)

Technique 2: Spaced Repetition (High Effectiveness)

Method: Distributing study sessions over time rather than massing them

Why it works: Spacing introduces "desirable difficulty"—modest forgetting between sessions makes retrieval harder, strengthening memory. Also provides multiple consolidation cycles.

Research support: Cepeda et al. (2006) meta-analysis of 317 studies confirmed spaced practice produces large benefits across domains, ages, and content types.

Optimal spacing: Depends on retention interval

Retention Goal Optimal Spacing Between Sessions
1 week 1-2 days
1 month 1 week
1 year 1 month
Permanent Expanding intervals (1 day → 3 days → 1 week → 2 weeks → 1 month → 3 months...)

General principle: Spacing should be long enough that retrieval requires effort but not so long that material is completely forgotten.

Practical implementation:

  • Leitner system: Flashcard box with compartments for different review frequencies
  • Spaced repetition software: Anki, SuperMemo (algorithms optimize spacing)
  • Calendar scheduling: Plan review sessions in advance at increasing intervals
  • Interleaved content: Study different topics across sessions

Technique 3: Elaboration (Moderate-High Effectiveness)

Method: Explaining and describing ideas with details, connecting new information to existing knowledge

Why it works: Creates richer, more interconnected memory representations. Adds retrieval paths. Deepens encoding through semantic processing.

Forms of elaboration:

  • Elaborative interrogation: Ask and answer "why" and "how" questions
  • Self-explanation: Explain concepts in your own words
  • Connecting to prior knowledge: Link new material to what you already know
  • Generating examples: Create your own examples of concepts
  • Analogies: Find similarities between new and familiar domains

Example: Learning about natural selection

Poor elaboration: "Natural selection is evolution through differential reproduction."

Good elaboration: "Natural selection works like quality control in manufacturing—products (organisms) with better features (traits) 'succeed' (survive and reproduce), so those features become more common in future production (generations). Just as profitable products get manufactured more, successful traits spread through populations. The 'quality control' is environmental pressures rather than human designers."

Research support: Dunlosky et al. (2013) rated elaborative interrogation as moderate utility; effectiveness varies with implementation quality.

Technique 4: Interleaving (Moderate-High Effectiveness)

Method: Mixing different topics or problem types in single study session rather than blocking same type together

Why it works:

  • Forces discrimination between concepts
  • Improves ability to choose correct approach (not just execute it)
  • Strengthens memory through varied context
  • Reduces interference between similar concepts

Example: Mathematics practice

Blocked practice: 20 problems on quadratic equations, then 20 on linear equations, then 20 on systems

Interleaved practice: Mix problem types—quadratic, then linear, then system, then quadratic, then system, then linear...

Counterintuitive effect: Interleaving makes practice feel harder and performance during practice is worse, but retention and transfer are superior.

Research support: Rohrer & Taylor (2007) showed interleaved math practice produced 43% better test performance than blocked practice despite worse performance during practice.

When it works best: Tasks requiring discrimination between similar concepts or choosing appropriate approaches.

Technique 5: Concrete Examples (Moderate Effectiveness)

Method: Using specific, concrete instances to illustrate abstract concepts

Why it works: Concrete information encodes more easily than abstract. Examples provide retrieval cues. Facilitates transfer to novel situations.

Implementation:

  • Generate your own examples (more effective than reading others')
  • Use multiple diverse examples (not just one)
  • Abstract underlying principle from examples
  • Return to examples when concept seems too abstract

Research support: Cognitive load theory explains why examples reduce extraneous load, freeing resources for learning. Worked examples particularly effective in early learning stages.

Technique 6: Dual Coding (Moderate Effectiveness)

Method: Combining verbal and visual representations

Why it works: Creates two independent memory representations (verbal and visual), providing multiple retrieval paths. Information coded both verbally and visually is more memorable than either alone.

Implementation:

  • Create diagrams for verbal material
  • Write verbal descriptions of visual material
  • Combine text with relevant images
  • Draw concept maps or flowcharts
  • Use spatial arrangements to represent relationships

Caveat: Visual and verbal must be genuinely integrated, not merely presented side-by-side without connection.

How to Actually Accelerate Learning

Can learning be sped up? Yes—but not through shortcuts. Through better techniques applied systematically.

Accelerator 1: Front-Load Attention

Principle: Learning efficiency is highest when attention is highest.

Application:

  • Study most challenging material when mentally fresh
  • Minimize distractions ruthlessly (phone off, single-tasking)
  • Use techniques like Pomodoro (intense focus blocks with breaks)
  • Recognize attention as finite resource—budget wisely

Accelerator 2: Test Early, Test Often

Principle: Retrieval practice produces learning, not just assessment.

Application:

  • Don't wait until you've "mastered" material to test yourself
  • Test immediately after initial encoding
  • Test again at expanding intervals
  • Use low-stakes testing (reduces anxiety that interferes with learning)

Accelerator 3: Embrace Difficulty (The Right Kind)

Principle: "Desirable difficulties" strengthen learning; unproductive difficulties waste time.

Desirable difficulties (strengthen learning):

  • Spacing (introduces forgetting that makes retrieval harder)
  • Interleaving (forces discrimination)
  • Testing (requires retrieval)
  • Generation (producing answers vs. reading)
  • Variation (changes contexts, formats, examples)

Undesirable difficulties (waste time):

  • Poor instruction or confusing materials
  • Excessive cognitive load (too much new information simultaneously)
  • Irrelevant distractions
  • Unclear goals or feedback

Application: Seek material that's challenging but not overwhelming. Sweet spot is ~85% success rate—enough difficulty to stretch capabilities without becoming frustrated.

Accelerator 4: Build Mental Models, Not Facts

Principle: Isolated facts are hard to retain and useless for transfer. Connected, structured knowledge is easier to learn and more useful.

Application:

  • Start with big picture (overview, structure)
  • Organize information into frameworks
  • Identify relationships between concepts
  • Ask: "How does this fit into what I already know?"
  • Build from fundamentals rather than memorizing surface details

Example: Learning a programming language

Ineffective: Memorize syntax for every command

Effective: Understand underlying concepts (variables, loops, functions, data structures), then look up syntax as needed. Syntax becomes memorable once you understand purpose.

Accelerator 5: Teach to Learn

Principle: Explaining to others reveals gaps, forces organization, and provides retrieval practice.

Application:

  • Study groups where members teach each other
  • Write explanations as if teaching someone
  • Create tutorials or guides
  • Answer questions on forums
  • Use Feynman technique: Explain concept in simple terms; identify gaps; review; simplify explanation

Caveat: Teaching is most effective after you've achieved initial understanding. Teaching too early can reinforce errors.

Accelerator 6: Get Immediate Feedback

Principle: Feedback allows error correction before mistakes consolidate.

Application:

  • Check answers immediately after practice
  • Use worked examples to compare your approach
  • Seek instructor/tutor feedback on understanding
  • Identify not just wrong answers but faulty reasoning

Timing matters: Immediate feedback best for procedural skills; slightly delayed better for conceptual learning (allows initial retrieval attempt).

Accelerator 7: Leverage Sleep and Exercise

Principle: Biological factors affect learning beyond study techniques.

Sleep:

  • Memory consolidation happens during sleep
  • Sleep deprivation impairs encoding and consolidation
  • 7-9 hours for adults optimal
  • Naps can boost consolidation after learning

Exercise:

  • Aerobic exercise increases BDNF (brain-derived neurotrophic factor), enhancing neuroplasticity
  • Exercise improves attention and reduces stress
  • Even light exercise (walking) during breaks benefits learning

The Paradox of Forgetting: Why It Helps Learning

Forgetting feels like failure. But controlled forgetting enhances learning.

Why Forgetting Helps

Reason 1: Creates desirable difficulty

Modest forgetting makes retrieval harder. Effortful retrieval strengthens memory more than easy retrieval.

Implication: Don't review immediately after learning. Wait until material becomes slightly harder to recall (but not completely forgotten).

Reason 2: Discriminates strong from weak learning

Forgetting reveals what you haven't truly learned. If you can't retrieve something after delay, you never really learned it—you just temporarily activated it.

Implication: Use testing to identify gaps, then focus re-study on material you couldn't retrieve.

Reason 3: Reduces interference

Similar memories interfere with each other when learned too close together. Spacing with forgetting reduces interference.

Implication: Don't cram similar topics back-to-back. Interleave or space them.

The Forgetting Curve

Hermann Ebbinghaus (1885) discovered systematic forgetting pattern:

  • 20 minutes after learning: ~60% retained
  • 1 day later: ~30% retained
  • 1 week later: ~20% retained
  • 1 month later: ~15% retained

But: Each retrieval resets the curve at higher baseline. After 4-5 spaced retrievals, information can be retained permanently.

Implication: Schedule reviews before complete forgetting but after partial forgetting. Optimal timing balances difficulty with success.

Individual Differences: What Varies and What Doesn't

Learning principles are universal, but some factors vary individually.

What's Universal (Applies to Everyone)

  • Testing effect works
  • Spacing works
  • Elaboration works
  • Attention is required for encoding
  • Sleep aids consolidation
  • Active learning beats passive learning

These are not "learning styles"—they're fundamental cognitive mechanisms shared by all humans.

What Varies

Prior knowledge: People with more relevant prior knowledge learn new related information faster (easier to integrate). This explains why experts learn in their domain rapidly—not different mechanism, just better foundation.

Working memory capacity: Varies between individuals. Higher capacity allows processing more information simultaneously, but doesn't change basic learning mechanisms.

Processing speed: Some people process information faster, but speed doesn't determine depth or retention quality.

Interest and motivation: Vary dramatically. Interest increases attention and willingness to engage in effortful learning. Motivation affects persistence.

Optimal difficulty level: What constitutes "desirable difficulty" varies—experts can handle more complexity than novices. Personalize difficulty, not learning mechanism.

Content modality preferences: Some prefer reading, others lectures. But preferences don't interact with learning effectiveness—matching instruction to preference doesn't improve outcomes. Choose modality based on content demands, not preferences.

Practical Implementation: Building Effective Learning Systems

How to integrate evidence-based techniques into real learning?

Strategy 1: The Testing-Spacing Combo

Most powerful combination: Spaced retrieval practice

Implementation:

Step 1: Initial learning through active engagement (reading + note-taking + self-explanation)

Step 2: Test yourself same day (retrieval practice)

Step 3: Review and test 1-2 days later

Step 4: Review and test 1 week later

Step 5: Review and test 2-4 weeks later

Step 6: (Optional for permanent retention): Review 2-3 months later

Tools: Spaced repetition software (Anki), physical flashcard boxes with Leitner system, calendar reminders.

Strategy 2: Pre-Testing Before Learning

Counterintuitive technique: Test yourself before learning material.

Why it works: Pre-testing primes attention for relevant information. Failed retrieval attempts create curiosity gap, increasing encoding when correct answers appear.

Implementation: Before reading chapter, try to answer end-of-chapter questions or predict what content will cover.

Strategy 3: Interleaved Practice Sessions

Structure each practice session with variety:

  • Mix different topics
  • Mix different problem types
  • Mix review (old material) with new material
  • Change contexts or formats

Example schedule: 30-minute session

  • 10 minutes: New topic A
  • 5 minutes: Test on old topic B
  • 10 minutes: Continue topic A
  • 5 minutes: Test on old topic C

Strategy 4: Elaborative Study Notes

Transform passive notes into learning tools:

Instead of: Transcribing or copying information

Do this:

  • Summarize in your own words
  • Add questions in margins
  • Create connections to prior knowledge
  • Generate your own examples
  • Draw diagrams showing relationships
  • Add confusion markers ("I don't understand why X") to address later

Strategy 5: Study Groups Done Right

Effective study groups:

  • Members study individually first
  • Meet to test each other
  • Take turns teaching concepts
  • Challenge each other's understanding
  • Focus on difficult material (not socializing)
  • Keep groups small (3-4 people)

Ineffective study groups:

  • First exposure to material happens in group
  • Passive reviewing or re-reading together
  • One person does all explaining
  • Social time dominates
  • Avoid difficult topics

Strategy 6: Track Your Learning

Metacognition improves with data:

  • Predict test performance before testing
  • Compare prediction to actual performance
  • Note which techniques worked well
  • Identify patterns in what you forget
  • Adjust strategies based on evidence

Over time, calibrate your metacognitive judgments—learn when you've actually mastered material vs. when you've merely created fluency illusion.

Common Misconceptions and Myths

Myth 1: "I'm a Slow Learner"

Reality: Learning speed varies less than people think. What looks like "fast learning" is often combination of: (1) strong prior knowledge enabling faster integration, (2) better techniques creating efficiency, (3) higher interest sustaining attention.

Most "slow learners" use ineffective techniques. Switch to evidence-based methods and "speed" improves dramatically.

Myth 2: "Some People Are Just Good at School"

Reality: "Good at school" usually means "figured out how to learn efficiently and what teachers want."

Academic success is learnable skill, not fixed trait. Students who learn effective techniques (testing, spacing, elaboration) outperform "naturally smart" students using poor techniques.

Myth 3: "You Can't Teach an Old Dog New Tricks"

Reality: Neuroplasticity persists throughout life. Older adults can absolutely learn new skills and information.

What changes with age: Processing speed declines slightly; working memory capacity decreases modestly. But these changes are small compared to benefits of experience and prior knowledge.

Older learners often learn more effectively—they have richer knowledge networks to integrate new information into.

Myth 4: "Cramming Works Because I Passed the Exam"

Reality: Cramming can boost short-term performance while producing poor long-term retention.

If goal is genuinely "pass this test then forget everything," cramming can work. But if goal is learning (knowledge you can use later), cramming is counterproductive.

Myth 5: "Multitasking Helps Me Learn"

Reality: Multitasking during learning severely impairs encoding. "Background" activities (music, TV, social media, texting) compete for attention, reducing learning efficiency.

People who claim to "learn better with distractions" are comparing distracted learning to their typical ineffective techniques—not to focused learning with effective techniques.

Myth 6: "More Time = More Learning"

Reality: How you study matters more than how long. One hour of retrieval practice produces better learning than four hours of re-reading.

Focus on effective techniques, not clock time.

Conclusion: Learning Is a Skill You Can Master

The Roediger-Karpicke experiment revealed fundamental insight: your intuitions about your own learning are often wrong. Familiarity feels like mastery. Easy practice feels effective. Difficult retrieval feels inefficient.

These feelings mislead. Effective learning feels harder than ineffective learning during practice, but produces dramatically superior retention and transfer.

The key insights:

1. Learning is physical brain change—memory formation involves encoding, consolidation, and retrieval. Understanding mechanisms clarifies why techniques work or fail.

2. Most common study techniques are ineffective—re-reading, highlighting, cramming, passive listening, and learning styles matching have poor evidence. They persist because they feel productive and are easy.

3. Evidence-based techniques work across domains—retrieval practice, spaced repetition, elaboration, interleaving, concrete examples, and dual coding have robust research support. They work for everyone, though implementation details vary.

4. Difficulty can strengthen learning—"desirable difficulties" like spacing, testing, and generation force effortful processing that strengthens memory. Avoid confusing desirable difficulty with unproductive difficulty from poor instruction.

5. Forgetting is part of learning—modest forgetting creates retrieval challenges that strengthen memory. Optimal learning involves spacing that allows forgetting, not continuous reviewing that maintains accessibility.

6. Core principles are universal—while pacing, modality preferences, and motivation vary individually, basic learning mechanisms are shared. Focus on universal principles, not individual "learning styles."

7. Learning is a metacognitive skill—improving learning requires understanding what works, monitoring your understanding accurately, and adjusting techniques based on evidence rather than feelings.

8. Implementation matters—knowing principles isn't enough. Build systems: spaced review schedules, retrieval practice routines, elaborative note-taking methods, interleaved practice.

As cognitive scientist Daniel Willingham observed: "Memory is the residue of thought." What you think about is what you'll remember. Techniques that force deeper thinking (retrieval, elaboration, generation) produce better learning than techniques that allow shallow processing (re-reading, highlighting).

The research is clear. The techniques work. The challenge is implementation—abandoning comfortable but ineffective habits, embracing effortful but productive techniques, and building systems that make evidence-based learning sustainable.

Learning how to learn is the ultimate meta-skill—it multiplies everything else. Invest time understanding cognitive science. Experiment with techniques. Track what works for you. Adjust based on evidence, not intuition.

The paradox: Learning to learn feels harder than mindless studying. But that difficulty is precisely what makes it effective. As Bjork's research shows, creating "desirable difficulties" isn't comfortable—but it's how expertise develops.

Your brain evolved to learn. Give it conditions and techniques evolution never anticipated—spaced practice, retrieval testing, elaborative processing—and it learns far more effectively than intuition suggests possible.

The science is settled. The question is: will you use it?

References

Bahrick, H. P., & Phelps, E. (1987). Retention of Spanish vocabulary over 8 years. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13(2), 344–349. https://doi.org/10.1037/0278-7393.13.2.344

Bjork, R. A. (1994). Memory and metamemory considerations in the training of human beings. In J. Metcalfe & A. Shimamura (Eds.), Metacognition: Knowing about knowing (pp. 185–205). MIT Press.

Brown, P. C., Roediger, H. L., & McDaniel, M. A. (2014). Make it stick: The science of successful learning. Harvard University Press.

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. https://doi.org/10.1037/0033-2909.132.3.354

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58. https://doi.org/10.1177/1529100612453266

Ebbinghaus, H. (1885/1913). Memory: A contribution to experimental psychology (H. A. Ruger & C. E. Bussenius, Trans.). Teachers College, Columbia University.

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415. https://doi.org/10.1073/pnas.1319030111

Karpicke, J. D., & Roediger, H. L. (2008). The critical importance of retrieval for learning. Science, 319(5865), 966–968. https://doi.org/10.1126/science.1152408

Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105–119. https://doi.org/10.1111/j.1539-6053.2009.01038.x

Roediger, H. L., & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17(3), 249–255. https://doi.org/10.1111/j.1467-9280.2006.01693.x

Rohrer, D., & Taylor, K. (2007). The shuffling of mathematics practice problems improves learning. Instructional Science, 35(6), 481–498. https://doi.org/10.1007/s11251-007-9015-8

Willingham, D. T. (2009). Why don't students like school? A cognitive scientist answers questions about how the mind works and what it means for the classroom. Jossey-Bass.

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