---
id: wiki-2026-0508-deliberate-practice
title: Deliberate Practice
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [deliberate practice, Anders Ericsson, expertise, 10000 hours, mental representation, growth mindset]
duplicate_of: none
source_trust_level: A
confidence_score: 0.93
verification_status: applied
tags: [learning, deliberate-practice, ericsson, expertise, mental-models, skill-acquisition]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: learning theory
  applicable_to: [Skill Acquisition, Career Growth, Expertise Development]
---

# Deliberate Practice

## 매 한 줄
> **"매 단순 반복 X — 매 한계 zone 의 precise 의 training"**. Anders Ericsson 의 "Peak" (2016). 매 specific goal + 매 feedback + 매 effort + 매 mental model. 매 10K hour 의 myth — 매 quality > quantity. 매 modern: 매 LLM-aided coach.

## 매 핵심 element

### Ericsson 의 4 condition
1. **Specific goal** (not "improve").
2. **Focused intensity** (not background).
3. **Immediate feedback** (not delayed).
4. **Comfort zone 의 escape** (learning zone).

### 매 mental representation
- 매 expert 의 domain-specific structure.
- 매 chunk recognition (chess master).
- 매 deep pattern.

### 매 zone
- **Comfort**: 매 already mastered.
- **Learning**: 매 just-beyond — 매 deliberate target.
- **Panic**: 매 too far → 매 disengage.

### 매 vs general practice
| 측면 | Deliberate | Casual |
|---|---|---|
| Goal | Specific | Vague |
| Effort | Maximum | Comfortable |
| Feedback | Immediate | None |
| Reflection | Yes | No |
| Mentor | Often | Rarely |

### 매 limit
- 매 매 hour 4-5 max (cognitive fatigue).
- 매 mentor / coach 의 important.
- 매 self-practice 의 wrong technique 의 reinforce.
- 매 over-emphasis on natural talent ignored.

### 매 critique (recent research)
- 매 talent + practice 매 둘 다 important.
- 매 10K hour 의 average 가, 매 huge variance.
- 매 domain 의 따라 transfer 의 다름.

### 매 modern AI 의 응용
- **Aim training** ([[Cognitive Training Software (eg Aim Lab_KovaaKs)]]): 매 deliberate practice 의 gamified.
- **Code review feedback**: 매 immediate.
- **LLM coach**: 매 personalized feedback.
- **Spaced repetition** (Anki).
- **Active recall**.

### 매 plan
1. **Identify weakness** (specific).
2. **Set measurable goal**.
3. **Design exercise** (just-beyond).
4. **Schedule** (focused 4 hour max).
5. **Get feedback** (mentor / data / LLM).
6. **Reflect** (what worked / didn't).
7. **Iterate**.

## 💻 패턴

### Practice plan template
```yaml
skill: 'TypeScript advanced types'
current_level: 'intermediate'
target: 'use conditional types comfortably in 2 weeks'

weakness_audit:
  - 'don't recognize when to use conditional types'
  - 'syntax of `infer` 의 rough'
  - 'distributive conditional 의 confused'

weekly_schedule:
  - day: Mon
    focus: 'conditional type basic'
    exercise: 'solve 5 type challenges'
    duration_min: 60
    feedback: 'TypeScript Playground'
  - day: Wed
    focus: 'infer keyword'
    exercise: 'extract type from function signature'
    duration_min: 60
    feedback: 'review with senior'
  - day: Fri
    focus: 'apply to real codebase'
    exercise: 'refactor one util'
    duration_min: 90
    feedback: 'PR review'

reflection_after_each:
  - 'what was hardest?'
  - 'what mental model is forming?'
  - 'what is next constraint?'
```

### LLM-aided coach
```python
def deliberate_coach(user_attempt, reference, skill='code_review'):
    prompt = f"""You are a deliberate practice coach for {skill}.

User's attempt:
{user_attempt}

Reference (best practice):
{reference}

Provide:
1. Specific gap (1 sentence).
2. Root cause / missing mental model.
3. ONE concrete next exercise (just-beyond comfort).
4. What feedback signal to look for.

Don't praise. Be specific and constructive."""
    return llm.generate(prompt)
```

### Spaced repetition (Anki-style)
```python
class SpacedReview:
    def __init__(self):
        self.cards = {}  # 매 id → (next_review, interval, ease)
    
    def review(self, card_id, quality):  # 매 quality 0-5
        prev = self.cards.get(card_id, (datetime.now(), 1, 2.5))
        _, interval, ease = prev
        
        if quality < 3:
            interval = 1  # 매 reset
        else:
            ease = max(1.3, ease + 0.1 - (5 - quality) * 0.08)
            interval = int(interval * ease)
        
        self.cards[card_id] = (
            datetime.now() + timedelta(days=interval),
            interval, ease,
        )
```

### Active recall (vs re-read)
```python
def study_session(material, mode='active_recall'):
    if mode == 'active_recall':
        return [
            'Read chapter (no notes)',
            'Close book',
            'Write everything you remember (5 min)',
            'Compare with book — note gaps',
            'Re-read only the gap parts',
            'Test self again next day',
        ]
    elif mode == 'passive_reread':  # 매 ❌ less effective
        return ['Read 3 times']
```

### Feedback loop (immediate)
```python
class PracticeSession:
    def __init__(self, skill):
        self.skill = skill
        self.attempts = []
    
    def attempt(self, action):
        result = execute(action)
        feedback = evaluate(result, target=self.skill.target)
        self.attempts.append({
            'action': action,
            'result': result,
            'feedback': feedback,
            'timestamp': datetime.now(),
        })
        # 매 immediate 의 next attempt 의 inform.
        return feedback
    
    def reflect(self):
        return llm.generate(f"""Reflect on this practice session:
{self.attempts[-10:]}

What patterns? What's the next bottleneck?""")
```

### Mental model construction
```python
def chunk_practice(domain):
    """매 expert 의 chunking 의 build."""
    # 매 e.g., chess: 매 매 board configuration → 매 pattern recognize
    # 매 매 day 의 100 position → 매 quick recognize / response
    return [
        'Day 1-7: 매 100 pattern flashcard / day',
        'Day 8-14: 매 mixed deck (no order)',
        'Day 15+: 매 apply in game (transfer)',
    ]
```

### Energy management
```python
def deliberate_practice_schedule():
    """매 cognitive fatigue 의 limit."""
    return {
        'morning_block': '90 min hardest skill (peak focus)',
        'break': '15 min walk (DMN-friendly)',
        'mid_block': '90 min secondary skill',
        'long_break': '60 min lunch + nap',
        'afternoon_block': '60 min review + reflect',
        'rest_of_day': 'light tasks / non-deliberate',
        'total_deliberate': '~4 hours max',
        'days_off': '1-2 / week (recovery)',
    }
```

### Skill progression (Bloom's Taxonomy + Dreyfus)
```python
DREYFUS_STAGES = [
    ('Novice', 'Rule-following, hand-holding'),
    ('Advanced Beginner', 'Recognize aspects'),
    ('Competent', 'Plan + analyze, follow standard process'),
    ('Proficient', 'Holistic + experience-driven'),
    ('Expert', 'Intuitive + transcend rules'),
]

def practice_for_stage(stage):
    """매 매 stage 의 different practice."""
    return {
        'Novice': 'Tutorials + close mentorship',
        'Advanced Beginner': 'Guided practice + frequent feedback',
        'Competent': 'Independent project + post-mortem',
        'Proficient': 'Complex challenge + reflection',
        'Expert': 'Teaching + writing + research',
    }[stage]
```

## 매 결정 기준
| 상황 | Approach |
|---|---|
| New skill | Tutorial + mentor + small wins |
| Plateau | Identify specific weakness + targeted exercise |
| Career growth | T-shape: 매 deep + 매 broad |
| Esports | Aim trainer + mentor (review video) |
| Code | TDD + code review + refactor practice |
| Writing | Daily output + edit + critic |
| Music | Slow + isolated + correct rep |

**기본값**: 매 specific + 매 feedback + 매 4-hour cap + 매 reflection.

## 🔗 Graph
- 부모: [[Expertise]]
- 응용: [[Cognitive Training Software (eg Aim Lab_KovaaKs)]] · [[Pair-Programming]]
- Adjacent: [[Default Mode Network (DMN)]] · [[Brain-Derived Neurotrophic Factor (BDNF)]] · [[Cognitive Reserve Theory]] · [[Articulateness]] · [[Bounded_Rationality|Bounded-Rationality]]
- 사상가: [[Anders-Ericsson]] · [[Carol-Dweck]] (growth mindset)

## 🤖 LLM 활용
**언제**: 매 skill development plan. 매 plateau breaking. 매 feedback design. 매 personal coach.
**언제 X**: 매 fixed mindset 의 reinforce. 매 burnout 의 over-push.

## ❌ 안티패턴
- **Mindless rep**: 매 habit 의 X.
- **Comfort zone 의 stuck**: 매 plateau.
- **No feedback**: 매 wrong technique 의 reinforce.
- **Over-train (>4hr)**: 매 fatigue 의 quality drop.
- **Talent 의 over-emphasize**: 매 fixed mindset.
- **Solo practice 의 only**: 매 mentor 의 가치 lose.
- **No reflection**: 매 learning 의 X.

## 🧪 검증 / 중복
- Verified (Ericsson "Peak", Dreyfus stages, Bloom taxonomy).
- 신뢰도 A.
- Related: [[Cognitive Training Software (eg Aim Lab_KovaaKs)]] · [[Default Mode Network (DMN)]] · [[Brain-Derived Neurotrophic Factor (BDNF)]] · [[Cognitive Reserve Theory]] · [[Articulateness]] · [[Be-Detailed]].

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — Ericsson 4 + 매 zone + plan + LLM coach + Dreyfus + spaced rep code |
