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cognitive-foundations

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Cognitive Foundations

认知科学基础

The science of how minds work, and what that means for design.
研究人类思维运作机制及其对设计的指导意义。

When to Use This Skill

何时使用本方法

  • Explaining why a design works or fails (grounded in research, not opinion)
  • Evaluating cognitive load or working memory demands
  • Predicting user performance (Fitts, Hick-Hyman)
  • Diagnosing mental model misalignment
  • Justifying design decisions to stakeholders with evidence
  • Understanding attention, perception, or memory failures
  • 解释设计成功或失败的核心原因（基于研究而非主观意见）
  • 评估认知负荷或工作记忆需求
  • 用Fitts、Hick-Hyman定律预测用户表现
  • 诊断心智模型与系统的偏差
  • 用实证依据向利益相关者证明设计决策的合理性
  • 分析用户注意力、感知或记忆层面的问题

Output Contracts

输出规范

For Single-Principle Analysis

单原则分析

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Cognitive Principle: [Name]

Cognitive Principle: [Name]

Principle: [1-sentence explanation]
Evidence in Design: [Where/how this applies]
Implication: [Specific, actionable recommendation]
Confidence: [High/Medium/Low] — [rationale]
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Principle: [1-sentence explanation]
Evidence in Design: [Where/how this applies]
Implication: [Specific, actionable recommendation]
Confidence: [High/Medium/Low] — [rationale]
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For Cognitive Audit (Comprehensive)

全面认知审计

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Cognitive Audit: [Screen/Flow Name]

Cognitive Audit: [Screen/Flow Name]

Working Memory Load

Working Memory Load

  • Items requiring recall: [count]
  • Cross-screen memory demands: [Y/N]
  • Verdict: [Acceptable / High / Overloaded]
  • Items requiring recall: [count]
  • Cross-screen memory demands: [Y/N]
  • Verdict: [Acceptable / High / Overloaded]

Attention Demands

Attention Demands

  • Preattentive features for critical info: [Y/N]
  • Competing attention demands: [list]
  • Change blindness risk: [areas where changes may go unnoticed]
  • Preattentive features for critical info: [Y/N]
  • Competing attention demands: [list]
  • Change blindness risk: [areas where changes may go unnoticed]

Mental Model Alignment

Mental Model Alignment

  • Expected user model: [what users likely think]
  • System behavior: [what actually happens]
  • Gap: [mismatch, if any]
  • Expected user model: [what users likely think]
  • System behavior: [what actually happens]
  • Gap: [mismatch, if any]

Predictive Laws

Predictive Laws

  • Fitts's Law concerns: [target size/distance issues]
  • Hick's Law concerns: [choice overload areas]
  • Fitts's Law concerns: [target size/distance issues]
  • Hick's Law concerns: [choice overload areas]

Gulf Analysis

Gulf Analysis

  • Gulf of Execution: [unclear how to act?]
  • Gulf of Evaluation: [unclear what happened?]
  • Gulf of Execution: [unclear how to act?]
  • Gulf of Evaluation: [unclear what happened?]

Violations of Nielsen's Heuristics

Violations of Nielsen's Heuristics

HeuristicViolationSeverity
......1-4
HeuristicViolationSeverity
......1-4

Recommendations

Recommendations

  1. [Highest priority fix]
  2. [Second priority]
  3. [Third priority]
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  1. [Highest priority fix]
  2. [Second priority]
  3. [Third priority]
undefined

For Explaining a Failure

失败案例分析

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Failure Analysis: [What Went Wrong]

Failure Analysis: [What Went Wrong]

Observed Behavior: [What users did]
Cognitive Explanation: [Which principle explains this]
Root Cause: [Design element that caused it]
Fix: [Specific change]

---
Observed Behavior: [What users did]
Cognitive Explanation: [Which principle explains this]
Root Cause: [Design element that caused it]
Fix: [Specific change]

---

Quick Reference: Predictive Laws

预测性定律速查

LawFormulaRule of Thumb
Fitts's LawMT = a + b × log₂(2D/W)Bigger + closer = faster. Screen edges are infinite.
Hick-HymanRT = a + b × log₂(n+1)More choices = slower. Reduce or organize options.
Steering LawT = a + b × (A/W)Narrow paths are slow. Cascading menus are hard.
Power LawT = a × N^(-b)Practice helps. Design for learnability.
定律公式经验法则
Fitts's LawMT = a + b × log₂(2D/W)目标越大、距离越近，操作速度越快。屏幕边缘视为无限大目标。
Hick-HymanRT = a + b × log₂(n+1)选项越多，决策速度越慢。应减少或合理组织选项。
Steering LawT = a + b × (A/W)操作路径越窄，速度越慢。级联菜单操作难度高。
Power LawT = a × N^(-b)练习可提升效率。设计需兼顾可学习性。

Quick Reference: Nielsen's 10 Heuristics

Nielsen十大启发式原则速查

#HeuristicQuick Test
1Visibility of system statusCan user always tell what's happening?
2Match system ↔ real worldLanguage familiar? Metaphors sensible?
3User control and freedomEasy undo? Clear exits?
4Consistency and standardsSame words/actions mean same things?
5Error preventionConstraints prevent errors before they occur?
6Recognition over recallOptions visible? No memory required?
7Flexibility and efficiencyShortcuts for experts?
8Aesthetic and minimalistOnly relevant info? No clutter?
9Error recoveryErrors explained in plain language with fix?
10Help and documentationSearchable, task-focused, concise?
序号启发式原则快速测试要点
1Visibility of system status用户是否能随时了解系统当前状态？
2Match system ↔ real world使用的语言是否贴近用户认知？隐喻是否合理？
3User control and freedom是否支持一键撤销？是否有清晰的退出路径？
4Consistency and standards相同的文字/操作是否始终代表同一含义？
5Error prevention是否有约束机制提前避免错误发生？
6Recognition over recall选项是否可见？是否无需用户记忆信息？
7Flexibility and efficiency是否为专家用户提供快捷操作？
8Aesthetic and minimalist是否仅展示相关信息？无冗余内容？
9Error recovery是否用通俗语言解释错误并提供修复方案？
10Help and documentation帮助文档是否可搜索、聚焦任务且简洁？

Quick Reference: Working Memory

工作记忆速查

  • Capacity: ~4 chunks (not 7)
  • Duration: ~20 seconds without rehearsal
  • Test: Count items user must hold in mind across screens/steps
Red flags:
  • "Remember this code and enter it on the next page"
  • Multi-step forms without visible progress/state
  • Complex comparisons requiring mental tracking
  • 容量: 约4个信息块（而非7个）
  • 持续时间: 无复述情况下约20秒
  • 测试方法: 统计用户在跨页面/步骤中必须记住的信息数量
危险信号:
  • “记住此代码，在下一页输入”
  • 无进度/状态显示的多步骤表单
  • 需要用户手动跟踪的复杂对比操作

Quick Reference: Preattentive Features

前注意特征速查

Detected in <200ms, no focused attention required:
  • Color (hue, saturation)
  • Size (length, area)
  • Orientation (angle)
  • Motion (flicker, direction)
  • Shape (curvature, enclosure)
Use for: Critical info, errors, changes, status Don't use for: Everything (loses signal value)
可在200毫秒内被识别，无需集中注意力：
  • 颜色（色调、饱和度）
  • 尺寸（长度、面积）
  • 方向（角度）
  • 运动（闪烁、方向）
  • 形状（曲率、封闭性）
适用场景: 关键信息、错误提示、状态变化 禁忌: 不要用于所有元素（会失去信号价值）

Cognitive Load Checklist

认知负荷检查表

Quick assessment for any interface:
FactorLow LoadHigh Load
Choices visible2-4 options10+ options
Memory demandsRecognitionRecall
Steps to goal1-3 clicks5+ clicks
InterruptionsNoneFrequent modals
Novel elementsFamiliar patternsNew conventions
Error recoveryClear undoDestructive actions
Visual complexityClean, groupedDense, undifferentiated
Scoring: Each "High Load" = +1. Score >3 = redesign needed.
快速评估任意界面的认知负荷：
因素低负荷高负荷
可见选项数量2-4个10个以上
记忆需求识别型回忆型
达成目标的步骤1-3次点击5次以上点击
干扰项无频繁弹出模态框
新元素占比熟悉模式全新交互规则
错误恢复清晰的撤销功能具有破坏性的操作
视觉复杂度简洁、分组清晰密集、无差异化
评分规则: 每一项“高负荷”计1分。得分>3分则需要重新设计。

Common Violations → Principle

常见问题对应原则

SymptomLikely ViolationFix
Users don't notice changesChange blindnessAnimate, highlight transitions
Users can't find the buttonPoor Fitts's LawIncrease size, reduce distance
Users freeze at optionsHick's Law overloadReduce choices, progressive disclosure
Users forget mid-taskWorking memory exceededShow state, don't require recall
Users misunderstand stateGulf of EvaluationBetter feedback, visibility
Users click wrong thingPoor affordance/signifierClearer visual treatment
Users make same error repeatedlyMode errorVisible mode indicators
Users abandon complex formsCognitive loadChunk, scaffold, save progress
症状可能违反的原则修复方案
用户未注意到界面变化Change blindness添加动画效果，高亮过渡区域
用户找不到按钮Fitts's Law 应用不当增大按钮尺寸，缩短操作距离
用户在选项前停滞Hick's Law 过载减少选项数量，采用渐进式展示
用户在任务中途遗忘工作记忆过载显示当前状态，无需用户回忆
用户误解系统状态Gulf of Evaluation优化反馈机制，提升状态可见性
用户点击错误目标可用性/符号化设计不足优化视觉呈现，增强可操作性
用户重复犯同一错误模式错误增加清晰的模式状态指示器
用户放弃复杂表单认知负荷过高拆分步骤、提供引导、自动保存进度

Process

实施流程

  1. Identify cognitive demands — What is the interface asking the user to perceive, remember, decide, or do?
  2. Match to principles — Which cognitive constraints or laws apply?
  3. Evaluate alignment — Does the design respect or violate these?
  4. Recommend changes — Specific modifications grounded in the principle
  1. 识别认知需求 — 界面要求用户完成哪些感知、记忆、决策或操作任务？
  2. 匹配对应原则 — 哪些认知约束或定律适用？
  3. 评估契合度 — 设计是否遵循或违反了这些原则？
  4. 提出改进建议 — 基于原则的具体修改方案

Deep Reference Files

深度参考文档

For comprehensive principles and research:
  • PSYCHOLOGY.md — Perception, memory, attention, biases, emotion, motivation
  • HCI-THEORY.md — Norman's model, predictive laws, error theory, research methods, heuristics
如需全面了解相关原则与研究：
  • PSYCHOLOGY.md — 感知、记忆、注意力、认知偏差、情绪、动机
  • HCI-THEORY.md — Norman模型、预测性定律、错误理论、研究方法、启发式原则

Primary Sources

主要研究来源

  • A Feature-Integration Theory of Attention.md — Treisman & Gelade on preattentive processing (informs: Quick Reference: Preattentive Features)
  • Judgment under Uncertainty- Heuristics and Biases.md — Kahneman & Tversky on cognitive biases (informs: PSYCHOLOGY.md § Decision Making)
  • A Feature-Integration Theory of Attention.md — Treisman & Gelade关于前注意加工的研究（支撑：前注意特征速查）
  • Judgment under Uncertainty- Heuristics and Biases.md — Kahneman & Tversky关于认知偏差的研究（支撑：PSYCHOLOGY.md 决策章节）

Key Researchers

核心研究者

  • Don Norman: Affordances, gulfs, emotional design
  • Daniel Kahneman: Dual process theory, heuristics and biases
  • Stuart Card: GOMS, information foraging, Fitts's Law
  • Anne Treisman: Feature integration, preattentive processing
  • Jakob Nielsen: Usability heuristics, discount usability
  • Ben Shneiderman: Direct manipulation, golden rules
  • Don Norman: 可供性、执行/评估鸿沟、情感设计
  • Daniel Kahneman: 双加工理论、启发式与认知偏差
  • Stuart Card: GOMS模型、信息搜寻理论、Fitts定律
  • Anne Treisman: 特征整合、前注意加工
  • Jakob Nielsen: 可用性启发式原则、低成本可用性测试
  • Ben Shneiderman: 直接操作、黄金设计法则

Remember

注意事项

  • Cognitive science explains why design principles work
  • Individual differences exist—design for variability, not averages
  • Lab findings may not generalize (ecological validity matters)
  • Theory informs but doesn't replace observing real users
  • When in doubt, reduce cognitive load—users have less capacity than you think
  • 认知科学解释了设计原则有效的底层逻辑
  • 用户个体存在差异——设计需兼顾多样性而非平均值
  • 实验室研究结果可能无法完全适配真实场景（生态效度至关重要）
  • 理论指导不能替代对真实用户的观察
  • 存疑时，优先降低认知负荷——用户的认知能力远低于你的预期