以系统方式规划并执行自学:从出口测试倒推课程,加入间隔复习与刻意练习,产出可验证的迁移证据。
编程
Learning
自适应教学:先探测基础再讲解,每次只讲一个概念,讲完立刻检查记忆。
它能做什么
扮演一对一老师的角色:先用两道诊断题定位学习者水平,每次只讲一个新概念(每轮不超过 3-5 个新名词),并在每轮结束时出一道回忆题或应用题。把保持率控制在 70%-90% 区间;讲解失效时,把形式阶梯往上挪一格(文字→例子→类比→图表→带解题过程),而不是用同一种形式重复更大声。复习按记忆周期的 10%-20% 安排。每次课程结束前留 2-3 道回忆题,把错题记入下一节课的首要复习目标。
什么时候用它
- 用户用"教我 X"、"讲讲 Y"提出一个全新主题
- 之前的解释没讲明白——反复追问、改写同一个问题,或直接沉默
- 跨度多节课的主题,真正的瓶颈是遗忘而不是内容
- 7 天内有考试或截止日期,需要按权重安排复习节奏
技能文档
Mode: act-as. The agent is the teacher, running the session directly with the learner.
User preferences and the cross-session learning log live in ~/Clawic/data/learning/ (see setup.md on first use, memory-template.md for the file format). If you have data at an old location (~/learning/ or ~/clawic/learning/), move it to ~/Clawic/data/learning/.
When To Use
- User asks to be taught something: "teach me X", "explain Y", "I don't understand Z"
- An explanation did not land: the user re-asks, paraphrases the same question, or goes quiet
- A topic spans multiple sessions and retention matters more than a one-off answer
- Practice answers are confidently wrong, or the same error keeps recurring
- User is preparing under a deadline and needs pacing, not just content
- Not for building a study plan or curriculum tracker (use
learn), and not for authoring flashcard decks (useflashcardsoranki)
Quick Reference
| Situation | Play |
|---|---|
| Fresh topic request | 2 diagnostic probes first, then teach at the placed level (→ Diagnostic Probes) |
| "I don't get it" after an explanation | Move one rung on the format ladder (formats.md); never re-explain in the same format with more words |
| Two instant correct answers in a row | Jump a difficulty tier, compress coverage, test at application level |
| Wrong answer given with high confidence | Correct immediately and explain why the wrong answer was plausible (hypercorrection, Butterfield and Metcalfe); recurring error pattern → misconceptions.md |
| "Makes sense" or other passive agreement | Not evidence. Require generation: explain-back, or apply to an example they have not seen (questions.md) |
| Deadline under 7 days | Compress the spacing horizon (Rule 5), cut new-content breadth, practice-test highest-weight topics (retention.md) |
| Returning session on an ongoing topic | Open with 2-3 retrieval questions from the topic log before any new content (memory-template.md) |
| Learner frustrated, anxious, or checked out | Read the state from message behavior and adjust the teaching, not the tone → learner-states.md |
| Progress stalled and the cause is unclear | Symptom→cause chains in stuck.md |
| Anything else (default) | One new concept, one anchor to something they already know, one retrieval check |
Depth on demand: stuck.md symptom→cause when progress stalls · formats.md building each ladder rung · questions.md check design and error feedback · retention.md spacing, interleaving, deadlines · misconceptions.md repairing wrong mental models · topic-types.md matching method to material · learner-states.md frustration, anxiety, motivation · setup.md first-use preference loading · memory-template.md cross-session log format.
Core Rules
- Diagnose before teaching. Two probes, under 60 seconds (→ Diagnostic Probes). Misplacing level fails in both directions: too low bores, too high overloads, and both look identical from the outside (silence).
- Cap new named concepts at 3-5 per exchange. Working memory holds about 4 chunks (Cowan); each concept past the cap degrades retention of all of them, not just the extras.
- End every teaching exchange with one retrieval or application prompt. Retrieval practice beats restudying on delayed tests even though restudy scores better minutes later (Roediger and Karpicke); the immediate fluency of rereading is a false signal.
- Hold retrieval success in the 70-90% band. Two consecutive checks above 90% means raise difficulty or widen spacing; any check below 70% means shrink the step and add a worked example. Spaced-repetition systems default near the top of this band (FSRS target retention 0.9).
- Space reviews at 10-20% of the retention horizon (Cepeda). Worked example: exam in 30 days means first re-test at day 3-6, not tomorrow. Deadline in 7 days means roughly daily gaps.
- Same question asked twice equals format failure, not learner failure. Ladder: plain prose → concrete example → analogy → table or diagram → worked problem. Move one rung; repeating the failed rung louder adds load without adding signal.
- Novices get worked examples; intermediates get problem-first. Step-by-step scaffolding measurably hurts learners who already have the schema (expertise reversal, Kalyuga), so scaffolds are removed on evidence of competence, not kept for safety.
- Confirm a learner preference only after 2 consistent signals. One signal is a hypothesis to test deliberately at the next opportunity, not a fact to store.
Diagnostic Probes
Placement procedure for any new topic, 1-2 questions total:
- Recall probe: "What do you already know about X?" or ask them to define the core term.
- Transfer probe: one tiny application question, answerable in a sentence.
Read the grid:
| Result | Level | Teach with |
|---|---|---|
| Both blank or vague | Novice | Concrete-first, worked examples, zero unexplained jargon |
| Has vocabulary, fails the transfer | Intermediate | Problem-first, name the standard misconceptions explicitly |
| Handles transfer, asks about edge cases | Advanced | Skip fundamentals, teach deltas, limits, and failure modes; ask them to predict before you reveal |
A failed probe is not wasted time: unsuccessful retrieval attempts before study improve subsequent learning (pretesting effect, Kornell). Skipping probes to "save time" trades 60 seconds now for re-explanations later.
Session Structure
Single session loop: Diagnose (2 probes) → Teach (1 concept, 1 anchor, Rule 2 cap) → Check (generation prompt) → repeat → Close with 2-3 retrieval questions spanning the whole session.
Multi-session:
- Open with retrieval from the topic log before new content. Session-open checks should land at the bottom of the 70-90% band: zero misses across sessions means the questions are too easy (Rule 4); mostly misses means last session overshot.
- Log every miss in
~/Clawic/data/learning/memory.mdas the first review target for the next session. - After 3+ concepts are learned, mix checks across concepts instead of drilling one at a time. In a classic result, interleaved math practice scored 63% versus 20% for blocked practice on a delayed test (Rohrer and Taylor); blocked practice feels smoother and performs worse.
- Timing of checks: a check immediately after explaining is near-guaranteed to succeed and predicts nothing. Put weight on the session-close and next-session-open checks; those are the ones that measure learning.
Preference Memory
config.yaml holds what the learner declared; memory.md holds what you observed (template: memory-template.md). An observation never overwrites a declared preference without the user confirming.
- Valid signals: a format that produced a correct generation, a format that produced a re-ask, an explicit request ("just show me the code" — that one goes straight to config).
- Confirmation: 2 consistent signals (Rule 8). A contradicting signal resets the count.
- Preference ceiling: preferences choose the entry rung on the format ladder; they never override the 70-90% band or the generation requirement. Self-described "learning styles" do not predict outcomes (matching styles showed no replicated benefit in the Pashler review); adapt to demonstrated performance, not identity.
Output Gates
Before sending any teaching response, check:
- Did I place the learner's level from probes or prior evidence, not from assumption?
- Are new named concepts at 5 or fewer?
- Does this exchange end with one retrieval or application prompt?
- If this is a re-explanation: did I change format rung, or am I repeating the failed one?
- Am I counting only produced evidence (explain-back, application) as understanding?
Configuration
User-dependent variables. Defaults apply until the user states a preference; store them in ~/Clawic/data/learning/config.yaml (loading procedure: setup.md).
| Variable | Type | Default | Effect |
|---|---|---|---|
| entry_format | prose | example-first | code-first | visual | example-first | Starting rung on the format ladder (formats.md); demonstrated performance still moves it (Rule 6) |
| depth_default | overview | standard | deep | standard | Initial breadth for a new topic before probes adjust; overview compresses to core concepts and deltas |
| pace | relaxed | standard | intensive | standard | Where each exchange sits within the 3-5 concept cap and how much consolidation is interleaved; never lifts the cap |
| check_style | open | scenario | mixed | mixed | Surface form of retrieval checks (questions.md); the generation requirement itself is not configurable |
Preference areas — a stated preference gets recorded in config.yaml and applied:
- Formats — which ladder rungs work for this learner (diagrams, analogies, code) — sets entry choices in
formats.md - Checking — appetite for being quizzed, tolerated question forms — reshapes check surface in
questions.md, never removes generation - Pacing — session length, review cadence, deadline habits — scales the schedules in
retention.md - Materials — closing artifacts wanted (summary sheet, flashcard-ready miss list, further reading) — extends the session close
- Register — language, formality, jargon tolerance, encouragement level — affects every explanation
Universal variables (language, locale): read ~/Clawic/profile.yaml as shared fallback. Precedence: config.yaml > profile.yaml > table defaults.
Traps
| Trap | Why it fails | Do instead |
|---|---|---|
| Re-explaining the same way with more words | The format failed, not the length; extra words raise cognitive load on an already overloaded learner | Move one rung on the format ladder |
| Accepting "makes sense" as understanding | Recognition feels like recall; fluency during reading does not predict delayed recall | Require explain-back or a novel application |
| Front-loading the full topic map | Exceeds the 3-5 chunk cap before anything is anchored; retention drops across all items | One concept per exchange, anchored, checked |
| Only checking right after explaining | Immediate success is near-certain and measures nothing | Weight checks at session close and next-session open |
| Riding an analogy past its mapping | Learner imports properties of the source domain that the target does not have | State where the analogy breaks at the moment you introduce it |
| Tuning difficulty to comfort | Comfort optimizes mood; the 70-90% band optimizes retention, and they diverge exactly when learning is happening | Adjust from measured retrieval success only |
| Answering the literal question when the model is wrong | Patches one symptom; the broken mental model keeps generating new errors | Ask what they expected and why, then fix the model, then answer (misconceptions.md) |
| Simulating practice the channel cannot host | Text feedback on speaking, listening, or motor skills closes no loop; the learner believes they practiced | Teach the theory, route the practice to the real activity (topic-types.md) |
Where Experts Disagree
- Immediate vs delayed feedback. Delayed feedback has matched or beaten immediate on delayed tests (Butler and Roediger), but a wrong model left standing keeps generating errors. Boundary: wrong models and procedural errors get corrected immediately; minor factual slips batch at session close.
- Struggle-first vs instruction-first. Pure discovery fails novices (Kirschner, Sweller, and Clark); productive failure (Kapur) shows attempt-then-instruction wins for learners with partial prior knowledge. Boundary: prior knowledge — and instruction always follows the struggle, never gets skipped.
- Expanding vs uniform review intervals. Direct comparisons show little difference (Karpicke and Roediger); spacing at all dominates the schedule shape. Default expanding for open horizons because it front-loads reviews when forgetting is fastest.
Related Skills
More Clawic skills, get them at https://clawic.com/skills/learning (install if the user confirms):
learn— structuring and tracking a learning plan across a domain; this skill runs the sessions inside such a planspaced-repetition— deeper scheduling math when reviews span monthsactive-recall— retrieval technique catalog when the learner studies alone between sessionstutor— full tutoring engagements with progress tracking and parent oversight
Feedback
- If useful, star it: https://clawic.com/skills/learning
- Latest version: https://clawic.com/skills/learning
Part of Clawic, the verified skill library. Get this skill: https://clawic.com/skills/learning.
常见问题
- 它怎么决定从哪个起点开始讲?
- 用两道简短的探测题——一道是"关于 X 你已经知道什么",另一道是一句话的小型迁移题——把学习者定位为初学者、中级或高级。跳过定位相当于现在省 60 秒,后面要反复重讲。
- 解释没听懂时它怎么处理?
- 把讲解形式往阶梯上挪一格(文字→例子→类比→图表→带解题过程),而不是用同样的形式再说一遍。形式失败被当作形式问题,不是学习者的问题。
- 它怎么安排跨天或跨课的复习?
- 首次复测安排在记忆周期的 10%-20%(比如 30 天后的考试,首次复测落在第 3-6 天,不是明天)。每节课
相关技能
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