Design pre-class, in-class, and follow-up practice

작성자: AILesson9 분 소요검토일: 2026-08-29

빠른 답변

Sequence preparation, guided application, feedback, and later retrieval around one learning target. 제공할 내용: Learning target and evidence, Learners and access, Course constraints. 예상 결과: A three-phase practice sequence with workload, feedback, access, and completion evidence.

맥락 추가

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Learning target and evidenceLearners and accessCourse constraints

프롬프트

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Design connected pre-class, in-class, and follow-up practice for one learning target.

Objective, success criteria, prior evidence, misconceptions, and transfer:
[target]

Level, group size, language, accessibility, device or home access, workload, and safeguarding:
[learners]

Class time, pre/follow-up time, materials, feedback capacity, grading, deadlines, and alternatives:
[course]

Give each phase a distinct function. Pre-class should activate or diagnose prerequisites without making unequal home access determine success. In class, use the evidence to model, practise, receive feedback, and attempt again. Follow-up should retrieve or transfer the same target, not introduce unsupported new content. Keep total workload within supplied limits and provide equivalent access routes. Do not invent completion data or assume non-completion means low motivation. Return phase map, learner instructions, time budget, evidence flow, feedback route, access alternatives, non-completion response, and instructor review triggers.

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입력에서 결과까지

적용 예시

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실제 입력

Learning target and evidence: Introductory statistics. Target: choose mean or median for a supplied dataset and justify with distribution/extreme-value evidence. Success: correct calculation and conditional justification. Prior work shows many learners say median is always better when an outlier exists.
Learners and access: 24 adult learners. Some have phone access but home internet cannot be assumed. Printed alternative required. Calculators available in class. No personal financial disclosure.
Course constraints: 60-minute class. Pre-class maximum 10 minutes, ungraded diagnostic. Follow-up maximum 15 minutes due in three days, low stakes. Teacher can give whole-class and checklist feedback, not individual written comments to all.

예시 출력

Pre-class, 8–10 minutes: paper or downloadable-identical sheet with two small datasets. Learners calculate mean/median, choose one for 'typical', and tick a reason. Purpose: diagnose procedure versus conditional-choice gaps. Non-completion is Unknown, not low motivation; provide the same two questions in the first five class minutes.

In class, 60 minutes: 0–5 access/diagnostic completion; 5–12 anonymous response pattern and model of one calculation; 12–22 contrast two datasets where an extreme is a valid observation versus a suspected entry error; 22–34 pairs calculate and justify using a four-item checklist; 34–41 whole-class feedback on the 'always median' misconception; 41–50 learners revise the same justification; 50–57 unseen individual choice; 57–60 exit reason. Evidence flows from diagnostic grouping of needs to model emphasis, then from checklist feedback to revision.

Follow-up, 12–15 minutes: one new non-personal dataset; calculate both measures, choose conditionally, state one limitation, then self-check against the same checklist. Paper and digital versions are identical. Instructor trigger: if more than one-third still use an unconditional rule, begin next class with a new contrast case rather than adding harder calculations.

효과가 있는 이유

1
Distinct phase functions prevent homework, classwork, and follow-up from repeating the same low-value task.
2
Evidence flow lets each phase change what happens next instead of being an isolated activity.

결과 확인

Does each phase serve a different but connected learning function?
Can learners without assumed home technology access an equivalent route?
Does feedback lead to another attempt on the same target?

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자주 묻는 질문

이 레시피를 언제 사용해야 하는지, 무엇을 제공해야 하는지, 그리고 어떤 부분에서 사람의 검토가 여전히 중요한지에 대한 실용적인 답변

What should I prepare before using “Design pre-class, in-class, and follow-up practice”?

For “Design pre-class, in-class, and follow-up practice,” prepare Learning target and evidence, Learners and access, and Course constraints. Replace placeholders only with information you can verify. If a detail is unknown, preserve that uncertainty explicitly instead of asking the model to infer it.

When is the “Design pre-class, in-class, and follow-up practice” result not ready to use?

The result is not ready if it does not yet deliver the stated outcome—A three-phase practice sequence with workload, feedback, access, and completion evidence—from the supplied evidence, or if it relies on unresolved assumptions, missing approvals, or invented details. Use the checks as release gates: revise the source inputs or assign a named, authorized reviewer instead of polishing an unsupported output.

Which AI tools have recorded tests for “Design pre-class, in-class, and follow-up practice”?

No model run is recorded for “Design pre-class, in-class, and follow-up practice” as of 2026-08-29. Treat it as a model-portable template rather than a compatibility claim. Run the worked example first, keep every constraint visible, and compare the output with the result checks before using it on real material.

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