try-first-tell-later_skill

This skill helps you design educational materials using try-first-tell-later pedagogy to boost active learning and diagnostic insight.
  • Python

1

GitHub Stars

2

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill dbosk/claude-skills --skill try-first-tell-later

  • LICENSE.md1.0 KB
  • SKILL.md15.5 KB

Overview

This skill structures educational content using the try-first-tell-later pedagogy to make learners predict, attempt, or reflect before receiving explanations. It creates active learning by triggering cognitive engagement, diagnostic insight, and contrast patterns that reveal critical aspects of a topic. Use it to design prompts, exercises, lecture notes, or problem sets that prioritize discovery before exposition.

How this skill works

The skill generates try-first prompts (prediction, design, reasoning, comparison, reflection, experimentation) placed before explanations or solutions. Prompts act as diagnostic pre-tests: learner responses reveal which critical aspects they already discern and which require targeted variation patterns. After learner attempts, the skill provides concise expert explanations and explicit contrast statements that highlight what matters and why.

When to use it

  • When drafting educational materials that should encourage prediction or productive failure
  • Designing exercises, problem sets, or lecture notes that scaffold discovery
  • Creating LaTeX/Beamer teaching slides or examples with embedded try-first prompts
  • When you want to diagnose student misconceptions before teaching a concept
  • When building activity sequences that move from recognition → exploration → implementation → understanding

Best practices

  • Keep try-first prompts specific enough to guide thinking but avoid revealing critical aspects
  • Use short exercises (1–2 minutes) for quick discovery and longer activities for hands-on exploration
  • Always follow prompts with clear explanations and explicit contrast to students' likely responses
  • Use layered sequences: recognition, exploration, implementation, then understanding
  • Design prompts to surface diagnostic information you can target with variation patterns

Example use cases

  • Lecture slide that shows a concrete example, asks a discovery question, then contrasts the canonical solution
  • Problem set where each question asks students to predict or design before seeing model answers
  • Beamer slides using exercise blocks to make students guess syntax or behavior before presenting code and rationale
  • A post-lecture diagnostic pre-test that reveals which critical aspects students miss and guides follow-up instruction
  • Activity prompts that require coding experiments, then structured reflection comparing outcomes to predictions

FAQ

Use try-first only when learners have some relevant prior knowledge; for completely novel facts, supply scaffolding or a brief orienting explanation first.

How many try-first prompts are appropriate per lesson?

Limit prompts so they remain productive—mix short exercises for activation with a few deeper activities; avoid overload and ensure timely follow-through explanations.

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