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[curriculum-eval] 05-agentic-workflows-intro.md: active_learning — predict-then-reveal pattern missing for key-terms table

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评估

难度
1/5
预计耗时
1 小时以内
新手友好度
88/100
Issue 类型
文档
描述清晰度
描述清楚
活跃度
活跃
技术栈
github-actions, markdown
领域
content, documentation

调研方向

编辑 workshop/05-agentic-workflows-intro.md。阅读“The two-file structure”之前现有的 predict-then-reveal prompt 和附近的“Three key terms”表格，然后在表格之前添加一个可比的 prompt。运行 npx --yes markdownlint-cli2 "**/*.md"；当新 prompt 已存在、与页面的活动和 checkpoint 一致，并且 lint 通过时，即表示完成。

由索引模型根据 Issue 内容生成。

描述

curriculum documentation quality

File: workshop/05-agentic-workflows-intro.md
Overall Score: 5.4 / 10.0 (corpus mean: 6.1)

Flagged Dimensions:

Dimension Score Benchmark Delta
active_learning 2.4 ≥ activity density 3 (score 10) -7.6
cognitive_load 8.5 ≤ 800 words / ≤ 15 new concepts (score 10) -1.5

Note: the rubric also flags missing_checkpoint, but this is a confirmed tooling bug (see scorecard issue) — the file has a well-formed ## :white_check_mark: Checkpoint with 6 specific checklist items plus a collapsible self-test. Dismissed.

Root Cause (≤ 2 sentences):
This page is the conceptual introduction to agentic workflows (1,107 words, 15 new concepts — near the ideal ceiling) but has only 0.72 activity density: two conceptual diagrams and three named "Activity" sections are described, yet the ratio of code blocks + checklist items to word count is low because most of the content is narrative explanation of the trigger/task-brief/safe-outputs model. The three labeled "Activity" sections (predict-the-answer, classify, write) are good active-learning design, but they're spread thin across a long conceptual narrative, diluting density.

Evidence (quoted from the file):

An Agentic Workflow is a plain-English task brief that an AI agent executes inside GitHub Actions. You write what you want — "summarize open issues and post a daily digest" — and the agent reads your repo, calls tools, and posts the output automatically.

Learning Science Rationale:
Mayer's multimedia principle on generative activity indicates that pairing conceptual diagrams with an explicit retrieval prompt increases retention over passive diagram viewing alone. Here, "The two-file structure" section does ask learners to predict which file GitHub Actions actually runs before showing the diagram — a good technique — but this pattern is not repeated for the "Three key terms" table, missing a low-cost opportunity to convert more of the page's prose into active recall.

Improvement Prompt (for an agent):

Edit workshop/05-agentic-workflows-intro.md to raise activity density by adding one short predict-then-reveal prompt before the "Three key terms" table, similar to the existing "write your prediction" pattern used before "The two-file structure" diagram (e.g., "Before reading the table below, guess: which of trigger, task brief, or safe outputs controls how the workflow writes back to GitHub?"). Keep this consistent with the page's existing three "Activity" sections and its checkpoint. Run npx --yes markdownlint-cli2 "**/*.md" after editing.

Expected Score After Fix: 6.0 / 10.0

Generated by 🔬 Curriculum Quality Evaluator · copilot · auto · 74.5 AIC · ⌖ 11.9 AIC · ⊞ 9K · ◷

  • expires on Sep 23, 2026, 3:48 AM UTC
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