Skip to main content

design-a-research-method

Design a research method that aligns the question, evidence, sampling, measurement, analysis, feasibility, and limitations. Use when turning a research question into an empirical or analytical study.

ソース情報

リポジトリ
protosphinx/sphinxstack
ソースの最終更新活動
2026年7月29日 13:55
検出された SKILL.md の言語
英語
スター
3
フォーク
0

インストール方法

デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。

ソースファイルを確認

インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。

ファイルエクスプローラー
2 ファイル

SKILL.md を表示中

SKILL.md
ソースの指示 · 読み取り専用プレビュー
name
design-a-research-method
category
school
description
Design a research method that aligns the question, evidence, sampling, measurement, analysis, feasibility, and limitations. Use when turning a research question into an empirical or analytical study.
# design-a-research-method Choose the least burdensome method capable of answering the bounded question. ## When to use - Use for observational, experimental, qualitative, quantitative, mixed, archival, computational, or design research. - Do not begin collection involving people, sensitive data, hazards, or protected sites before required approval. ## Procedure 1. State the question, target population or system, unit of analysis, concepts, and decision the evidence should inform. 2. Define the claim type: descriptive, comparative, relational, causal, predictive, interpretive, or methodological. 3. Map each concept to observable evidence and identify likely confounders, biases, and alternative explanations. 4. Compare candidate designs for validity, ethics, burden, access, cost, timing, and analytic fit. 5. Select sampling or case-selection logic, inclusion and exclusion rules, comparison conditions, and stopping criteria. 6. Specify measures, instruments, procedures, timing, quality controls, and pilot tests. 7. Predefine analysis, missing-data treatment, uncertainty, subgroup logic, and sensitivity checks where appropriate. 8. Plan consent, privacy, safety, data governance, accessibility, and researcher positionality. 9. Run a feasibility pilot without using unapproved pilot data as final evidence. 10. Document limitations and the claims the design cannot support. ## Worked example A project asks whether a tutoring program improves grades. The method distinguishes a causal question from a satisfaction survey, identifies selection bias, and compares randomized, matched, and interrupted-time designs. Constraints lead to a prospective matched design with preregistered outcomes and explicit residual limitations. ## Done - A method design document links question, claim type, sampling, measures, procedure, analysis, governance, and feasibility - A design review verifies that planned evidence supports only the stated claims and records unresolved bias plus required approvals
GitHubで見る