모든 템플릿

Open Source Contributor Experience & Governance Survey

Measures contribution path clarity, governance transparency, maintainer responsiveness, and improvement priorities for open-source projects. Designed for project maintainers seeking to improve contributor satisfaction and retention.

샘플 질문

템플릿에 포함된 내용을 미리 확인해 보세요. 모든 질문은 설문 공개 전에 자유롭게 수정할 수 있습니다.

질문 18개 · 약 9분
Q01
메시지

Welcome to the Open Source Contributor Experience Survey. This survey takes approximately 9 minutes to complete. Your responses are completely anonymous and will be reported only in aggregate to help improve the contributor experience for this project. Participation is voluntary, there are no right or wrong answers, and you may stop at any time. By proceeding, you consent to participate.

Q02
객관식

Which of the following best describes your current relationship to this project?

  • Maintainer
  • Regular contributor
  • Occasional contributor
  • New contributor
  • User only (no contributions yet)
Q03
의견 척도

How clear are the contribution entry points (e.g., documentation, labeled issues, getting-started guides) for this project?

척도: 17
최소:Very unclear최대:Very clear
Q04
객관식

Which of the following governance elements are clear to you for this project? (Select all that apply.)

  • Roadmap and project direction
  • Decision-making process
  • Release process and cadence
  • Code of Conduct enforcement
  • Maintainer roles and permissions
  • Project ownership or legal entity
  • None of the above
Q05
객관식

For your most recent contribution, how long did it take to receive an initial response from a maintainer?

  • Within 24 hours
  • 2–3 days
  • 4–7 days
  • 8–14 days
  • More than 14 days
  • No response yet
  • Not applicable
Q06
순위 매기기

Please rank the following areas by how much they need improvement for this project, with the most important at the top.

  1. Contribution documentation
  2. Issue triage speed
  3. Code review throughput
  4. Decision-making transparency
  5. Roadmap visibility
  6. New contributor onboarding
드래그하여 순위 지정
Q07
장문형

Based on your responses in this survey, is there anything else you would like to share about your experience contributing to this project?

Q08
객관식

How long have you been involved with this project?

  • Less than 3 months
  • 3–12 months
  • 1–2 years
  • 3 or more years
Q09
메시지

Thank you for your time and insights! Your feedback will be used to improve the contributor experience for everyone involved in this project.

Q10
객관식

In the past 12 months, how often have you contributed to this project?

  • Weekly or more
  • 2–3 times per month
  • About once per month
  • A few times this year
  • Once in the last year
  • Not in the last 12 months
Q11
장문형

What, if anything, slows you down when contributing to this project?

Q12
의견 척도

How transparent has project decision-making been in the last 6 months?

척도: 17
최소:Not at all transparent최대:Extremely transparent
Q13
의견 척도

How would you rate the quality of code review feedback you received on pull requests in the last 6 months?

척도: 17
최소:Very poor최대:Excellent
Q14
AI 인터뷰

We'd like to learn a bit more about your contributor experience. An AI moderator will ask you a couple of brief follow-up questions.

Q15
드롭다운

In which region do you primarily reside?

  • Africa
  • Asia
  • Europe
  • Latin America
  • North America
  • Oceania
  • Prefer not to say
Q16
의견 척도

In the last 6 months, how often were contributors invited to provide input on project decisions (e.g., roadmap priorities, release plans, policy changes)?

척도: 17
최소:Never최대:Very frequently
Q17
의견 척도

How accessible have maintainers been on project communication channels (e.g., chat, forums, issue trackers) in the last 6 months?

척도: 17
최소:Not at all accessible최대:Extremely accessible
Q18
의견 척도

Overall, how satisfied are you with maintainer responsiveness in the last 6 months?

척도: 17
최소:Very dissatisfied최대:Very satisfied

포함된 기능

  • AI 후속 질문

    정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.

  • 주의력 확인 장치

    성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.

  • AI가 작성한 문안

    문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.

  • 자동 리포트

    응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

  • Includes dedicated governance-transparency items (decision-making transparency, contributor input opportunities) rather than generic project-satisfaction questions.
  • Pairs closed-ended opinion scales with an open-text question on what specifically slows down contributions, plus a final open-text catch-all for anything unaddressed.
  • Includes a ranking question so maintainers get a prioritized list of improvement areas (e.g., documentation, review quality, responsiveness) instead of a flat satisfaction score.
  • Adds an AI follow-up interview segment where an AI moderator can probe deeper into a contributor's experience, and every response is automatically quality-scored and rolled into an auto-generated report.

SurveySparrow

Project Satisfaction Survey Template

This is a general-purpose project satisfaction template aimed at client/stakeholder or team-project feedback, not open-source contributor or governance dynamics specifically. It's a fielding-ready static form that a maintainer could adapt, but none of its questions address contribution entry points, governance transparency, or maintainer responsiveness out of the box. Useful mainly as a generic satisfaction baseline rather than a purpose-built open-source community survey.

잘하는 점

  • Ready-to-deploy template with SurveySparrow's conversational, mobile-friendly survey format
  • Broad applicability across any 'project' context, so it's quick to launch with minimal customization
  • Likely supports standard question types (rating scales, open text) for basic satisfaction tracking

아쉬운 점

  • Static question set with no adaptive AI follow-up probing into individual contributor answers
  • No open-source-specific coverage of governance transparency, contribution entry-point clarity, or maintainer responsiveness
  • No voice AI interview option or automated per-response quality scoring/report generation

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