모든 템플릿

Campus Climate, Belonging, and Inclusion Survey

Measures students' sense of belonging, perceived fairness and safety, and firsthand experiences with exclusionary or discriminatory treatment on campus. Built for institutional research and DEI offices, with an AI follow-up interview that reconstructs the specific incident or context behind a student's belonging score instead of leaving it as an abstract number.

샘플 질문

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

질문 14개 · 약 7분
Q01
메시지

Thanks for taking a few minutes to share how campus feels for you. Your answers help shape decisions about inclusion, safety, and support services — everything here is confidential. About 6-7 minutes.

Q02
의견 척도필수

Overall, how strongly do you feel you belong at (Replace with institution name)?

척도: 17
최소:Not at all최대:Extremely strongly
Q03
매트릭스필수

How much do you agree or disagree with each statement about campus climate?

5개 행 × 5개 열
  • Students of different backgrounds are treated with respect here
  • Faculty and staff create an inclusive learning environment in my classes
  • I feel physically safe on campus, including at night
  • Campus policies and discipline are applied fairly regardless of a student's background
  • I would recommend this campus's environment to a prospective student like me
: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q04
객관식필수

In the last 12 months, how often have you personally experienced exclusionary, disrespectful, or discriminatory treatment on campus?

  • Never
  • Once
  • A few times
  • Regularly
Q05
객관식

In the last 12 months, how often have you witnessed someone else experience this kind of treatment on campus?

  • Never
  • Once
  • A few times
  • Regularly
  • Not sure
Q06
의견 척도필수

If you experienced or witnessed a climate concern, how comfortable would you be reporting it to the university?

척도: 15
최소:Very uncomfortable최대:Very comfortable
Q07
최선·최악 선택형(MaxDiff)필수

Which of these should the university prioritize improving first? Pick the one that matters most and the one that matters least each round.

  • More diverse faculty and staff
  • A clearer, easier process for reporting incidents
  • Mandatory bystander/allyship training
  • More inclusive course content and assignments
  • Better lighting and security across campus
  • More funding for identity-based student organizations
  • Faster, more visible follow-up after a concern is reported
세트별 최선·최악 선택최선:Improve first최악:Improve last
Q08
객관식

Which of these campus resources have you used in the past year?

  • Counseling or mental health services
  • Diversity & inclusion office
  • Student advocacy or ombuds office
  • Bias incident reporting system
  • Peer support or affinity group
Q09
AI 인터뷰

Ground the respondent's belonging score and reporting-comfort answer in a real, specific situation: what happened, who was involved, and what shaped how included or excluded they felt. If they reported experiencing or witnessing exclusionary treatment, gently probe what happened, whether they reported it, and why or why not. If their belonging score was high, probe what specifically makes campus feel that way so it can be replicated elsewhere.

Q10
메시지

Almost done — just a few quick background questions to help us see patterns across student groups. Feel free to skip any of these.

Q11
객관식

What is your current academic level?

  • First-year undergraduate
  • Sophomore
  • Junior
  • Senior
  • Graduate or professional student
  • Other
  • Prefer not to say
Q12
객관식

How do you describe your gender identity?

  • Woman
  • Man
  • Non-binary
  • Prefer to self-describe
  • Prefer not to say
Q13
객관식

How do you describe your race or ethnicity? Select all that apply.

  • American Indian or Alaska Native
  • Asian
  • Black or African American
  • Hispanic or Latino/a/x
  • Middle Eastern or North African
  • Native Hawaiian or Pacific Islander
  • White
  • Prefer not to say
Q14
메시지

Thank you for your honesty. Your responses are combined with others across campus to inform belonging, safety, and inclusion initiatives — no individual answers are shared with instructors or advisors.

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

  • Goes beyond a belonging score with an AI follow-up interview that asks respondents to reconstruct the actual incident or context behind a low belonging or reporting-comfort answer, giving DEI offices a real narrative instead of a number
  • Pairs quantitative measures (opinion-scale belonging score, climate agreement matrix, frequency-of-experience and witnessing questions, MaxDiff prioritization, resource-usage checklist) with qualitative depth in one flow
  • Uses transparent, reviewable AI prompts and automated per-response quality scoring, so IR and DEI teams can audit exactly what was asked and how responses were graded
  • Auto-generates a report from combined structured and interview data, with a free tier available and a $50/mo Business plan for full institutional use — no separate academic tier is offered

Jotform

Campus Climate Survey Form Template

A ready-to-field, drag-and-drop form covering standard campus climate questions. It's built on Jotform's general form platform, so customization and distribution are easy, but the questionnaire itself is static and generic rather than purpose-built for DEI/IR incident analysis.

잘하는 점

  • Quick to deploy and customize via a familiar drag-and-drop form builder
  • Benefits from Jotform's broad integration and distribution ecosystem

아쉬운 점

  • Static question set with no adaptive follow-up to probe individual responses further
  • No mechanism to reconstruct the specific incident behind a low score — respondents choose from fixed options only

QuestionPro

Campus Climate Survey Questions + Sample Questionnaire Template

This page reads more as a question bank and sample questionnaire guide than a single fielding-ready survey, offering example items researchers can copy into their own instrument. It's a useful reference for question design but leaves assembly and logic-building to the user.

잘하는 점

  • Broad library of sample question wording researchers can borrow from
  • Backed by an established enterprise survey platform with analytics tools

아쉬운 점

  • Presented as a sample/guide rather than a ready-to-send template, requiring manual assembly
  • No adaptive or voice AI interview component to follow up on individual open-ended answers

SurveyMonkey

Belonging And Inclusion Survey Template

A polished, ready-to-send template focused specifically on belonging and inclusion, backed by a well-known survey platform with strong distribution and reporting tools. Like most SurveyMonkey templates, it relies on fixed-choice and rating items without any conversational follow-up.

잘하는 점

  • Purpose-built belonging/inclusion focus with clean, tested question flow
  • Reliable distribution, panel, and basic analytics tools from an established platform

아쉬운 점

  • No adaptive AI or voice interview to dig into the context behind a belonging score
  • No published methodology for how underlying question logic or scoring works

SurveySparrow

Free School Climate Survey Template | For Students

A free, conversational-style template covering general school climate themes; it's framed around students broadly and school settings rather than specifically higher-education campus climate or DEI reporting workflows. Useful as a lightweight starting point, but not tailored to institutional research needs.

잘하는 점

  • Chat-style, student-friendly survey format that may improve completion rates
  • Free to use as a starting template

아쉬운 점

  • Oriented toward general school climate rather than campus-specific belonging, fairness, and discrimination reporting
  • No adaptive AI follow-up to reconstruct incidents behind low scores, and no automated quality scoring of responses

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