모든 템플릿

Faculty Perspectives on AI in Grading & Assessment

An academic research survey exploring faculty attitudes, concerns, and readiness regarding AI-assisted grading and assessment tools. Covers current practices, openness to adoption, concerns about bias/accuracy/privacy, training needs, and willingness to participate in controlled experiments.

샘플 질문

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질문 29개 · 약 12분
Q01
메시지

Thank you for your interest in this research study on faculty experiences with grading and assessment. This survey is conducted for academic research purposes. Your participation is entirely voluntary, and you may stop at any time without consequence. There are no right or wrong answers — we are interested in your honest opinions and experiences. Your responses will be kept confidential, stored securely, and reported only in aggregate. No identifying information will be linked to your individual answers. Results will be used for academic research purposes only. Estimated completion time: 12–15 minutes. By proceeding, you indicate that you have read this information and consent to participate.

Q02
객관식

Which of the following best describes your current primary role?

  • Full-time faculty (tenured or tenure-track)
  • Full-time faculty (non-tenure-track or contract)
  • Part-time or adjunct faculty
  • Graduate teaching assistant
  • Academic administrator with teaching duties
  • Research-only position (no teaching)
  • Other
Q03
객관식

Which of the following types of student assessment do you currently use in your courses? (Select all that apply)

  • Essays or written assignments
  • Multiple-choice or short-answer exams
  • Research papers or term projects
  • Lab reports or technical assignments
  • Presentations or oral exams
  • Peer assessments
  • Portfolios
  • Discussion or participation-based assessment
  • Other (please specify)
Q04
메시지

In the next section, we will ask about your views on AI-assisted grading and assessment. By "AI-assisted grading," we mean the use of artificial intelligence tools that can help evaluate student work — for example, automated scoring of written assignments, AI-generated feedback suggestions, or AI-flagged inconsistencies in grading. These tools are designed to assist faculty, not replace their judgment. Please keep this description in mind as you answer the following questions.

Q05
의견 척도

How open would you be to using AI-assisted tools as part of your grading and assessment process?

척도: 17
최소:Not at all open최대:Extremely open
Q06
의견 척도

How concerned are you that AI-assisted grading tools could introduce or perpetuate biases in student assessment?

척도: 15
최소:Not at all concerned최대:Extremely concerned
Q07
의견 척도

How concerned are you about student data privacy when student work is processed by AI-assisted grading systems?

척도: 15
최소:Not at all concerned최대:Extremely concerned
Q08
의견 척도

How prepared do you currently feel to use AI-assisted grading tools effectively?

척도: 15
최소:Not at all prepared최대:Fully prepared
Q09
메시지

Researchers are exploring the possibility of conducting controlled experiments to evaluate AI-assisted grading tools. These experiments would involve faculty volunteers grading a set of student assignments both with and without AI assistance, then comparing outcomes such as grading consistency, time spent, and student satisfaction. Participation would typically require 3–5 hours over a semester and would be compensated. All data would be anonymized.

Q10
AI 인터뷰

We'd like to understand your thinking about how AI-assisted grading might affect assessment integrity — the fairness, validity, and trustworthiness of how student learning is evaluated. In your view, what are the most important considerations when thinking about whether AI tools can uphold assessment integrity?

Q11
장문형

Based on your responses throughout this survey, please share any additional thoughts or feelings about the role of AI in grading and assessment that we may not have covered.

Q12
드롭다운

What is your primary academic discipline or field?

  • Arts & Humanities
  • Biological & Life Sciences
  • Business & Management
  • Computer Science & Information Technology
  • Education
  • Engineering
  • Health Sciences & Medicine
  • Law
  • Mathematics & Statistics
  • Physical Sciences
  • Social Sciences
  • Other (please specify)
Q13
메시지

Thank you for completing this survey. Your perspectives are valuable to understanding how AI tools may shape the future of academic assessment. Your responses have been recorded and will be kept confidential. If you have any questions about this research, please contact the research team at the email provided in your invitation. You may now close this window.

Q14
객관식

Which of the following activities are part of your current responsibilities? (Select all that apply)

  • Designing course curricula or syllabi
  • Delivering lectures or leading seminars
  • Grading or assessing student work
  • Advising or mentoring students
  • Conducting research
  • Administrative or committee duties
  • Supervising teaching assistants
Q15
객관식

During a typical teaching week, approximately how many hours do you spend grading and providing feedback on student work?

  • Fewer than 2 hours
  • 2–5 hours
  • 6–10 hours
  • 11–15 hours
  • 16–20 hours
  • More than 20 hours
Q16
의견 척도

How likely are you to adopt an AI-assisted grading tool within the next two years, assuming one were available and supported by your institution?

척도: 17
최소:Extremely unlikely최대:Extremely likely
Q17
의견 척도

How concerned are you about the accuracy of grades or feedback produced by AI-assisted tools?

척도: 15
최소:Not at all concerned최대:Extremely concerned
Q18
순위 매기기

Please rank the following data protection measures in order of importance to you if AI-assisted grading tools were used at your institution. (Drag to rank, most important first)

  1. Student work is processed on-campus servers only (no cloud processing)
  2. AI tool providers cannot retain or use student data for model training
  3. Students are informed and consent before their work is processed by AI
  4. Faculty retain full control over whether and how AI tools are used
  5. Regular third-party audits of AI tool data practices
  6. Compliance with institutional data governance policies (e.g., FERPA)
드래그하여 순위 지정
Q19
객관식

If training on AI-assisted grading tools were offered, which formats would you prefer? (Select all that apply)

  • In-person workshop (half-day or full-day)
  • Online self-paced modules
  • Live webinar or virtual workshop
  • One-on-one consultation with an instructional technologist
  • Peer mentoring from a colleague already using the tool
  • Written documentation or user guides
  • I would not be interested in training
  • Other (please specify)
Q20
의견 척도

Based on the description above, how willing would you be to participate in a controlled experiment evaluating AI-assisted grading tools?

척도: 17
최소:Not at all willing최대:Extremely willing
Q21
객관식

How many years of college or university teaching experience do you have?

  • Fewer than 3 years
  • 3–7 years
  • 8–15 years
  • 16–25 years
  • More than 25 years
Q22
의견 척도

How often do you use standardized rubrics when grading student work?

척도: 15
최소:Never최대:Always
Q23
객관식

For which of the following assessment types would you consider using AI-assisted grading? (Select all that apply)

  • Multiple-choice or short-answer exams
  • Essays or written assignments
  • Research papers or term projects
  • Lab reports or technical assignments
  • Presentations or oral exams
  • Discussion or participation-based assessment
  • Peer assessment moderation
  • I would not consider using AI-assisted grading for any of these
  • Other (please specify)
Q24
의견 척도

How concerned are you that AI-assisted grading could reduce the personal connection between faculty and students in the feedback process?

척도: 15
최소:Not at all concerned최대:Extremely concerned
Q25
객관식

How many hours of training would you be willing to invest to learn to use an AI-assisted grading tool effectively?

  • None — I would not invest time in training
  • 1–2 hours
  • 3–5 hours
  • 6–10 hours
  • More than 10 hours
Q26
객관식

What would be your primary reason for participating or not participating in such an experiment?

  • Curiosity about how AI tools perform in grading
  • Desire to contribute to evidence-based research on teaching
  • Interest in improving my own grading efficiency
  • Concern about the time commitment required
  • Skepticism about AI's role in assessment
  • Discomfort with being evaluated or observed
  • Privacy or ethical concerns about the research design
  • Other (please specify)
Q27
객관식

Which best describes your institution?

  • Research university (R1/R2 or equivalent)
  • Comprehensive or master's-granting university
  • Liberal arts college
  • Community or two-year college
  • Professional or specialized institution
  • Other (please specify)
Q28
의견 척도

Overall, how satisfied are you with your current grading and assessment process?

척도: 17
최소:Not at all satisfied최대:Extremely satisfied
Q29
객관식

What is the typical enrollment size of the courses you teach?

  • Fewer than 20 students
  • 20–50 students
  • 51–100 students
  • 101–200 students
  • More than 200 students

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 a dedicated adaptive AI follow-up interview that probes faculty's own reasoning about how AI-assisted grading might affect their teaching relationships, going beyond fixed-choice questions
  • Separates concerns into distinct scaled items for bias, accuracy, loss of personal connection, and student data privacy, rather than one generic 'AI concerns' question
  • Captures actionable readiness signals: preferred training formats, hours willing to invest, and willingness to join a controlled grading experiment, plus a ranking of data protection priorities
  • Closes with an open-text reflection and discipline/experience/institution-size demographics, enabling segmented reporting on faculty AI grading attitudes

SurveyMonkey

AI Readiness Assessment Template

This is a general-purpose AI readiness template aimed at organizations assessing AI adoption broadly, not one built for academic faculty or grading/assessment contexts specifically. It's a fielding-ready static form on an established survey platform, useful as a generic AI-attitudes starting point but not tailored to higher-ed grading concerns. Researchers would need to heavily customize it to cover rubric use, bias-in-grading, or controlled experiment participation.

잘하는 점

  • Backed by a widely-used, established survey platform with broad distribution and analytics tools
  • Provides a ready-made framework for gauging general AI adoption attitudes
  • Likely offers standard reporting/benchmarking features typical of SurveyMonkey templates

아쉬운 점

  • Static question set with no adaptive AI follow-up probing into individual faculty reasoning
  • Generic organizational AI-readiness focus, not tailored to academic grading, rubrics, or bias-in-assessment concerns
  • No voice AI interview option, per-response quality scoring, or published prompt-level methodology

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