모든 템플릿

AI Lesson Planning & Grading: Teacher Workload Impact

Measures whether AI lesson-planning and grading tools are actually reducing teacher workload, which tasks see the biggest time savings, and how much teachers trust the output. Built for school and district leaders evaluating AI tool adoption, with an AI follow-up interview that reconstructs a real week to separate genuine time savings from hidden re-work.

샘플 질문

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질문 14개 · 약 7분
Q01
메시지

Thanks for taking a few minutes for this! We're trying to understand how AI tools for lesson planning and grading are actually affecting your workload — the good, the messy, and the in-between. Your responses are completely confidential and anonymized. About 8 minutes, and there are no wrong answers.

Q02
객관식필수

Which types of AI tools have you used for lesson planning or grading in the last month?

  • AI lesson planning assistant (e.g., MagicSchool, Diffit)
  • AI grading or feedback tool (e.g., Grade genie, Turnitin AI)
  • AI rubric or differentiation generator
  • General AI chatbot used for drafting materials (e.g., ChatGPT, Claude) (Template note: replace these tool examples with the ones your staff actually use)
  • Something else
Q03
의견 척도필수

Overall, how much have AI tools reduced your weekly workload for lesson planning and grading?

척도: 17
최소:No reduction at all최대:Major reduction
Q04
숫자

About how many hours per week do these AI tools save you, compared to doing the same work without them?

Q05
점수 배분필수

Thinking about where AI actually saves you time, split 100 points across these tasks based on how much of the time savings comes from each.

  • Lesson planning
  • Grading and feedback
  • Differentiating materials for different students
  • Parent or student communication
  • Administrative paperwork
100점 배분
Q06
매트릭스필수

How much do you agree with each statement about the AI tools you use?

4개 행 × 5개 열
  • The AI-generated lesson plans align well with my curriculum standards
  • The AI-generated feedback on student work is accurate
  • I have to significantly edit AI output before I can use it
  • I trust AI grading enough to use it on graded, not just practice, assignments
: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q07
최선·최악 선택형(MaxDiff)필수

Which of these tasks would benefit most from additional AI support?

  • Drafting initial lesson plans
  • Creating differentiated materials for different skill levels
  • Grading multiple-choice or short-answer assessments
  • Writing narrative feedback on essays or open-ended work
  • Generating quiz and test questions
  • Translating materials for multilingual families
  • Flagging students who need extra help based on their work
  • Handling routine parent emails
세트별 최선·최악 선택최선:Would help most최악:Would help least
Q08
평점 척도필수

Overall, how would you rate the quality of the lesson plans or feedback AI tools generate for you?

범위: 15
최소:Poor, needs heavy editing최대:Excellent, ready to use
Q09
AI 인터뷰

Anchor on the respondent's workload-reduction rating and their trust-in-grading answer. Ask them to walk through one specific recent week: which task actually got faster because of AI, and where AI created extra work, like double-checking or fixing errors. If their workload-reduction rating was low, probe what's blocking bigger savings — tool limitations, school policy, or lack of trust. If they said they trust AI for graded work, ask what safeguards they use before finalizing a grade.

Q10
객관식

What has gotten in the way of using AI tools more for lesson planning or grading?

  • School or district policy restrictions
  • Concerns about accuracy or bias in the output
  • Cost of tools not covered by my school
  • Lack of training on how to use them well
  • Concerns about student academic integrity
  • I don't see enough time savings to bother
  • Nothing — I use them as much as I want to
Q11
객관식

What subject area do you primarily teach?

  • English / Language Arts
  • Math
  • Science
  • Social Studies
  • Elective or special subject
  • Multiple subjects
  • Prefer not to say
Q12
객관식

What grade level do you primarily teach?

  • Elementary (K-5)
  • Middle school (6-8)
  • High school (9-12)
  • Multiple levels
  • Prefer not to say
Q13
객관식

How many years have you been teaching?

  • Less than 3 years
  • 3-9 years
  • 10-19 years
  • 20+ years
  • Prefer not to say
Q14
메시지

That's everything — thank you for the honest answers. Your responses will help school leaders decide which AI tools are worth keeping, dropping, or getting more training on.

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.

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이 템플릿을 선택하는 이유

  • Includes an AI follow-up interview that reconstructs a respondent's actual week to distinguish genuine time savings from hidden re-work, rather than relying on self-reported estimates alone
  • Uses a constant-sum question to force teachers to allocate where AI actually saves time across specific tasks, plus a max-diff ranking of which tasks most need more AI support
  • Combines a numeric estimate of hours saved with a matrix of trust/agreement statements and a rating of output quality, giving leaders both quantitative and attitudinal signal on AI grading tools
  • Captures teaching context (subject, grade level, years teaching) and barriers to adoption so district leaders can segment results by who benefits most and what's blocking wider use

QuestionPro

Course evaluation sample questions and survey template

This is a general course/teacher evaluation template aimed at gathering student feedback on instruction quality, not an AI-tool workload or adoption survey. It's a fielding-ready static template within the same broad education-survey space, but its questions don't touch AI lesson-planning or grading tools at all. Useful mainly as a point of comparison for general survey design quality in education, not as a direct substitute.

잘하는 점

  • Established, education-specific survey template library
  • Likely covers standard course/instructor evaluation dimensions (clarity, engagement, fairness) educators expect
  • Backed by a broader survey platform with reporting and analytics features

아쉬운 점

  • No adaptive AI follow-up interview to probe individual responses or reconstruct actual behavior/time use
  • Not designed to measure AI tool adoption, time savings, or trust in AI-generated output — different subject matter entirely
  • As a static form, cannot distinguish self-reported perception from verified real-world workload impact the way a reconstructed-week interview can

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