QuestionPunkQuestionPunk
無料で始める
すべてのテンプレート
Industry-Specific

Post-Lecture Feedback & Teaching Quality Survey

Captures how clear, well-paced, and engaging a lecture was, plus which specific aspects (pacing, examples, Q&A, materials) students most want improved. An AI follow-up interview digs into a concrete moment the student found confusing or engaging, turning vague 'it was fine' ratings into specifics an instructor can act on.

このテンプレートを使うほかのテンプレートを見る

設問の例

テンプレートの内容をプレビューできます。すべての設問は公開前に自由に編集できます。

全11問・約6分
Q01
メッセージ

Hi! We'd love your honest feedback on the lecture you just attended (or watched). Your responses are completely confidential and anonymized. It takes about 7 minutes and helps the instructor improve future sessions.

Q02
選択式必須

In the past month, how many of this course's lectures have you attended in person or watched live?

  • All of them
  • Most of them
  • About half
  • A few
  • None
Q03
オピニオンスケール必須

How likely are you to recommend this lecture to a classmate who's deciding whether to attend?

スケール: 0 – 10
最小:Not at all likely最大:Extremely likely
Q04
マトリクス必須

How much do you agree with each statement about this lecture?

5行 × 5列
  • The pace of the lecture was appropriate
  • The instructor explained concepts clearly
  • The examples used helped my understanding
  • The slides or visual materials supported learning
  • The instructor encouraged questions and discussion
列: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q05
評価スケール

How would you rate the instructor's responsiveness when you asked questions during or after the lecture?

範囲: 1 – 5
最小:Poor最大:Excellent
Q06
ベスト・ワースト選択（MaxDiff）必須

If the instructor could only change a few things about this lecture, which would matter most to you?

  • More real-world examples
  • More time for questions and discussion
  • Clearer explanations of core concepts
  • Better structured or paced content
  • More engaging delivery style
  • Improved slides or visual aids
  • More opportunities for hands-on practice
各セットで最も良いもの・最も悪いものを選択最も良い:Would improve the lecture most最も悪い:Would improve the lecture least
Q07
AIインタビュー

Ask the respondent to describe a specific moment in the lecture where they felt most engaged or most lost, anchoring on whichever statement they rated lowest in the pacing/clarity/examples battery. Get concrete detail: what was being explained at that point, what confused them or made it click, and what the instructor could have done differently right there. If they flagged a top improvement area in the trade-off question, ask them to describe what a fixed version of that lecture would actually look like.

Q08
自由回答（長文）

Is there anything else about this lecture you'd like to share with the instructor or course organizers?

Q09
選択式

What is your current year or level of study?

  • First year
  • Second year
  • Third year
  • Fourth year or above
  • Graduate student
  • Prefer not to say
Q10
選択式

What is your field of study or department? (Template note: replace the list below with your institution's actual departments before launching.)

  • (Replace with Department A)
  • (Replace with Department B)
  • (Replace with Department C)
  • Other
  • Prefer not to say
Q11
メッセージ

Thanks so much for the feedback! Your responses are combined with other students' answers into a summary report the instructor uses to improve future lectures — individual answers are never shared with a name attached.

含まれる機能

  • AIによる深掘り

    自由回答に合わせてAIが追加で質問し、固定のフォームでは拾えない具体的な内容を引き出します。

  • 注意確認設問

    急いだ回答や質の低い回答者を除外する仕組みを標準で備えています。

  • AIが作成する設問文

    文言、設問の順序、条件分岐をAIが調査の目的に合わせて作成します。

  • 自動レポート

    回答が集まると、テーマ、引用、わかりやすい要約が自動で作成されます。

他ツールとの比較

ほかのアンケートツールで最も近いテンプレートを調べました。それぞれの優れている点と、このテンプレートがさらに踏み込んでいる点をまとめています。

このテンプレートを選ぶ理由

  • Combines quick quantitative pulses (pacing/clarity opinion scale, agreement matrix, instructor responsiveness rating) with a max-diff question that forces students to prioritize which single change matters most
  • Includes an AI follow-up interview that asks the student to describe one specific confusing or engaging moment, turning generic 'it was fine' answers into concrete, actionable detail for the instructor
  • Bookends the survey with friendly chat-style intro/outro messages and closes with an open long-text field so students can add anything the structured questions missed
  • Captures context (attendance frequency, year of study, field/department) so instructors can see if feedback patterns differ by student segment

SurveyMonkey

Teaching Assistant Evaluation: TA Survey Examples

This is a ready-to-use template on an established survey platform, aimed at evaluating teaching assistants rather than lecture-specific instructor performance, so it's a related but not identical use case. It likely covers standard rating and open-text questions typical of SurveyMonkey's education templates, with the platform's usual reporting and distribution tools. No AI-driven probing or per-response scoring is part of the offering.

優れている点

  • Backed by a well-known, mature survey platform with broad distribution and analytics tooling
  • Purpose-built for academic/teaching evaluation context, so question framing is likely relevant to instructors
  • Ready to deploy without configuration, useful for a quick baseline TA evaluation

物足りない点

  • Static question set with no adaptive AI follow-up to probe vague answers like 'it was fine'
  • No voice AI interview option or guided screen-share tasks
  • No transparent, published prompt/methodology for how responses are interpreted or scored

よくあるご質問

「Post-Lecture Feedback & Teaching Quality Survey」テンプレートにはどのような設問が含まれていますか？

すぐに使える設問が11問含まれており、最初の設問は次のとおりです：「Hi! We'd love your honest feedback on the lecture you just attended (or watched). Your responses are completely confiden…」・「In the past month, how many of this course's lectures have you attended in person or watched live?」・「How likely are you to recommend this lecture to a classmate who's deciding whether to attend?」。すべての設問は上でプレビューでき、自由に編集できます。

このアンケートの回答にはどのくらい時間がかかりますか？

回答者は通常、11問を約6分で回答し終えます。

テンプレートは編集できますか？

はい。公開前であれば、すべての設問、選択肢、順序を編集できます。設問の追加や削除のほか、調査の目的に合わせた作り直しをAIエディターに依頼することもできます。

このテンプレートは無料で使えますか？

はい。エディターで開けば、すぐに編集を始められます。お試しにアカウントは不要で、無料プランでアンケートを公開できます。

公開の準備はできましたか？

このテンプレートをエディターで開いてみてください。最初の回答者が目にする前に、すべてを自由に変更できます。

このテンプレートを使う無料で始める

関連テンプレート

似たテーマのほかの調査もご覧ください。

すべて見る
Industry-Specific

Patient Experience of Nursing Care Assessment

Captures how patients or clients experienced the nursing care they received — communication, responsiveness, pain management, and discharge preparation — for hospitals, clinics, and home health teams. An AI follow-up interview reconstructs the specific moment that most shaped their overall rating, surfacing concrete coaching moments beyond a satisfaction score.

テンプレートを見る
Industry-Specific

End-of-Class Feedback and Course Improvement Survey

Captures how students experienced a class — clarity of instruction, pacing, workload, and what actually helped them learn — then uses an AI follow-up interview to dig into the specific moment behind their overall rating. Built for instructors and departments who want more than a satisfaction number at term's end.

テンプレートを見る
Industry-Specific

End-of-Course Student Feedback Survey

Captures how students experienced a course — clarity of instruction, workload, materials, and instructor effectiveness — plus a best-worst prioritization of what to fix first. An AI follow-up interview digs into the reasoning behind the overall rating so instructors get specific, actionable detail instead of a single number.

テンプレートを見る
Industry-Specific

Professor Teaching Effectiveness Evaluation Survey

Measures how students experience a professor's teaching across clarity, engagement, feedback, availability, and fairness, plus overall satisfaction and likelihood to recommend. Built for academic departments and course coordinators running end-of-term reviews, with an AI follow-up interview that digs into the specific moment or assignment that most shaped a student's rating.

テンプレートを見る
Industry-Specific

Student Feedback on Teacher Effectiveness Survey

Gathers student feedback on a teacher's clarity, fairness, engagement, and support, plus which qualities matter most to learning. An AI follow-up interview digs into the specific moment behind each student's overall recommendation score, surfacing concrete examples instead of vague praise or complaints.

テンプレートを見る
Industry-Specific

Online Training Course Feedback Survey

Captures how learners actually experienced an online training course — completion, content quality, instructor clarity, and confidence applying the material — for L&D teams and course designers. An AI follow-up interview digs into the real obstacles behind low satisfaction or recommendation scores instead of settling for a bare number.

テンプレートを見る