Q01
Message
All templatesIndustry-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.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
11 questions · ~6 min
Q02
Multiple ChoiceRequired
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
Opinion ScaleRequired
How likely are you to recommend this lecture to a classmate who's deciding whether to attend?
Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q04
MatrixRequired
How much do you agree with each statement about this lecture?
5 rows × 5 columns
- 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
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q05
Rating Scale
How would you rate the instructor's responsiveness when you asked questions during or after the lecture?
Range: 1 – 5
Min:PoorMax:Excellent
Q06
Best–Worst Trade-off (MaxDiff)Required
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
Pick best & worst per setBest:Would improve the lecture mostWorst:Would improve the lecture least
Q07
AI Interview
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
Long Text
Is there anything else about this lecture you'd like to share with the instructor or course organizers?
Q09
Multiple Choice
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
Multiple Choice
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
Message
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.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- 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 ExamplesThis 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.
What it does well
- 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
Where it falls short
- 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
Frequently asked questions
What questions are in the “Post-Lecture Feedback & Teaching Quality Survey” template?
The template includes 11 ready-to-use questions, starting with: “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?”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 11 questions in about 6 minutes.
Can I customize this template?
Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.
Is this template free to use?
Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
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