Q01
Message
All templatesIndustry-Specific
Virtual Class & Remote Learning Feedback Survey
Captures how well a virtual class delivered on content clarity, technical quality, and engagement — for training teams and educators running live or recorded remote sessions. An AI follow-up interview digs into what actually happened during the session that a rating alone can't explain, like where attention dropped or which moment made the material click.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
12 questions · ~7 min
Q02
Multiple ChoiceRequired
How did you attend this class?
- Live, on camera
- Live, audio/camera off
- Watched a recording
- Joined live but missed parts, caught up on recording
Q03
Opinion ScaleRequired
Overall, how satisfied were you with this class?
Scale: 1 – 7
Min:Very dissatisfiedMax:Very satisfied
Q04
MatrixRequired
How much do you agree with each statement about this class?
5 rows × 5 columns
- The audio and video quality were reliable throughout
- The pace of the session matched my ability to follow along
- The materials or slides shared were clear and useful
- The instructor explained concepts clearly
- I had real opportunities to ask questions or participate
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q05
Rating ScaleRequired
How would you rate the instructor's ability to keep remote attendees engaged?
Range: 1 – 5
Min:Not engaging at allMax:Extremely engaging
Q06
Multiple Choice
Which, if any, technical issues did you experience during this class?
- Audio cutting out or lagging
- Video freezing or poor quality
- Difficulty accessing the platform or link
- Screen sharing or slides not visible
- Chat or Q&A features not working
Q07
AI Interview
Reconstruct what actually happened for this respondent during the class rather than just their rating: ask them to walk through one specific moment that stood out, whether positive (something clicked) or negative (attention drifted, confusion, or a technical problem). If they mentioned any technical issues or disagreed with statements about pacing or participation opportunities, probe exactly when it happened and how it affected their ability to follow the session. If their satisfaction rating was low, ask what single change would have made the biggest difference.
Q08
Opinion ScaleRequired
How likely are you to recommend this class to a colleague or peer?
Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q09
Long Text
What is one thing we could change to make future virtual classes more valuable for you?
Q10
Multiple Choice
Which best describes your role in attending this class?
- Student
- Employee / workplace training
- Professional development / certification
- Prefer not to say
Q11
Dropdown
How much prior experience did you have with the topic before this class? (optional)
- None
- A little
- Moderate
- Extensive
- Prefer not to say
Q12
Message
That's everything — thank you for the detailed feedback! Your responses will be reviewed by the training team to improve delivery, materials, and platform reliability for future sessions.
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
- Goes beyond a satisfaction score with an AI follow-up interview that reconstructs what actually happened in the session — where attention dropped, what made the material click — instead of leaving that context up to a single open-text box.
- Combines standard feedback metrics (satisfaction, likelihood to recommend, engagement rating, agreement matrix) with role and prior-experience segmentation, so training teams can see how different attendee types experienced the class.
- Directly captures technical delivery quality via a dedicated technical-issues question alongside content and engagement measures, giving a fuller picture of what broke down and why.
- Backed by transparent, auto-generated reporting and per-response quality scoring, so training teams get a synthesized readout rather than raw transcripts to sift through manually.
SurveySparrow
Virtual Class Feedback Form TemplateA ready-to-field static feedback template built specifically for virtual classes, covering the same general territory as our survey (satisfaction, engagement, content quality). It's a fixed questionnaire, so all respondents answer identical questions regardless of what actually happened in their session.
What it does well
- Purpose-built for virtual class feedback rather than a generic survey template
- Likely quick to deploy with SurveySparrow's form-building tools
Where it falls short
- No adaptive follow-up questioning — cannot probe further when a rating reveals a problem
- No mechanism to reconstruct session-specific moments (drop-off points, standout moments) beyond what open-text fields capture
- No published methodology on question logic or scoring
Typeform
Free Class Feedback Form TemplateA general class feedback template (not specific to virtual/remote delivery) offered free on Typeform's platform. Good for basic satisfaction capture with Typeform's conversational UI, but it's a static form rather than an interview-style survey.
What it does well
- Polished, conversational one-question-at-a-time interface
- Free to use and easy to customize for general class feedback
Where it falls short
- Not tailored to virtual/remote-specific issues like technical quality or attendance mode
- Fixed question flow with no adaptive AI probing into what happened during the session
- No automated quality scoring or structured report generation built for training teams
QuestionPro
Seminar feedback & attendee information survey questions + Sample questionnaire templateA broader seminar/event feedback template with attendee information questions; it's oriented toward seminars generally rather than remote/virtual class delivery specifically. Useful as a question-bank reference, but requires adaptation for virtual-class contexts like technical issues or engagement over video.
What it does well
- Covers attendee information alongside feedback, useful for segmentation
- Broad question library that can be adapted for various seminar formats
Where it falls short
- Not specifically designed for remote/virtual delivery nuances (technical issues, remote engagement)
- Static questionnaire format with no adaptive interview component to explain low scores
- No auto-generated report or per-response quality scoring described
Frequently asked questions
What questions are in the “Virtual Class & Remote Learning Feedback Survey” template?
The template includes 12 ready-to-use questions, starting with: “Thanks for taking a few minutes to share feedback on the virtual class you just attended! Your input helps us make the n…” · “How did you attend this class?” · “Overall, how satisfied were you with this class?”. The full set is previewed above, and every question is editable.
How long does this survey take to complete?
Respondents typically finish the 12 questions in about 7 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.
Related templates
More studies on similar topics.
Industry-Specific
Crisis Response Evaluation and Debrief Survey
Gathers structured feedback from employees or stakeholders on how your organization communicated and led through a specific crisis — speed, clarity, and trust in decision-making — plus an AI follow-up that reconstructs the moment communication broke down or worked well. Built for comms, HR, and leadership teams running a post-incident debrief.
View templateIndustry-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.
View templateIndustry-Specific
Online Course Feedback & Completion Survey
Captures how learners experienced an online course — content clarity, pacing, instructor delivery, and completion barriers — with an AI follow-up interview that digs into the specific moment a learner struggled, disengaged, or nearly dropped out. Built for course creators, instructional designers, and academic teams reviewing a cohort or module.
View templateIndustry-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.
View templateIndustry-Specific
Post-Training Session Feedback & Impact Survey
Captures how a training session landed — content quality, trainer effectiveness, and confidence applying new skills — for L&D teams and instructors. An AI follow-up interview digs into the real story behind the recommendation score: what specifically helped or blocked people from using what they learned.
View templateIndustry-Specific
Distance Learning Experience Survey for Teachers
Captures how teachers are actually experiencing remote and hybrid instruction — platform use, engagement and assessment challenges, confidence levels, and support priorities — for school and district leaders planning training and tools. An AI follow-up interview digs into each teacher's single biggest obstacle and what would genuinely fix it, not just a wish list.
View template