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.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
How many of the class sessions did you attend in person or watch live?
- All or nearly all
- Most
- About half
- A few
- None
Overall, how satisfied are you with this class?
How much do you agree with each statement about this class?
- The instructor explained concepts clearly
- The pace of the class matched my ability to keep up
- Course materials (readings, slides, assignments) helped me learn
- I felt comfortable asking questions or participating
- Feedback on assignments or exams was timely and useful
In the last month, which part of the class contributed most to your learning?
- Lectures
- In-class discussions or activities
- Assignments or homework
- Group work or projects
- Office hours or extra help
- Readings or course materials
Looking at these aspects of the class, which most and least urgently need improvement?
- Pace of lectures
- Amount of homework or assignments
- Clarity of grading criteria
- Availability of the instructor for help
- Relevance of content to real-world skills
- Quality of course materials
- Opportunities for discussion or participation
How would you rate the overall workload for this class?
Reconstruct a specific moment or assignment that most shaped the respondent's overall satisfaction rating — ask them to walk through what happened, what the instructor or materials did well or poorly, and how it affected their learning. If they flagged a low-agreement item in the statement ratings (pacing, feedback timeliness, clarity), probe that concretely with an example. If workload was rated as too heavy or too light, ask what specifically they'd cut or add.
What's one specific change that would have made this class better for you?
What is your class standing?
- First-year
- Second-year
- Third-year
- Fourth-year
- Graduate student
- Other
- Prefer not to say
That's everything — thank you for the honest feedback! Your responses will be combined with your classmates' answers to help improve how this course is taught going forward.
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 single satisfaction score with a matrix of agreement statements plus a dedicated workload rating and attendance/standing questions for segmentation
- Uses an AI follow-up interview to reconstruct the specific moment or assignment that most shaped a student's overall rating, not just capture the rating itself
- Includes a max-diff exercise to prioritize which aspects of the class most urgently need improvement, giving instructors a ranked action list instead of open-ended guesses
- Closes with a specific 'what one change would help' long-text question, so qualitative feedback is targeted rather than generic
Jotform
Course Feedback Form TemplateA static, customizable course feedback form built on Jotform's drag-and-drop builder. It's fielding-ready but relies on fixed question sets with no mechanism to probe deeper into any individual response. Good for quick deployment and basic reporting, not for uncovering the reasoning behind a rating.
What it does well
- Fielding-ready template with drag-and-drop customization
- Wide range of field types and integrations typical of Jotform's builder
- Easy to embed or share across common LMS/email workflows
Where it falls short
- No adaptive follow-up questioning — every respondent sees the same static fields
- No automated per-response quality scoring
- No transparent AI prompt methodology, since there's no AI interview component
Typeform
Class Feedback Form TemplateA conversational-style static form using Typeform's one-question-at-a-time UI to collect class feedback. It's polished and fielding-ready, but the conversational feel is purely visual — there's no actual dynamic interviewing based on what a student answers. Best suited for simple satisfaction pulses rather than deep diagnostic feedback.
What it does well
- Clean, high-completion-rate UI with one-question-at-a-time flow
- Fielding-ready and easy to customize without technical setup
- Familiar branding and design polish for student-facing surveys
Where it falls short
- No true adaptive AI follow-up — question order and content are fixed regardless of answers
- No voice interview option or guided screen-share tasks
- No automated scoring of response quality or auto-generated analytical reports
QuestionPro
Course evaluation & improvement survey questions + Sample questionnaire templateThis is primarily a question-bank/guide page listing sample course evaluation questions rather than a single ready-to-field template. It's useful as a reference for building a survey manually, but it doesn't ship as an interactive, adaptive instrument. Reporting and analysis would need to be configured separately in QuestionPro's platform.
What it does well
- Broad library of sample course-evaluation questions across common categories
- Backed by an established survey platform with standard analytics tooling
- Useful as a reference/checklist for departments designing their own evaluation
Where it falls short
- Presented as a question bank/guide rather than a single ready-to-deploy adaptive template
- No adaptive AI interview to probe the specific moment behind a rating
- No published methodology for how any AI-assisted features (if used) generate or score results
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.