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Education & Academic

Student Program Recommendation & Advocacy Survey

Measures how likely students are to recommend a course, program, or instructor to a peer, what drives that willingness, and where the experience falls short. An AI follow-up interview digs into the specific reasons behind each student's score, surfacing concrete moments and details that a rating alone can't capture. Built for academic departments, bootcamps, and course teams tracking word-of-mouth and retention risk.

Sample questions

A preview of what’s in the template. Every question is editable before you launch.

10 questions · ~6 min
Q01
Message

Hi! We're checking in on your experience with (Replace with course/program name) and whether you'd recommend it to another student. Your responses are completely confidential and anonymized. This takes about 5 minutes and your honest feedback helps us improve it. (Template note: replace the program name and any references throughout before launching.)

Q02
Opinion ScaleRequired

How likely are you to recommend this program to a fellow student in a similar situation?

Scale: 010
Min:Not at all likelyMax:Extremely likely
Q03
MatrixRequired

How would you rate each of the following aspects of your experience?

5 rows × 5 columns
  • Quality of instruction
  • Relevance of course content to your goals
  • Workload and pacing
  • Availability of support (instructors, TAs, advisors)
  • Preparation for next steps (further study, career, project work)
Columns: Poor · Below average · Average · Good · Excellent
Q04
Multiple ChoiceRequired

In the last month, which single thing most influenced how you'd describe this program to a friend?

  • A specific class, lecture, or assignment
  • Interaction with an instructor or advisor
  • Workload or time demands
  • Career or academic outcomes you're seeing
  • Interactions with other students
  • Administrative or logistical issues
Q05
Ranking

If you could change three things about this program, rank these from most to least urgent to fix.

  1. Course content and materials
  2. Instructor availability and feedback speed
  3. Workload and pacing
  4. Clarity of expectations and grading
  5. Career or academic support
  6. Peer collaboration opportunities
  7. Administrative processes
Drag to rank
Q06
AI Interview

Reference the respondent's recommendation likelihood score directly and ask them to walk through the specific experience that most shaped it — a class, conversation, or moment. If the score is 8 or above, probe what would make them actively promote the program rather than just approve of it. If the score is 6 or below, identify the single fixable issue that would move their score up, and press for a concrete example rather than a general complaint. Do not let vague answers like 'it was fine' or 'not great' stand without a specific instance.

Q07
Long Text

Is there anything else about your experience — good or bad — that these questions didn't capture?

Q08
Multiple Choice

What is your current year or stage in the program?

  • First year
  • Second year
  • Third year
  • Fourth year or beyond
  • Recently completed/graduated
  • Prefer not to say
Q09
Short Text

What is your major, track, or program specialization? (Optional)

Q10
Message

Thank you for sharing your honest perspective! Your responses will be reviewed alongside other students' feedback to guide changes to the program — individual answers are not shared with instructors in identifiable form.

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

  • Directly measures recommendation likelihood with an opinion scale, then uses an AI follow-up interview that references the respondent's specific score to dig into the concrete reasons behind it — something a static rating question can't do.
  • Combines quantitative signals (opinion scale, matrix ratings, ranking of what to change) with qualitative depth (open long-text and AI-driven probing) in a single flow, rather than forcing a choice between the two.
  • Includes a ranking question so departments know which specific changes students prioritize, plus optional major/stage questions to segment recommendation drivers and retention risk by student group.
  • Ends with a transparent close-out message and produces an auto-generated report, so course teams get organized findings without manually coding open-ended responses.

QuestionPro

Course evaluation sample questions and survey template

A course/teacher evaluation template with sample questions covering instructional quality, materials, and general satisfaction. It's a fielding-ready static form aimed at broad course evaluation rather than specifically isolating word-of-mouth recommendation drivers. Good for standard end-of-term evaluations but not built around a single recommendation-likelihood metric.

What it does well

  • Established survey template library with sample question sets tailored to academic course/teacher evaluation
  • Covers general course quality dimensions likely useful for broad satisfaction reporting
  • Backed by a full survey platform with standard analytics and reporting tools

Where it falls short

  • Static question set with no adaptive AI follow-up to probe the specific reasons behind a low or high evaluation score
  • No voice AI interview or screen-share guided task option for deeper qualitative context
  • No transparent, published prompt methodology for how open-ended responses are analyzed

SurveyMonkey

Graduation Survey Template for University

A university graduation survey template focused on capturing overall student experience and outcomes at the point of graduation. It's a ready-to-use static form, but its scope is broader program-completion feedback rather than a dedicated recommend-to-a-peer and retention-risk instrument. Useful for exit surveys, less suited to ongoing word-of-mouth tracking mid-program.

What it does well

  • Simple, ready-to-deploy template backed by a widely used survey platform with standard reporting dashboards
  • Framed specifically for the graduation milestone, useful for end-of-program outcome capture
  • Easy distribution and basic analytics through an established survey tool

Where it falls short

  • Fixed question set with no adaptive AI interview to follow up on why a student would or wouldn't recommend the program
  • No voice AI or guided screen-share task option to surface specific moments behind a score
  • Not designed for mid-program, recurring recommendation/retention-risk tracking — more of a one-time exit 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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