Capstone Project Support & Learning Outcomes Survey
Evaluates students' capstone project experiences—including mentorship quality, resource availability, skill development, and key challenges—to inform data-driven program improvement decisions.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
When did you complete your most recent capstone project?
- This term
- Last term
- 2–3 terms ago
- More than a year ago
Which of the following support resources did you use during your capstone? Select all that apply.
- Faculty advisor meetings
- Industry mentor/sponsor
- Workshops or clinics
- Online modules or guides
- Instructor office hours
- Peer collaboration
- Library/research support
- Labs/tools/equipment access
- Project management templates
- None of the above
How satisfied are you with the overall outcomes of your capstone project?
Based on your capstone experience, what should we change or add to better support future capstone students?
What is your current program level?
- Undergraduate
- Master's
- Doctoral
- Certificate/Bootcamp
- Other
- Prefer not to say
Thank you for completing the survey! Your feedback will be used to improve capstone support and outcomes for future students. If you have any questions about this study, please contact [program contact email].
What was the primary domain of your capstone project?
- Software/IT
- Engineering (non-software)
- Business/Entrepreneurship
- Data/Analytics
- Design/Arts
- Health & Life Sciences
- Education
- Social Impact/Public Policy
- Other (please specify)
Overall, how available was support when you needed it during the capstone?
To what extent did the capstone project prepare you for professional or academic work in your field?
We'd like to learn more about your capstone experience. An AI moderator will ask a few follow-up questions based on your responses.
What is your current enrollment status?
- Full-time
- Part-time
- Prefer not to say
How would you rate the quality of guidance you received from your faculty advisor or primary mentor?
Which skills improved the most as a result of your capstone project? Select up to five.
- Problem solving
- Technical depth
- Communication
- Teamwork
- Project management
- Research methods
- Stakeholder management
- Ethics/professionalism
- Creativity
- Data analysis
What is your primary mode of instruction?
- On-campus
- Online
- Hybrid
- Prefer not to say
How would you rate the adequacy of tools, equipment, and technical resources available to you?
Rank the following challenges based on their impact on your capstone experience (1 = greatest impact).
- Unclear or shifting scope
- Time management/workload
- Limited stakeholder access
- Insufficient technical skills
- Team coordination issues
- Tool or data constraints
What is your age range?
- 18–20
- 21–24
- 25–34
- 35–44
- 45–54
- 55+
- Prefer not to say
How would you rate the quality of peer collaboration and teamwork support during your capstone?
How do you describe your gender?
- Woman
- Man
- Non-binary
- Prefer not to say
In which region is your institution located?
- North America
- Latin America & Caribbean
- Europe
- Africa
- Middle East
- South Asia
- East Asia
- Southeast Asia
- Oceania
- Prefer not to say
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 closed-ended scales (advisor guidance, resource adequacy, peer collaboration, career readiness) with an AI follow-up interview that lets students elaborate on their capstone challenges in their own words.
- Includes a ranking question to surface which specific challenges (e.g., mentorship gaps, resource shortages) had the greatest impact, plus a skills-gained multi-select for outcome tracking.
- Captures program-level context (program level, enrollment status, mode of instruction, region) so administrators can segment results by cohort for data-driven program improvement.
- Every AI-generated follow-up question is shown transparently, and results roll up into an auto-generated report — no manual coding of open-ended feedback required.
Jotform
Project Information Form TemplateThis is a generic project-intake form for collecting basic project details (title, description, team, deliverables), not an education-specific outcomes or mentorship-quality survey. It's a fielding-ready static form builder template, but it isn't designed to evaluate capstone support, advising quality, or learning outcomes. Useful only as a loose structural reference, not a direct competitor to a program-improvement survey.
What it does well
- Simple, quick-to-deploy form for capturing standardized project metadata
- Jotform's drag-and-drop builder and integrations make distribution and data collection easy
Where it falls short
- No adaptive AI interviewing or voice AI follow-up — purely static fields
- Not built for evaluating mentorship quality, resource adequacy, or learning outcomes
- No automated quality scoring or auto-generated analysis of open responses
SurveySparrow
Project Submission Form TemplateSurveySparrow's education template is aimed at collecting student project submissions (files, descriptions, deadlines) rather than evaluating the support and learning-outcomes experience around a capstone. It's a ready-to-use form in the education category, but its scope is submission logistics, not program-improvement research. Some question style overlap (conversational form format) but different intent.
What it does well
- Education-category template with a conversational, chat-style UI familiar to students
- Ready-to-use for handling project deliverable submissions and deadlines
Where it falls short
- No mentorship, resource-adequacy, or skill-development evaluation questions
- No adaptive AI or voice AI follow-up probing on challenges faced
- No built-in per-response quality scoring or auto-generated program-improvement report
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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