360 Feedback Questions: What to Ask, Example Questions, and Template

360 feedback is valuable when it improves decisions, not when it creates more forms. Most teams know the feeling of collecting a lot of answers that don’t change next week’s plan. The difference between “busy data” and useful insight comes down to three things: asking the right questions, designing a template that fits your context, and keeping data clean enough to analyze without heroic cleanup. For workforce-development programs, this is especially important because you’re not evaluating static employees inside a single org chart; you’re supporting learners, mentors, and future employers who operate across different schedules, environments, and expectations.

This guide gives you everything you need to run a modern 360 feedback process that actually drives improvement. It focuses on what to ask, shows complete example questions you can use, and ends with a practical template that aligns with continuous feedback (pre → mid → post → follow-up). It uses the fictional SkillBridge Workforce Initiative as a running example. SkillBridge prepares adults for digital roles; their challenge was familiar: long surveys, scattered files, and reports that arrived after the cohort had ended. By tightening question design and moving to a clean, continuous process, they converted feedback from a periodic ritual into a weekly operating system.

What 360 feedback means in a workforce program

In corporate HR, 360 feedback typically gathers views from a manager, peers, and direct reports. In a workforce program, the “360” includes the learner, mentors, instructors, program staff, and—later—employers. The goal shifts from ranking or rating to supporting growth: building skills, confidence, and job readiness. Your questions should therefore probe three zones:

• Skills and application: what learners can do and where they’re stuck.
• Confidence and behavior: whether attitudes and habits shift over time.
• Environment and support: whether mentors, resources, and logistics help or hinder progress.

A good 360 process makes these zones visible, compares them across time and segments, and links each signal to a clear next step (adjust content, add support, change practice). That “link to action” requirement is the biggest difference between a survey that reads nicely and a feedback system that consistently helps people improve.

Principles for writing effective 360 feedback questions

Write less, learn more. The best 360 forms are short enough to finish without fatigue and specific enough to guide change. SkillBridge adopted seven design principles that you can copy:

1. Make every question actionable. If no program decision would change based on the answer, cut it.
2. Focus on observable behaviors. Ask about tasks, communication, deadlines, and participation, not personality labels.
3. Use neutral, non-leading wording. Replace “How excellent was the mentoring?” with “How useful was the mentoring feedback for your next step?”
4. Mix closed and open questions. Closed items track trends; open items explain the “why.” A 70/30 mix (closed/open) is a reliable starting point.
5. Keep scales consistent. Use the same 1–5 or 1–7 anchors across sections to compare fairly.
6. Protect confidentiality where needed. Learners must feel safe giving constructive feedback on mentors, and mentors need space to be candid about program constraints.
7. Limit the total length. Across any single wave, aim for 18–25 questions total (including 3–6 open-ended). Over a lifecycle (pre, mid, post, follow-up), you’ll still gather a rich dataset without burning people out.

What to ask: core question sets you can use today

Below are question banks organized by the three zones and by respondent type. You can copy them as-is or adapt the verbs and nouns to your program. Where a question is closed-ended, assume a 1–5 scale with labeled endpoints (1 = Not at all, 5 = Extremely).

Learner questions — skills & application (closed)

• How confident are you completing the tasks covered in this module? (1–5)
• How often did you practice the new skill outside class this week? (Never to Very often)
• How clear were the instructions for the most recent assignment? (1–5)
• Did the projects feel relevant to the kind of work you want to do? (Not at all to Very relevant)
• Have you applied any course skill in a real or simulated work setting this month? (Yes/No)

Learner questions — skills & application (open)

• Describe one situation where you used a new skill. What worked and what didn’t?
• Which topic felt least relevant to your goals, and why?
• What would make the next assignment more realistic for the job you’re targeting?

Learner questions — confidence & behavior (closed)

• How comfortable are you asking for help when stuck? (1–5)
• How confident are you explaining your project to a non-technical audience? (1–5)
• How consistently did you complete practice tasks on time this week? (Never to Always)

Learner questions — confidence & behavior (open)

• What helped your confidence the most in the last two weeks?
• When did you feel most challenged, and how did you overcome it?

Learner questions — environment & support (closed)

• How useful was mentor feedback for your next step? (1–5)
• How accessible were program resources (e.g., labs, internet, office hours)? (1–5)
• Did scheduling or logistics make participation difficult this week? (Yes/No)

Learner questions — environment & support (open)

• What could the program do differently to help you succeed next week?
• What external factors (work, transport, caregiving) impacted your learning?

Mentor/instructor questions — skills & application (closed)

• The learner demonstrated the target skill in the last two weeks. (Strongly disagree to Strongly agree)
• The learner’s project quality meets the expected standard for this stage. (1–5)
• The learner proactively incorporated feedback. (1–5)

Mentor/instructor questions — confidence & behavior (closed)

• The learner participates constructively in group work. (1–5)
• The learner manages time effectively and meets deadlines. (1–5)
• The learner asks clarifying questions when uncertain. (1–5)

Mentor/instructor questions — environment & support (open)

• Which support would help this learner progress faster (e.g., peer partner, extra lab time, different materials)?
• What is the most important change we could make in the next week for this cohort?

Employer/supervisor (internship or early employment) — skills & application (closed)

• Graduate demonstrates the specific technical competencies needed in your context. (1–5)
• Graduate adapts to your workflows and tools within a reasonable learning curve. (1–5)
• Graduate applies feedback to improve performance. (1–5)

Employer/supervisor — confidence & behavior (open)

• Describe a moment when the graduate solved a problem independently.
• What gap, if any, appears repeatedly, and what practice would help close it?

Open vs. closed: the mix that drives learning

Closed questions let you see patterns by cohort, site, or baseline skill level. Open questions explain those patterns and surface “unknown unknowns.” When SkillBridge moved to a 70/30 mix and analyzed open comments with an AI assistant, they discovered that “peer support” in narratives closely tracked with higher confidence scores. They responded by formalizing peer sessions twice a week. Confidence improved within the same cohort, not just in the next one. That’s the payoff: question design that can change the outcome while training is still underway.

Scales, bias, and fatigue: make good choices up front

Pick a single scale (like 1–5) and label endpoints clearly. Consider adding a short descriptor under the midpoint (“3 = Moderately”) to reduce overuse of the middle. Avoid double-barreled items (“clear and engaging”) that split the meaning. Keep each section short: learners should complete a pulse in under four minutes mid-program, six to eight minutes pre/post. If you’re hitting ten minutes for a single wave, you’re probably asking too much.

Bias often sneaks in through adjectives or social pressure. Use neutral wording and remind respondents that candid feedback drives improvement and will be aggregated for reporting. If you’re collecting mentor feedback about learners, be clear about confidentiality and how comments are used.

The 360 template that works in real life

A single “master” template rarely fits every context. Instead, design a family of short templates that reuse core items for comparison:

• Pre (baseline): goals, current skill, initial confidence, expected barriers.
• Mid (pulse): what’s working, engagement level, confidence trend, early risks.
• Post (completion): confidence lift, skill application, satisfaction, next steps.
• Follow-up (outcomes): job relevance, skill use in the workplace, improvement suggestions.

SkillBridge kept five core items across all four waves so trends were easy to compare, then added context-specific questions to capture details unique to each stage. They limited open questions to two at mid (pulse) and four at post to protect completion rates.

Example 360 feedback template (copy-ready content)

Below is a condensed, practical template you can use. Replace bracketed competencies with yours.

Section A — Skills & Application (closed)

• I can complete [competency A] tasks required in this module. (1–5)
• I practiced [competency A] outside class this week. (Never to Very often)
• Project tasks matched my target job responsibilities. (1–5)
• I applied at least one course skill in a non-class context this month. (Yes/No)

Section B — Confidence & Behavior (closed)

• I ask for help when stuck. (1–5)
• I communicate my project clearly to non-technical audiences. (1–5)
• I finish planned practice tasks on time. (Never to Always)

Section C — Environment & Support (closed)

• Mentor feedback helped me decide my next step. (1–5)
• Program resources (labs, internet, office hours) were accessible. (1–5)
• Scheduling/logistics made participation difficult. (Yes/No)

Section D — Narrative (open)

• What was most challenging this week, and what would help?
• Describe one win from this week. What made it possible?
• What should we change in the next two weeks?

Mentor short form (biweekly)

• The learner demonstrated [competency A] in a recent task. (1–5)
• The learner incorporated feedback from the last session. (1–5)
• One action I recommend for the learner in the next week is: [open]

Employer short form (30–60 days after placement)

• Graduate demonstrates the core technical competencies for the role. (1–5)
• Graduate adapts to tools and workflows. (1–5)
• A specific practice that would have better prepared the graduate is: [open]

Sequencing, logic, and accessibility

Order items from easy to reflective. Open with quick wins (confidence, clarity), then move to more evaluative topics. Use skip logic to hide irrelevant sections. If a learner answers “No” to applying a skill in the last month, show one short question asking why and what would help. Keep language simple and mobile-friendly. Include a progress indicator. Save state so longer waves can be completed in two sittings where needed.

Clean data: the foundation for trustworthy 360 results

The most common failure in 360 isn’t bad questions; it’s bad data hygiene. When learners submit multiple forms from generic links, duplicates proliferate, merges break, and you spend weeks reconciling. Clean-at-source collection fixes this: every learner, mentor, and employer has a unique record and a unique link. Responses across waves attach to the same person automatically. If something needs correction, that same unique link lets the person update their record without creating a new row.

SkillBridge’s transformation started here. Once every respondent had a unique, persistent link and all waves were tied to the contact record, dashboards updated instantly. Analysts stopped doing VLOOKUPs and started discovering patterns. Instructors stopped waiting for reports and started acting on early trends. The organization moved from “proving impact” to “improving outcomes.”

How to analyze 360 feedback without losing nuance

Start with the basics: visualize closed-ended items across cohorts and segments (site, modality, baseline skill). Then connect narratives to those patterns. Use an AI assistant to extract themes (e.g., peer support, time pressure, access issues) and tag each comment with sentiment and one or two rubrics specific to your program (e.g., “communication clarity” or “project ownership”). Always keep original quotes linked to summaries so nothing gets lost in translation.

SkillBridge used this approach to discover a consistent gap: learners with evening jobs struggled to attend live code reviews, which coincided with lower confidence. The change was simple—adding a Saturday session and asynchronous review. Within one cohort, confidence and completion improved. That is the loop you’re trying to build: collect, see, act, verify.

Equity and disaggregation without tokenism

Disaggregate by factors that matter in your context: site, schedule, language, baseline skill, access to devices, caregiving responsibilities. Use suppression rules (e.g., don’t show charts for groups with n<10) to avoid overinterpreting small samples. Pair numeric differences with narrative evidence to avoid simplistic conclusions. Track whether your changes reduce gaps over time.

Example lifecycle for SkillBridge

• Pre: 18 questions (3 open). Focus on goals, baseline skill, confidence, and potential barriers.
• Mid: 12 questions (2 open). Focus on engagement, clarity, and early risks.
• Post: 22 questions (4 open). Focus on confidence lift, skill application, satisfaction, and next steps.
• Follow-up (90 days): 15 questions (3 open). Focus on workplace application and suggested improvements.

SkillBridge set aside one hour every Friday for “learning reviews.” The team opened live dashboards, read three to five representative quotes per theme, and committed to one change to test the next week. The cadence turned 360 feedback into standard practice rather than an annual event.

360 template variants (plug-and-play)

Variant A — Short learner pulse (mid-program)

• Confidence applying this week’s skill (1–5)
• Clarity of assignment instructions (1–5)
• I practiced outside class (Never to Very often)
• One thing that would help next week is: [open]
• Quick check: scheduling/logistics made participation difficult (Yes/No)
• If Yes: What got in the way? [open]

Variant B — Mentor micro 360

• Learner met the quality bar for [competency]. (1–5)
• Learner integrated feedback from last session. (1–5)
• One action for the next week: [open]

Variant C — Employer check-in (short)

• Graduate demonstrates core skill(s). (1–5)
• Graduate communicates progress and blockers. (1–5)
• One suggestion to improve training relevance: [open]

Response-rate tactics that don’t annoy people

Tell respondents why their answers matter and show them what changed. Keep it short. Send at sensible times. If you’re asking a mentor for feedback, provide the last two actions the learner took so the mentor can respond quickly. For learners, allow mobile completion and show a progress indicator. Consider tiny “thank you” gestures (recognition, certificates) over gift cards; the goal is to build a culture of input, not a marketplace of responses.

From questions to a continuous system

Questions are the visible part of 360 feedback. What makes the system work is everything behind them: unique IDs, clean linking across waves, validations that prevent typos, and instant analysis that respects both numbers and narratives. Whether you run SkillBridge-like cohorts or entirely different programs, the formula is the same: ask better, collect cleaner, learn faster.