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Beyond the Smiley Sheet: Participatory Approaches to Obtaining Feedback After a Training

Started by Rhoda Nakhosi Oct 14, 2026 2 replies 👁 2 views
Rhoda Nakhosi Admin Community Champion (1,500+ points) Community Champion
Oct 14, 2026 at 3:59 pm

I'd like us to discuss on how we gather feedback after a training session. Too often, we rely on end-of-workshop evaluation forms, Likert scales, tick boxes, and the occasional open-ended question that tell us whether participants were "satisfied" but little about what actually shifted in their thinking or practice. What if we made the feedback process itself participatory, reflective, and generative? The core shift here is from feedback as a compliance exercise to feedback as a learning process, one that honours participants' voices, generates richer data, and actually informs how we design and facilitate future trainings.

Questions for the group:
1. Which participatory feedback methods have you used after a training, and how did they compare to traditional evaluation forms?
2. How do you handle the tension between rich participatory feedback and the pressure to report standardized indicators to donors or leadership?
3. How do you ensure feedback actually feeds back into future training design rather than just being collected and filed?
4. Have you adapted any of these methods for virtual or hybrid trainings? What worked?
5. What ethical considerations arise when feedback becomes more personal or story-based especially around anonymity and vulnerability?
Charles Member Expert (800+ points) Expert
5 days ago

Beyond the Smiley Sheet is the right provocation, Rhoda.

The smiley sheet measures transaction. It asks: were you satisfied? Participatory feedback measures transformation. It asks: what shifted?
In adult learning theory, this is the difference between Kirkpatrick Level 1 and Level 3. Satisfaction does not equal learning, and learning does not equal practice. The Likert scale gives us compliance data for donors. It rarely gives us learning data for design.
Three shifts that have worked in our practice:
1. From extraction to co-creation. Instead of "rate us," we use After-Action Reflection circles: what will you stop, start, continue? And Most Significant Change stories: tell us one moment that changed your thinking. The data is messier, but it is real.
2. From standardized to stratified. We keep one standardized indicator for reporting, but we layer participatory methods for learning. Donors get their number. We get our narrative. Both can co-exist if we design for both from the start, not as an afterthought.
3. From collection to closure. Feedback fails when it is filed. We close the loop by opening the next training with "you said, we did." Participants see their voice in the design. That builds trust more than any smiley face.
For virtual spaces, we use anonymous digital boards and audio notes - lower vulnerability threshold than on-camera storytelling.
The ethical point you raise is critical: when feedback becomes story-based, anonymity is not enough. We need explicit consent for story use, and the option to share with facilitator only, not the group.

Feedback should not be the end of training. It should be the beginning of the next one.
Nonvicks Ochieng Member Community Champion (1,500+ points) Community Champion
4 days ago

@Rhoda Nakhosi Transforming post-training evaluations into participatory processes moves the focus from superficial satisfaction scores to deep, actionable learning. Methods like the "3Cs" (Celebrate, Challenge, Change), Fishbowl Reflections, and "River of Experience" mapping allow participants to collectively reflect on how concepts challenged their prior thinking. In practice, these approaches generate far richer qualitative data than traditional tick-box surveys because they surface nuanced shifts in mindset and reveal systemic barriers to implementation that standardized Likert scales completely miss.

Bridging the gap between rich qualitative reflection and the rigid reporting requirements of donors or executive leadership requires a deliberate synthesis strategy. Teams can address this tension by applying qualitative coding frameworks such as thematic analysis or Most Significant Change (MSC) categorization to convert narrative reflections into measurable indicators, percentages, and trend matrices. Combining an upfront, 2-minute standardized rating pulse with a deeper, 20-minute participatory debriefing yields a hybrid dataset that satisfies quantitative logframes while preserving the authentic human stories behind the numbers.

Ensuring that feedback directly shapes future training design, rather than sitting idle in a folder, demands an institutionalized feedback loop built directly into the instructional design cycle. Immediately following a session, facilitation teams should conduct an immediate "harvesting and translation" meeting to categorize participant insights into immediate quick fixes for upcoming cohorts versus systemic curriculum revisions for long-term updates. Sharing a short "What We Heard & What We Changed" summary document with both past participants and incoming cohorts creates accountability and demonstrates that participant voices directly inform program evolution.

Adapting these methods for virtual and hybrid environments relies on leveraging collaborative digital tools to mirror the interactivity of an in-person room. Utilizing interactive digital canvases like Miro or Mural for asynchronous graffiti walls, breakout room board work, and anonymous real-time polling tools like Slido creates a safe space for honest input. In hybrid setups, pairing an in-person participant with a virtual peer as "reflection partners" ensures online attendees share equal agency in guiding the discussion rather than remaining passive observers.

Finally, shift toward story-based and personal feedback introduces ethical challenges around psychological safety, vulnerability, and informed consent. When participants share personal experiences or workplace challenges during reflective debriefs, absolute anonymity becomes difficult to guarantee, making strict ground rules and voluntary sharing essential. Facilitators must establish clear boundaries regarding data usage up front, sanitize individual identifiers when synthesizing narrative reports, and grant participants full control over whether their specific quotes or case examples can be shared beyond the immediate reflection space.