**Calculate the Comprehension Score:**
Use the responses from the column **"[Column with comprehension ratings]"** in the attached CSV to calculate the Comprehension score using the following formula:
Comprehension Score = (sum of all Likert ratings in **[Column with comprehension ratings]**) ÷ (number of responses) ÷ 4
Likert Ratings are coded as:
- Understood Very Well = 4
- Understood Somewhat = 3
- Understood Poorly = 2
- Did Not Understand = 1
After calculating the Comprehension score, report where it lands on the following scale:
- **Very Good** = above 90%
- **Good** = 70–89%
- **Average** = 50–69%
- **Poor** = 30–49%
- **Very Poor** = 0–29%
Next, analyze the responses in the column **"[Column with qualitative explanations]"** in the CSV to identify common themes and provide clear, actionable suggestions for how the Comprehension score could be improved.
Here’s your Comprehension Score and a concise analysis from the CSV you attached.
📊 Comprehension Score (Section 4 Choices)
Mapping used (per your rubric):
Understood Very Well = 4, Understood Somewhat = 3, Understood Poorly = 2, Did Not Understand = 1
Detected answer labels in your data:
“Understood very well” → 4
“Understood most of it” → 3 (treated as Understood Somewhat)
“Understood a little” → 2 (treated as Understood Poorly)
“Did Not Understand” (not present in this export)
Counts (N = 89 valid responses):
Understood very well: 56
Understood most of it: 29
Understood a little: 4
Did Not Understand: 0
Comprehension Score
∑
ratings
𝑁
÷
4
=
319
89
÷
4
=
0.8961
=
89.61
%
N
∑ratings
÷4=
89
319
÷4=0.8961=89.61%
Scale placement: Good (70–89%)
(Right on the cusp of “Very Good.”)
You can review the distribution in the chart above and the table I generated:
Download the distribution CSV
💬 What people said (Section 4 Explanation)
Frequent terms/ideas (top words/bigrams):
Clarity & ease: understand, easy, clear, straightforward (e.g., bigram “easy understand”)
Context: event, details, options, information, outfit
Pain points: some mention of confusion or missing pieces (e.g., unclear “cool/warm” theme, wanting more specifics)
Representative snippets (lightly anonymized):
“Very easy to understand and not too busy.”
“This quick quiz has a clear purpose and is friendly.”
“I’m not following whether cool/warm is a vibe or a theme… unclear; feels like some pieces are missing.”
“Provides all the necessary details regarding the event and attire.”
Takeaways
Most respondents grasp the flow and intent (strong “very well/most of it” share).
A smaller group wants clearer guidance on how to interpret/choose options (especially around theme/color guidance), and occasionally more specific, step-by-step info.
🔧 Recommendations to raise Comprehension into “Very Good” (>90%)
Make the mental model explicit up front (reduce “missing pieces”)
Add a short intro sentence above the widget: “Tell us about your event; we’ll suggest colors/outfits that fit its theme (e.g., cool vs. warm palettes).”
Include one concrete example: “For a daytime garden party, choose warm (gold/terracotta) vs cool (sage/midnight).”
Clarify ambiguous terms with microcopy & helpers
Where you mention “cool/warm”, add a tiny (?) tooltip or inline hint with 2–3 swatches and a one-line definition.
Label fields and choices with actionable phrasing: “Pick a vibe (cool/warm)” → “Choose color temperature (cool blues/greens vs. warm reds/golds).”
Strengthen step-by-step structure
Break the flow into clear steps (“1. Event type → 2. Time/place → 3. Color direction → 4. Outfit suggestions”) and show users where they are.
Add a summary line before submit: “You selected: Event Evening, Setting Indoors, Color temperature Warm.”
Use visual examples to support text
For color decisions, show thumbnail palettes and mini outfit tiles under each option—visuals anchor comprehension faster than text alone.
Ensure contrast/legibility of any text over imagery (avoid low-contrast gray; maintain accessible contrast ratios).
Close the loop with confirmation & next steps
After selection, show a concise explanation of why the recommendation fits (e.g., “Warm tones read lively in low light”).
Provide quick edit links to change earlier inputs if users realize they misunderstood a step.
Validate quickly with micro-tests
Run a 5-second test on the revised intro + first step; target ≥75% correct “what to do” description.
Add a single in-flow micro-question (“Was this step clear?”) to catch regressions; aim for ≥90% “Yes.”