Lesson 5: Sensory Evaluation & Excel Basics — Measuring Font Impressions with the SD Method
Goals for This Lesson
- Understand the SD (Semantic Differential) method for measuring impressions
- Rate six font samples using a Google Form questionnaire
- Learn basic Excel operations (input, functions, sorting)
- Enter and calculate your own data
Instructor preparation
Before class:
Stimulus materials (font samples) Prepare slides or printed materials showing the same word (e.g., "DESIGN" or "音楽") in 6 different fonts. Suggested fonts: Yu Mincho / Impact / HGP Sōei Kaku Pop-tai / HGP Gyōshotai / Century Gothic / Yu Gothic
Google Form (questionnaire) Create a Google Form with 6 sections (one per font sample), each containing 7 bipolar scale items rated on a 1–5 scale. Share the link at the start of class.
After class (preparation for Lesson 6) Export the Google Form responses to Google Sheets, calculate class averages for each sample × item combination, and share an Excel file at the start of the next lesson.
1. What Is the SD Method?
1-1. Measuring Impressions with Numbers
Every day, we receive impressions from the things around us. Seeing a logo and thinking "that looks cool," or hearing music and feeling "that's warm" — these are sensations that are hard to put into words.
The Semantic Differential (SD) Method is a technique for measuring these impressions and feelings as numerical data. Developed by American psychologist Charles Osgood in 1957, it is widely used today in product design, UI/UX evaluation, marketing, architecture, and music research.
1-2. How the SD Method Works
The SD method uses pairs of adjectives with opposite meanings (bipolar scales). For each stimulus (e.g., a font), you rate which end of each scale it leans toward.
Example: Looking at a font
Bright [1] [2] [3] [4] [5] Dark
Light [1] [2] [3] [4] [5] Heavy
Like [1] [2] [3] [4] [5] Dislike- 1 = strongly matches the left adjective
- 2 = somewhat matches the left adjective
- 3 = neutral / neither
- 4 = somewhat matches the right adjective
- 5 = strongly matches the right adjective
1-3. Why This Matters for Art Students
In design, art, and entertainment, understanding how your work affects people — objectively — is essential. The SD method lets you go beyond "I like it" or "it doesn't feel right" and show what specific aspects work and to what degree, backed by data.
Where the SD method is used
- Measuring impression changes before/after product packaging redesigns
- Website and app design evaluation (UI/UX)
- Emotional response analysis for music and video content
- Environmental and interior design evaluation
- Brand logo image surveys
2. Today's Evaluation Task
2-1. What You're Evaluating
Today you will evaluate 6 font samples (A–F). The same word ("デザイン" — "Design" in Japanese) is displayed in six very different fonts. Rate the impression each one gives you based on your immediate, instinctive reaction.
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Important
- Rate your immediate impression upon seeing the font — not how readable it is
- Don't overthink it — go with your gut
- There are no right or wrong answers
2-2. Rating Items (7 items, 5-point scale)
| # | Left adjective | ← 1 2 3 4 5 → | Right adjective |
|---|---|---|---|
| 1 | Bright | Dark | |
| 2 | Light | Heavy | |
| 3 | Friendly | Intimidating | |
| 4 | Unique | Ordinary | |
| 5 | Refined | Unsophisticated | |
| 6 | Warm | Cold | |
| 7 | Like | Dislike |
2-3. Fill in the Google Form
- Open the Google Form link shared by the instructor (on screen or chat)
- For each font sample (A–F), rate all 7 items on the 1–5 scale
- Submit the form when done
The instructor will export all responses after class and prepare a class summary for Lesson 6.
3. Launch Excel
3-1. The Excel Interface
- Open Excel from the desktop or Start menu
- Click "Blank workbook" to create a new file
Excel's screen is a large grid of cells — the boxes where you enter data.
| Term | Description |
|---|---|
| Cell | One box in the grid where data is entered |
| Column | Vertical sequence, labeled A, B, C, … |
| Row | Horizontal sequence, labeled 1, 2, 3, … |
| Cell address | Column + row combination (e.g., B3 = column B, row 3) |
| Formula bar | Shows and edits the content of the selected cell |
3-2. Entering Data and Moving Between Cells
| Action | Method |
|---|---|
| Select a cell | Click |
| Confirm and move down | Enter key |
| Confirm and move right | Tab key |
| Cancel input | Esc key |
| Edit a cell | F2 key or double-click |
4. Build Your Data Entry Sheet
4-1. Enter Header Row
Type the following into the specified cells:
| Cell | Content |
|---|---|
| A1 | (leave blank) |
| B1 | Bright↔Dark |
| C1 | Light↔Heavy |
| D1 | Friendly↔Intimidating |
| E1 | Unique↔Ordinary |
| F1 | Refined↔Unsophisticated |
| G1 | Warm↔Cold |
| H1 | Like↔Dislike |
| I1 | Average |
Adjusting column width
Double-click the boundary between two column headers (e.g., between A and B) to auto-fit the column to its content.
4-2. Enter Sample Labels
| Cell | Content |
|---|---|
| A2 | Sample A |
| A3 | Sample B |
| A4 | Sample C |
| A5 | Sample D |
| A6 | Sample E |
| A7 | Sample F |
| A9 | Item average |
4-3. Enter Your Own Rating Data
Looking at your Google Form submission (or your memory of your answers), enter your ratings (1–5) into the corresponding cells.
- Enter data in the range B2 to H7 (each sample × each item)
Example (your data might look like this):
| Bright↔Dark | Light↔Heavy | Friendly | Unique | Refined | Warm | Like | |
|---|---|---|---|---|---|---|---|
| A | 2 | 2 | 2 | 3 | 4 | 2 | 1 |
| B | 3 | 4 | 4 | 2 | 2 | 4 | 4 |
| C | 1 | 1 | 1 | 2 | 5 | 1 | 2 |
| … | … | … | … | … | … | … | … |
Only enter values from 1 to 5
Values outside this range (e.g., 0 or 6) will distort your calculations.
5. Calculate Basic Statistics
5-1. AVERAGE Function — Row Average per Sample
Click on cell I2 and enter the following formula to calculate the average of all 7 ratings for Sample A:
=AVERAGE(B2:H2)Steps:
- Click I2
- Type
=AVERAGE(B2:H2) - Press Enter to confirm
Copy to I3–I7 using AutoFill:
- Select I2
- Hover over the small square in the bottom-right corner (the fill handle)
- When the cursor becomes a +, drag down to I7
What is AutoFill?
AutoFill copies the formula to adjacent cells, automatically adjusting row numbers. I3 will contain =AVERAGE(B3:H3), and so on.
5-2. AVERAGE Function — Column Average per Item
In cell B9, calculate the average across all 6 samples for the "Bright↔Dark" item:
=AVERAGE(B2:B7)Use AutoFill to fill C9 through H9 with averages for each item.
5-3. MAX and MIN Functions
In B11, find the highest rating (most "dark") given to any sample:
=MAX(B2:B7)In B12, find the lowest rating (most "bright"):
=MIN(B2:B7)Function syntax rules
- Always begin with
=(equals sign) - Function names are case-insensitive (Excel auto-capitalizes)
- Ranges are specified as
StartCell:EndCell
6. Sort Your Data
Sorting lets you immediately see which sample is rated highest (or lowest) on a given item.
6-1. Sort by "Like↔Dislike" Score
- Select the data range (A1 to I7)
- Go to "Data" tab → click "Sort"
- Set "Column" to H (Like↔Dislike)
- Set "Order" to "Smallest to Largest" (1 = Like appears at top)
- Click OK
The samples now appear in order from most liked to least liked.
6-2. Undo the Sort
Press Ctrl + Z to undo, or sort by column A (ascending) to restore the A–F order.
7. Save Your File
- Press Ctrl + S (or go to "File" → "Save As")
- File name:
SD_Ratings_[StudentID](e.g.,SD_Ratings_2024000) - Location: class folder or OneDrive
- Format: Excel Workbook (.xlsx)
Submission
| # | Item | How to submit |
|---|---|---|
| 1 | Excel file with your own rating data | Submit as instructed in class |
Pre-submission checklist
- [ ] Is data entered in all cells B2–H7 (6 samples × 7 items)?
- [ ] Does the AVERAGE formula appear in column I (I2–I7)?
- [ ] Are item averages calculated in row 9 (B9–H9)?
- [ ] Does the file name include your student ID?
Summary
In this lesson, you learned:
- The SD Method — a sensory evaluation technique that turns impressions into numbers with bipolar adjective pairs
- Excel basics — cell input, rows and columns, saving
- AVERAGE, MAX, MIN functions — fundamental data aggregation
- Sorting — organizing data visually
Next lesson, we'll use the class-wide dataset to create charts and analyze our findings together.