After college, I learned that you have to convince people, often on short notice, to invest in your ideas and give you time to develop them fully. College didn't teach how to do that. This class builds your capability to make your ideas compelling quickly — in or outside of your comfort zone.
Gallery walk (physical on display and digital (shared slides)) → Critique protocol → New challenge launch → In-class exercise
Remaining content + short theory discussion → Studio time (most of the time)
WIP doc updated + Gallery Slides polished + physical work ready to bring in
1. WIP & Reflections Doc
Your personal Google Doc — one for the term, a tab for each week. Drop in process work, sketches, reading reflections, data, notes. It can be messy.
2. Weekly Gallery Slides
Shared class deck — 3 polished slides in your name section each week. Clean photos, final work only. We present from this in class. Bring physical work to class Monday.
3. Weekly Reflection + Voting
Private Google Form — only teaching staff see your answers. Short weekly reflection + your votes on classmates' work. Voting is a form of reflection. Builds toward your POV statement.
Research and theory that gives you language for what you're doing. Each reading has a key insight and a "show it in your design" prompt. Theory discussions on Wednesdays.
Originality — most surprising approach
Feasibility — most buildable
Embodiment — best instantiation of the concept
Peer Favorite — voted by you
Meaningful — matters to someone · Delightful — surprises and pleases · Cool — signals identity · Covetable — you want to own it · Sustainable — doesn't cost the earth · Efficient — respects your time · Legible — helps you understand
Violet slides
Real-world designs analyzed for structural principles. What worked, what didn't, and why. These are the examples you'll learn from and transfer to your own work.
Combining insights from one domain to another. We'll do this from practice and research. For HCD minors, this is a different method from ethnography.
"The principle I applied is _____, and it shows up in my design as _____."
Must be structural, not surface. Every portfolio entry, starting Week 2.
Forest slides
What to make, deliverables, criteria, reflections, and deadlines — all on one dense slide. This is your reference. Come back to it throughout the week.
Your Portfolio
Every challenge = one entry. By Week 10 you have 7+ entries ready to assemble.
Your Curation Journal
1+ examples of "desirable" design each week. Feeds your midterm POV (Wk 6) and final POV (Wk 10).
Navy slides
Before we get into anything — list your favorite designed things. Products, apps, buildings, clothes, tools, experiences, anything. Try for 10, but 5 is fine. Just write what comes to mind.
Keep this list. You'll compare it to data later.
Once you have your list, put a letter next to each one for why you like it so much. Use as many letters as apply to each example:
Look at the letters clustering on your list. That's your first data drawing — a portrait of your taste in 7 letters.
Week 1
Required Reading
These slides with Altringer Eagle / DIAD Design Systems Survey — Expanding range of designer materials and methods to mix.
Further Reading
Lupi — "Data is not cold. Data is human traces made visible." Hand-drawn forces you to slow down.
Amabile — Three trainable components: domain skills, creative processes, task motivation.
Tufte — "Above all else, show the data." Restraint as a design skill.
Dear Data (Lupi & Posavec) — hand-drawn data postcards for a year. The imperfection is the point.
"Dear Data, Design Vision"
V1: Curate top 20 favorite designs. V2: Tag by DIAD system, draw as Dear Data drawing. Place side by side.
Due: Monday April 6th.
Week 1 full slides (required)
Amabile (1983) (optional)
Social psychology of creativity
Lupi & Posavec (optional)
Dear Data / Data Humanism
Tufte
Visual Display of Quantitative Information
Week 1: only these slides are required. Other readings are optional.
What counts as a designable material has grown since many design education frameworks were developed. Alongside concepts and physical materials are new ones that are arguably systems: service, sensory and interactive, computation, new materials, energy, and more. We're exploring a multi-system framework that gives designers expanded capability and range for their ideas.
Creativity has three components, all trainable: Domain Skills (what you know about the field), Creative Processes (how flexibly you think — risk-taking, reframing, tolerance for ambiguity), and Task Motivation (genuine engagement, not compliance). The strongest creative work happens when all three are active. This week: which components did you rely on? Which did you neglect?
You don't have to be a data scientist or programmer to work with data as material. You already do as a consumer. Websites, social media likes, product reviews with stars are data and visualization designs. Creators need to train themselves to see that data and designed data are everywhere. In this challenge, hand-drawn visualization forces you to slow down, interpret, and find the story that automated charts skip over. The imperfection is the point — it preserves the human quality of the data. Drawing data by hand changes what you notice and gives you more decision control over how you present it.
"Above all else, show the data." Remove everything that doesn't help comprehension. Every element should carry information — if it's decoration, cut it. What you leave out is as important as what you include.
A chair designer in 1925 worked with wood. A chair designer in 2026 works with wood and its supply chain, its carbon cost, its end-of-life path, its data. The material got revealed as a system it was always part of. We’re exploring new ways to help prepare future design+builders to name and think across systems.
Designers have always worked with materials. What's changed is the scale of what counts as a material. A chair designer in 1925 worked with wood. A chair designer in 2026 works with wood and its supply chain, its carbon cost, its end-of-life path, its manufacturability and shipping reality in different regions, sophisticated data on pricing, user reviews, and social media. The material got revealed as a system it was always part of.
In the 1920s, the Bauhaus pedagogical wheel covered stone, wood, metal, glass, clay, textiles, color, and paper — the materials that future designers and builders needed to learn to mix to innovate. This influenced countless design programs and Dieter Rams, who influenced Steve Jobs, who influenced designs you might be holding in your hand right now. A century of design influence from mixing materials and methods.
Despite its lasting influence on design education, much has changed in materials and methods since then. The same expansion from wood as material to wood as system happened everywhere. The workshop became service systems. Craft became longevity systems. Color became a broader range of visual and interactive design systems. Computation and biology showed up as entirely new workbenches.
No designer could hold all of this. You could think about the wood or you could think about the forest, but rarely both at once with any rigor. So designers worked with what was on the table in front of them and externalized the rest. Environmental cost was someone else's department. Health impact was someone else's department. Longevity was someone else's problem.
Today, it is time to think fresh about design education materials and methods. The things you design have always been part of these systems. Until recently, there was no way to work with them without abandoning the craft, intuition, and aesthetic judgment that make you a designer. AI changes this. It lets designers see, shape, iterate, and judge while staying aware of the system each material lives in. The designer still picks the wood. They still integrate art and science to design its form and function.
Increasingly, they also have tools that let them see the forest, the carbon, the repair path, and the 50-year lifecycle, and make choices accordingly. The question is what we will do with all this additional capability. That's why the Design Initiative at Dartmouth is piloting these seven material systems, naming the workbenches designers need for the problems ahead, so that the important ones don't get ignored.
Physical matter, form, manufacturing, supply chains
How designs are experienced, perceived, used — delight vs drudgery
Ecology, organisms, food systems, growth and decay cycles
Durability, repair, emotional attachment, aging — craft and beauty that earn care
Computation, AI, machine intelligence — research partner, mixing catalyst, building accelerator
Environmental flows, carbon, power, climate — every design has a metabolism
Experience journeys, touchpoints, delivery — designed relationships between people and organizations
Where systems converge on real problems. You'll identify yours in Week 2.
Dear Data
Lupi & Posavec
Two information designers mailed hand-drawn data postcards to each other for a year. Each postcard has a legend, a personal data set, and a visual system invented from scratch. The constraint of drawing by hand forces you to slow down, interpret, and find the story.
Two information designers. One in NYC, one in London. Never met.
For one year: each week they collected data about their lives, drew it on a postcard, mailed it to each other.
Data about what you admire
Data about which design systems draw you
Data about what you value — and what you overlook
Data made visible by hand
A simple question — "how many drinks of water this week?" — produces a single number. Adding dimensions transforms it into a story.
Level 1: Simple count
37 drinks. One number. No story yet.
Level 2: Tagged by source
Cup, bottle, fountain. Now you see habits.
Level 3: Time + source + amount
A story emerges. Patterns you couldn't see from the number alone.
Your version: "20 favorite designs" is Level 1. Tagging by DIAD system is Level 2. The drawing is Level 3.
Each level adds a question. Level 1: What app? Level 2: How long, why? Level 3: When, what day, where? Level 4: Who was I with?
The more dimensions you track, the more the data reveals about patterns you didn't know you had.
Fill in your 20 favorite designs. Tag each by DIAD system.
| # | Design I Admire | Who Made It | DIAD System(s) |
|---|---|---|---|
| 1 | e.g., Aeron Chair | Herman Miller | Material, Longevity |
| 2 | e.g., Spotify Wrapped | Spotify | Artificial, Sensory |
| 3 | |||
| 4 | |||
| 5 | |||
| ... | |||
| 20 |
Systems: Material · Artificial · Natural · Energy · Sensory · Longevity · Service
✎
Your Dear Data drawing goes here.
Hand-drawn on handmade textured paper. With a legend.
Rough-sketch on regular paper first.
Final drawing on the handmade paper.
What do you cluster around? What's missing?
Place your instinct list (V1) next to your system-tagged drawing (V2). The comparison is the point.
Think of the worst designed product you've ever owned or used. Draw it. Make it ugly. No one will judge your drawing skills. Tag which system(s) it violated.
Grab someone you haven't met. Introduce yourselves and what you study. Tell them the system(s) your worst product violated. They get 5 yes/no questions to guess what the product is.
Now they tell you their violated systems. You ask 5 questions. Can you reason toward their answer through the systems?
Could you reason toward their product through the systems? What did the 5 questions reveal about how design failures cluster around specific systems?
Before Wednesday
Read + curate 20 + tag with SEMINAL
Wednesday
Theory + Setup + Studio
Due Monday April 6th
Data drawing + WIP doc + Gallery Slides
Read your assigned theory reading (this slide deck). Other readings are optional. Curate 20 favorite designs (expand your in-class list). Tag each with SEMINAL letters (S, E, M, I, N, A, L). Bring your tagged list to Wednesday. You can start sketching what a data drawing might look like but you don't have to. We'll have time in class to learn and explore.
Theory discussion (10 min): share key idea from your reading in ~2 min. Studio (80 min): handmade textured paper handed out. Rough-sketch on regular paper first. Begin your Dear Data drawing.
Set Up Your 3 Documents
You keep up three things all term. Set them up today:
1. WIP & Reflections Doc — your personal Google Doc (make a copy, rename with your name). One doc, tab per week. Everything goes here first: sketches, photos, reading reflections, data. Messy is fine.
2. Weekly Gallery Slides — shared class deck, find your name section. 3 polished slides per week. Copy/paste final work from your WIP doc. We present from this in class.
3. Weekly Reflection (starts Week 2; nothing due this week).
Drawing materials and handmade paper will be available Wed in class 4/1 and in the CoLab to borrow (ECSC 027).
Your WIP Doc — Week 1 section:
Photo of your in-class Worst Product Game drawing
Your list of 5 designs from the in-class exercise
Photos of rough sketches on regular paper
Tag your 20 designs with SEMINAL systems: Service · Energy · Material · Interactive/Sensory · Natural · Artificial · Longevity
Data table of your ~20 designs with SEMINAL tags
Week 1 Challenge Deliverables
Data Drawing: bring your completed physical data drawing to class for the gallery walk. We’ll put these up around the room to discuss and appreciate your peers.
Gallery Slides — your name section (3 slides):
Slide 1: Clean, well-lit, high-resolution photo of your final Dear Data drawing on the handmade paper (with legend — a key explaining what your shapes, colors, and marks mean)
Slide 2: Your data table (copy/paste from your WIP doc: #, design, who made it, SEMINAL tags, any columns you added)
Slide 3: Any patterns you noticed in the things you collected or columns you added that surprised you?
Don’t worry about getting everything right. Week 1 is just getting set up and getting started. See you Monday!
Photo tips: natural light, straight-on angle, no shadows. Most modern phones are fine.
Week 1
Required Reading
These slides with Altringer Eagle / DIAD Design Systems Survey — Expanding range of designer materials and methods to mix.
Further Reading
Lupi — "Data is not cold. Data is human traces made visible." Hand-drawn forces you to slow down.
Amabile — Three trainable components: domain skills, creative processes, task motivation.
Tufte — "Above all else, show the data." Restraint as a design skill.
Dear Data (Lupi & Posavec) — hand-drawn data postcards for a year. The imperfection is the point.
"Dear Data, Design Vision"
V1: Curate top 20 favorite designs. V2: Tag by DIAD system, draw as Dear Data drawing. Place side by side.
Due: Monday April 6th.
We’re going to start simple — with drawing — and learn to see details and attributes we might not have paid attention to before.
Habits of noticing and collecting great (and poor) examples of design, and being able to articulate and analyze them, will build your internal repository of design possibilities and expand what you can remix in your own mind without tools. These habits can be as simple as photos and notes. They’ll make you a better designer.
Norman, Emotional Design, 2004
Visceral
Your first reaction. Before you think. Color, shape, feel. “I want that.”
Behavioral
How well it works. Ease, effectiveness, satisfaction in use. “This just works.”
Reflective
What it means to you. Identity, story, pride. “This says something about who I am.”
“
Sketching is fundamental to ideation and design. Traditional disciplines such as industrial design, graphic design and architecture make extensive use of sketches to develop, explore, communicate and evaluate ideas.
— Tohidi, Buxton, Baecker, Sellen
User Sketches: A Quick, Inexpensive, and Effective Way to Elicit More Reflective User Feedback, NordiCHI’06
“
Many data visualization designers use old-fashioned sketching and drawing techniques on paper as their primary design tool: they sketch with data to understand what is in the numbers and how to organize those quantities in a visual way to gain meaning out of it.
— Giorgia Lupi
Information designer, partner at Pentagram. Co-creator of Dear Data.
Sketching with Data Opens the Mind’s Eye, 2016
Think more openly and creatively about your ideas
Create abundant ideas without fixating on quality
Invent and explore concepts visually — shapes, colors, marks that mean something specific to your data
Iterate quickly — rough-sketch on regular paper first, move to the handmade paper when something clicks
See patterns in your own taste that a list can’t show you
Archive ideas for later reflection — your WIP doc is your sketchbook
Week 1: Dear Data Drawing
Your ~20 favorite designs, tagged with SEMINAL. The drawing reveals what you gravitate toward — and what you overlook.
Weeks 2–10: Sketching as design tool
Journey maps, experience prototypes, system diagrams, rabbit hole documentation. Every week, you’ll sketch before you build. The hand discovers what the mind hasn’t formulated yet.
Choose ideas worth pursuing
Sketching lets you try many directions cheaply. Most won’t work. The ones that surprise you are the ones to develop.
When you draw your data by hand, you create from what you currently know. Then you read back what you drew — and see something you didn’t know was there. The drawing talks back to you.
A sketch is a simple designed product. You’re communicating through it — to yourself (what do I actually see in this data?) and to one another on Monday (can you read what I made?).
After Tohidi, Buxton, Baecker & Sellen, NordiCHI’06
You draw what you know. Reading it back shows you what you didn’t know you knew.
“
Images perceived as a set of signs.
Sender encodes information in signs.
Receiver decodes information from signs.
— Jacques Bertin
Sémiologie Graphique, 1967
Every mark on your paper can vary in these ways. Each one can encode a different dimension of your data. These are your visual alphabet.
Position
Where on the page
Size
Bigger = more
Shape
Category
Color (Hue)
Type, not quantity
Color (Value)
Light → dark = intensity
Orientation
Angle or direction
Texture
Fill, stripes, dots
Connection
Lines = relationship
Transparency
Faint → solid = emphasis
Enclosure
Boundary = grouping
Blur / Focus
Crisp vs. sketchy marks
Use your drawing as a way of measuring and capturing time. Set a timer and draw the following patterns until the time is up.
Musical notation is a visual encoding system. Every symbol maps to a specific instruction: pitch, duration, volume, articulation. Composers encode. Musicians decode. The score is the designed product.
Quarter
1 beat
Half
2 beats
Whole
4 beats
Eighth
½ beat
Sixteenth
¼ beat
Half Rest
silence
Whole Rest
silence
pp
Pianissimo
very soft
f
Forte
loud
ff
Fortissimo
very loud
Staccato
short, detached
Tie / Slur
connected
♯
Sharp
raise pitch
♭
Flat
lower pitch
Crescendo
get louder
Fermata
hold longer
Shape = duration. Position on staff = pitch. Left to right = time. Symbols = how to play. A complete visual encoding system — designed centuries ago, still in use.
Imagine a student curated 6 designs and tagged them:
| # | Design | Systems |
|---|---|---|
| 1 | iPhone | M, A, S |
| 2 | Patagonia jacket | M, L, E |
| 3 | Noma restaurant | N, S, I |
| 4 | Central Park | N, E, S |
| 5 | ChatGPT | A, S |
| 6 | Repair Cafe | L, S, M |
Questions this student might ask: Which systems do I gravitate toward? Are there gaps? Do my favorites cluster or spread?
Color hue → SEMINAL system
S=red, E=green, M=blue, I=orange, N=brown, A=purple, L=gold
Shape → how many systems it touches
2 systems = circle, 3+ systems = star or flower
Position → when you first encountered it
Left = childhood, right = recent. Timeline of your taste.
Size → how much it matters to you
Big = life-changing, small = I admire it from a distance.
The legend explains your choices.
Without a legend, a data drawing is just a drawing. The legend is what makes it readable — by you later and by anyone else.
Your legend is the key that makes your visual choices readable. It should explain:
What each shape means
“Circle = 2 systems, star = 3+”
What each color means
“Red = Service, Blue = Material”
What position encodes
“Left = childhood, right = now”
What size encodes
“Bigger = matters more to me”
Look at the Dear Data postcards — every single one has a legend on the back. That’s not optional. It’s the design.
Federica Fragapane, Noise Pollution, 2020. Data visualization for La Lettura. In the collection of MoMA ↗
1. Look at your data table — your ~20 designs with SEMINAL tags.
2. Choose your visual variables. What will shape, color, size, and position each encode? Write these down first — this is your legend.
3. Rough-sketch on regular paper first. Experiment. Try different assignments. What reveals something interesting?
4. When you find a combination that surprises you, move to the handmade paper.
The goal is not a beautiful drawing. It is a legible one that inspires a conversation you can learn from.
The goal is a drawing that shows you something about your taste that you didn’t see in the table. Beauty comes from the clarity of the system you invent.