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AD217

Intro to Advertisign and Digital Design (A&DD)

Fall

Professor

C.J. Yeh
Co-chair, Advertising & Digital Design Curriculum
Founder and Executive Creative Director, Cynda Media Lab [➚]

Instagram
_cjny [➚]

Course Description

This course introduces students to the concepts, methodologies, and creative processes of advertising and digital design. Students are presented with brand communication challenges and learn to work in the new creative team of art directors, copywriters, and experienced designers.

A&DD Student Work Examples
ExperienceDesign.NYC [➚]

A&DD Instagram
NewCreatives.info [➚]

New Creatives (Medium)
New Creatives [➚]

Grade Breakdown and Evaluation

  • Professionalism, Teamwork, and Weekly Progress Uploads: 60% (4% per week)

  • Phase 1: 12.5%

  • Phase 2: 15%

  • Phase 3: 12.5%
    (A: 91% or above, B: 90% – 71%, C: 70% – 61%, D: 60% – 51%, F: 50% or below)
    * You will work in teams in this class, but you will be graded as an individual

Section Info
Section 104 / Tue 2:10 - 5:00 PM / Class Drive [➚]
Section 103 / Wed 3:10 - 6:00 PM / Class Drive [➚]

!! Create Weekly Folder and Upload Progress Every Week !!

Office Hours
Schedule a meeting with CJ via Calendly [➚]

Phase 1: Digital Product Design (Intro to UX)
Each student team will develop one digital product concept to solve a problem starting with choosing a specific community and interviewing people to find their biggest daily challenge and/or concerns.

Phase 2: Brand and UI Design
Each student team will develop a brand positioning and visual system for their digital product.

Phase 3: Brand Storytelling
In this final phase, you will develop an innovative brand campaign that communicates the brand’s purpose and its value propositions in a way that is both engaging and memorable.

WEEKLY OUTLINE
* Weekly outline is subject to change according to the pedagogical needs.

WEEK 1
Tue 09/01 | Wed 09/02

  • Introduction of the course and syllabus

  • Lecture/Discussion: What is Advertising & Digital Design?

  • Project Phase #1: Digital Product Design (Intro to UX)
    Each student team will develop one digital product concept to solve a problem starting with choosing a specific community and interviewing people to find their biggest daily challenge and/or concerns.

  • Lecture/Discussion: What Is Digital Product Design?

  • Lecture/Discussion: Design Research 101

  • In-class workshop:
    - Team forming
    - Define your target audience

  • Lecture/Discussion: Problem Framing (persona, POV)

  • In-class workshop / Homework:
    - Point-of-View (POV)

WEEK 2
Tue 09/08 | Wed 09/09

  • First Presentation: Problem Worth Solving

  • Lecture/Discussion: Competitor Analysis

  • Workshop: Competitor Analysis Worksheet

  • Homework:
    - Competitor Analysis Presentation

WEEK 3
Tue 09/15 | Wed 09/16

  • Empathy Interview Techniques

  • Design Thinking Exercise: The Wallet Project

  • Workshop: Empathy Interview Questions and Planning

  • Lecture/Discussion: Affinity Mapping

  • In-class Workshops: Affinity Map

  • Lecture/Discussion: JTBD

  • In-class Workshops: JTBD Statements

  • In-class Workshops: Ideation Workshop

  • Lecture/Discussion: Minimum Viable Product (MVP) & Competitor Analysis

  • Homework:
    - Competitor analysis
    - Interview 2 to 3 people and get feedback on your feature ideas
    - Draft your MVP worksheet
    - Update your final project deck and add JTBD statements, competitor analysis, and MVP worksheet

WEEK 4
Tue 09/22 | Wed 09/23

  • Lecture/Discussion: Wireframe and Sketches

  • Lecture/Discussion: Task flow

  • Team review: MVP Worksheet

  • In-class Workshop
    – Task flow and sketches

  • Lecture/Discussion: User Testing / Paper Prototyping

  • In-class Workshop / Homework:
    - Complete sketches
    - User feedback (minimum three per feature)
    - Revise sketches based on feedback

WEEK 5
Tue 09/29 | Wed 09/30

  • Lecture/Discussion: Branding 101 (purpose branding)

  • In-class Workshop
    – Brand purpose (Big IdeaL)
    – Brand name

  • Lecture/Discussion: Brand Archetype

  • In-class Workshop / Homework:
    - Review competitor analysis
    - Brand Archetypes
    - Brand pillars

WEEK 6
Tue 10/06 | Wed 10/07

  • Midterm Presentation Workshop

WEEK 7
Tue 10/13 | Wed 10/14

  • Mid-term Presentation

WEEK 8
Tue 10/20 | Wed 10/21

  • Lecture/Discussion: Brand Design #1

  • Demo: Figma #1

  • In-class Workshop / Homework:
    - Brand visual fundamentals

WEEK 9
Tue 10/27 | Wed 10/28

  • Lecture/Discussion: Brand Design #2

  • Demo: Figma #2

  • In-class Workshop / Homework:
    - Brand visual design

WEEK 10
Tue 11/03 | Wed 11/04

  • Lecture/Discussion: Brand Design #3

  • Demo: Figma #3

  • In-class Workshop / Homework:
    - Brand visual design + UI design

WEEK 11
Tue 11/10 | Wed 11/11

  • Lecture/Discussion: Is advertising dead?

  • Lecture/Discussion: The many faces of new creatives

  • In-class Workshop / Homework:
    - UI design
    - Campaign concepts

WEEK 12
Tue 11/17 | Wed 11/18

  • Lecture/Discussion: Art director vs designers

  • Lecture/Discussion: The future of brand communications

  • In-class Workshop / Homework:
    - UI design
    - Campaign design

WEEK 13
Tue 11/24 | Wed 11/25

  • Team review

  • In-class Workshop / Homework:
    - Final presentation prep

WEEK 14
Tue 12/01 | Wed 12/02

  • Team review

  • In-class Workshop/Homework:
    - Final presentation prep

WEEK 15
Tue 12/08 | Wed 12/09

  • Final Presentations

Creative Technology & Design (CT&D) Attendance Policy

Attendance is not optional. If you are going to miss a class, you must contact me via email ASAP. Due to the quantity of material covered in the course, I will not be able to spend class time explaining missed assignments or redo lectures. If a class is missed, it is your responsibility to get information regarding missed assignments and lectures from one of your classmates.

  1. Students are required to attend all classes, be on time, and remain for the entire class.

  2. Students who miss three classes for classes meeting once a week or four classes for classes meeting twice a week will receive a grade of “F.”

  3. The student who arrives 10 minutes after the start of the class will be considered late.

  4. Two late occurrences = one absence

  5. A student who arrives over 30 minutes late or not returning from the break will be considered absent from the class.

  6. Working on projects for another class or using digital devices for socializing (texting, social media…etc.) or gaming during class time will be recorded as an absence.

  7. An excused absence is still recorded as an absence. The difference is an excused absence won’t impact your grade for professionalism and class participation.

Additional Course Information:
Department Policy on Plagiarism

Plagiarism and other forms of academic deception are unacceptable. Each instance of plagiarism is distinct. A plagiarism violation is an automatic justification for an “F” on that assignment and/or an “F” for the course. A student found in violation of FIT’s Code of Conduct and deemed to receive an “F” for a course may not withdraw from the course prior to final grade assignments.

Use of AI tools

It is permissible to utilize AI tools in your creative process. However, you must identify which AI tool is being used at each stage of the process. You are required to fact-check AI output and avoid stereotyping and bias in your work. Finally, you are responsible for ensuring that the final creation is unique, ownable, and without any copyright issues.

Fact-checking AI output

AI tools are not infallible. They often generate incorrect or misleading information. It is your responsibility to fact-check any AI output before using it in your work. This includes checking the source of the information, evaluating the quality of the information, and considering the context in which the information was generated.

Avoiding stereotyping and bias

AI tools can be trained on data that contains stereotypes and biases. This can lead to AI output that is also biased. It is your responsibility to avoid the potential for bias in AI output. You should also be mindful of your own biases when using AI tools and take steps to mitigate them.

Ensuring the uniqueness and ownership of your work

You are responsible for ensuring that the final creation of your work is unique and ownable. This means that you must not plagiarize the work of others, including submitting works done solely by AI tools without meaningful improvement and input from you.

Penalty for violation

Violation of this policy may result in a grade reduction or suspension from the class.