CT400 65A (S24)

Digital Product Design II

Date & Time: Wednesday 5:30 pm – 8:20 pm (upon student’s agreement)
Semester: Spring 2024
Professor: Christie Shin
Design Studio: Cynda Media Lab
Program Portfolio: @newcreatives.info (Instagram), Behance
Email: christie_shin@fitnyc.edu
Classroom: D514
Office at FIT: D317 (email to schedule a remote meeting)
Office Hours: Monday 1 to 2, Tuesday 5 to 6, Wednesday 4 to 6
Prerequisite(s):  CT302 Digital Product Design I
Slack: Please join the class Slack channel. This is the main communication hub.
FIT Help Desk: TechHelp

Course Description
This course introduces advanced digital product design concepts. The primary goal of the course is to learn how to solve product design challenges with User Experience (UX) design knowledge.

Student Learning Outcomes
Upon completion of the course, students will be able to:

  1. Apply UX design principles to solve design challenges
  2. Understand what product thinking is
  3. Synthesize product research findings and conceptualize a digital product 
  4. Apply branded experience to digital product design
  5. Create high-fidelity prototypes to communicate digital product design features and functionalities 
  6. Create persuasive presentations for digital product concepts.

Projects
Project 1: Design a Digital Product
D&AD briefs
Students pick one of the D&AD briefs and propose a digital product concept.
Project 2: Create a Self-promotion card as a digital product designer
Project 3: Create an in-depth 2nd Interview presentation deck

Updated Projects & Evaluation
1. Project 1 (50 points): D&AD brief
2. Project 2 (15 points): Self-promotion
3. Project 3 (15 points): 2nd Interview presentation deck
4. Professionalism (25 points): Attendance, participation, presentation, etc.

A/A-: 90% or above (A 95 points above, A- 90-94 points)
B+/B/B-: 89% – 75% (B+ 89-85 points, B 84-80 points, B- 79-75 points)
C+/C/C-: 74% – 60% (C+ 74-70 points, C 69-65 points, C- 64-60 points)
D: 59% – 51%
F: 50% or below

Weekly Outline
Weekly outline is subject to change according to the pedagogical needs.

Week 1: 1/31 WED
1. Pre-preparation: Project brief (discover & define)
2. Presentation: A selected brief (10 min): Research findings, target persona, empathy interview, etc.
3. Homework:
– HMW + HMW answers
– Ideas + selected ideas
– MVP list (pick 2-3 ideas)

Week 2: 2/7 WED
1. Introduction – syllabus
2. In-class workshop: Group review
– HMW + HMW answers
– Ideas + selected ideas
– MVP list (pick 2-3 ideas)
3. Homework: Ideate
– Define features
– Task flow
– Sketches/wireframes

Week 3: 2/14 WED
1. In-class workshop: Group review
Ideate
– Define features
– Task flow
– Sketches/wireframes
2. Homework: Case study script & storyboard

—— 2/19 Presidents Day – College closed ——

Week 4: 2/21 WED
1. In-class workshop: Group review
– Feature development
– Case study script & storyboard
2. Homework: Design & development

Week 5: 2/28 WED
ADC/TDC deadline: 3/1

1. In-class workshop: Group review
– Design & development
2. Homework: Design & case study video

Week 6: 3/6 WED
1. In-class workshop: Group review
2. Homework: Case study video & presentation

Week 7: 3/13 WED
1. In-class workshop: Group review
2. Homework: D&AD submission

Week 8: 3/20 WED
D&AD submission presentation
Course Deadline: 3/19 (3/20 5PM GMT)

—— 3/25-3/31 Spring Recess – College closed——

Week 9: 4/3 WED
1. Lecture: Project 2 Introduction
2. In-class workshop: Planning
2. Homework: Round 1

Week 10: 4/10 WED
1. In-class workshop: Project review
2. Homework: Round 2

Week 11: 4/17 WED
Presentation: Self-promotion
1. Lecture: Project 3 Introduction

Week 12: 4/24 WED
1. In-class workshop: Project review
2. Homework: Round 1

Week 13: 5/1 WED
1. In-class workshop: Project review
2. Homework: Final

Week 14: 5/8 WED
Presentation

Week 15: 5/15WED
Mentorship: Mentor session

Keep and backup all the projects that you have done throughout the semester! You must submit all your projects for the final grade no later than the last day of class (Week 15)

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.

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.

FIT Student Code of Conduct
Student Disability Services
Academic Honesty and Integrity Policy
FIT’s Course Withdrawal Policy 
Children on campus policy
FIT-ABLE 
Academic Advisement Center 
FIT Writing & Speaking Studio
FIT Counseling Services
Academic Skills Tutoring Center
Dean of Students Office
Technical Support for Blackboard with Open SUNY Help Desk

Additional Course Information:
Credits/Hours: 2/3
Grade appeal process: http://www.fitnyc.edu/registrar/grades/appeal.php for more information.
Library Resources: FIT Library Databases
Academic Advisement Center: http://www.fitnyc.edu/academic-advisement/index.php
Technical Requirements: High-speed internet and Adobe CC
Textbooks and Required Materials: Lecture slides will be provided every week after class,