*Cubist Portrait 5: 3 Shaded Objects
1. Review Lesson Goals
Don't draw these objects, choose your own!
SWBAT:
1. Choose a subject for their cubist portraits.
2. Choose 3 or more objects to go with their subject.
3. Create a study of shaded drawings of the 3 objects (from observation)
2. Choose Subject
1. Self Portrait
2. Portrait of friend/family member
3. Celebrity
4. Historical Figure
3. Review Cubist Portrait Project Goals (if needed)
Remember, Assignment #5 "3 Shaded Objects" is just a study in preparation for the Cubist Portrait Project that we are starting with the next lesson.
Review Cubits Portrait Project goals if needed....Link
4. Choose Objects and Find References
• Find references for your drawings. Choose things that relate to the subject you chose for your Cubist Portrait (Your drawings are just studies in preparation for your Cubist Portrait.
1. Object(s) around the house
2. Internet searches
5. Abstract or Natural?
Don't forget, you don't have to make your drawings naturalistic!
6. Gather Supplies
1. Paper (white unlined preferred)
If you don't have white unlined paper, use whatever you have2. Pencil
If you don't have a pencil, use a pen or crayon7. Video Demonstrations
Email Ms. Hooker if you want a video demo of what need help drawing
mhooker@johndeweyhighschool.org
8. Extension/Modification
Draw more shaded drawings
9. Assessment
10. Submit
Submit your work through Google classroom only
Daily Question 4/8/20
How do some recent artworks/advertising designs show a Cubist influence?
NYC Visual Arts Benchmarks
• Art Making
• Developing Art Literacy
• Making Connections Through Visual Arts
• Community and Cultural Resources
• Exploring Careers and Lifelong Learning
Differentiation / Lesson Extension
...Students with different abilities can seek assistance from teacher, paraprofessional, or another student
...The students who finish early can ask a classmate if they need help or review
NYC VISUAL ARTS BENCHMARKS
• Developing Art Literacy
• Community and Cultural Resources
• Exploring Careers and Lifelong Learning