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numeric_notes_future.txt
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numeric_notes_future.txt
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Edit: test
Day 1:
Class goals:
- students understand the structure of the course
- introduce students to teaching team
- students start getting to know each other
- each student introduces themselves
- preferred name and pronouns
- grad/undergrad, major
- why they're taking the course
- where they put themselves on a
All slides/links on canvas website/github website.
Rachel: introduction to course - structure, grading, us, students introduce themselves.
- Office hours checks, who can't make Wed (R time), who can't make T (SA time), who can't make both.
Susan: introduction to notebooks, how to read lab 1, set up environment
TODOS:
1. Both: Prep Day 1.
2. Susan: to redo grad syllabus optional labs - combination that adds up to 10 (previously 20).
Lab 9 stays as a 5-point lab.
3. Rachel: Re-write ungrading of assignments in both syllabus.
- add final grade
- graded within a week
- resubmission 2 weeks after initial submission date
- Explicitly link syllabuses to canvas, publish canvas page. Hide "syllabus"
4. Understand how to reassign assignments with dates - Cameryon to submit lab 1 as test student
- Find materials - day 1 recording etc?
- Prep Day 2: RHW: numpy and jupyter, SA: group work
Meeting Jan 4th.
Decisions made:
1. Use un-run jupyter notebooks for website, only after Doug has confirmed they will work.
2. Assignment canvas grading:
Unsatisfactory = 0
Satisfactory = 8
Excellent = 10
Flexibility on resubmission timelines for accommodation
Final grade:
Undergraduates:
4 or more submissions at 'Excellent', none 'Unsatisfactory': 100%
2 or more submissions at 'Excellent', none 'Unsatisfactory': 90%
1 or fewer 'Excellent', none 'Unsatisfactory': 80%
1 'Unsatisfactory' submission: 70%
2 'Unsatisfactory' submissions: 60%
3 'Unsatisfactory' submissions: 50%
4 or more 'Unsatisfactory' submissions: 0%:
Graduates
5 or more submissions at 'Excellent', none 'Unsatisfactory': 100%
3 or more submissions at 'Excellent', none 'Unsatisfactory': 90%
1 or fewer 'Excellent', none 'Unsatisfactory': 80%
1 'Unsatisfactory' submission: 70%
2 'Unsatisfactory' submissions: 60%
3 'Unsatisfactory' submissions: 50%
4 or more 'Unsatisfactory' submissions: 0%:
Meeting Oct 5th 2023:
- two project presentation dates (one on Apr. 15th, day before exams start - students can choose which to present at)
- Change iPeer first evaluation for grads and undergrads
- Add student hours to website: RHW Wed (time tbd); SA Thurs (time tbd)
Meeting Aug 2023:
Add 'student hours' on Wed/Thurs, one hour each with Susan, Rachel, TA.
Assignments due on Friday. New schedule created - SA to add to new website.
Grads: Optional labs: combination that adds up to 10 (previously 20).
Lab 9 stays as a 5-point lab.
Grad mini-project based on UG mini-project, with time dependence added.
Meeting Jul 2023:
New UG grading:
Labs -> 20%
Mini-projects -> 30%
Gs
Labs -> 15%
New mini-project -> 15% (based on Lab 4?)
- One due date for assignments (after the class)
- Ungraded assignments: first submission gets feedback only, no grade; second submission requires a changes summary at the top describing how they have responded to the feedback. Grade is S or U. Need n-1 S grades to get full marks.
- Projects include self-evaluation and self-grade
Worksheets
- check where we can add scaffolding
- emphasize they are opportunities for learning, graded for participation, but might be a bit stressful in the moment for those with less coding experience - try to use these as learning opportunities.
Labs and assignments
- go through all to check learning goals (put into slides for class introduction to lab)
- check lab hits the learning goals
- check assignments are testing the learning goals (don't add any problems though!)
- create lecture summary of labs/assignments showing learning goals and how they should have reached them
Classes
- include ~10 minute summary of worksheets towards the end of the class
- include explicit time to ask questions on the upcoming lab assignment: include overview of learning goals of the lab
- include summary of previous lab assignment, and the main points they should have taken from it.
Previous thoughts
Instructions for uploading of labs - upload pdf file separately. Can include ipynb and code in zip file, or individual files, but pdf MUST be separate.
(lose 0.5 marks if a pdf file isn't uploaded separately!). Show example on canvas to show what it looks like for us, and why we are requesting this.
Hand in JUST the questions from the assignment, not the entire lab. Preference to also include any .py or .yaml files that are required for your
.ipynb to run - this way we can provide feedback on code and/or help debug code that is incorrect.
Update Assignment 6 for undergrads on Canvas
Worksheet 2 - needs more scaffolding, what are we trying to solve and why. (try to scaffold enough that we don't need to go through it afterwards).
Lab 5 - some questions don't seem to make much sense with the default values in the .yaml files. Needs some re-thinking.
Replace problem estimate in the assignment with a different problem. Give more scaffolding aroudn the predator problem.
Mini-project 2 (undergrads). Add 'new equations for Daisy World' in list of requirements. Add rubric for this.
Add rubrics for all labs?
Add to Assignment 9 to make equivalent to other 10-mark assignments. Update solutions to Assignment 9 (Anya).
For grads (undergrads?):
Project proposal -> 5 marks
Project presentation -> 5 marks
Project -> 50 marks