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Week 1
Class Preparation
Please complete the following material before Class 1 on Tue Sep 2 @ 3:00pm.
Videos:
- Part 1: Preface (03:31)
- Part 2: Command Line Intro (11:04)
- Part 3: Command Line Primer (22:01)
- Part 4: VSCode (11:48)
- Part 5: Web Server (11:11)
Total video time: ~1 hour
Tip: Click Details in Panopto to see topic timecodes for the videos
Notes:
- Programmer’s Mindset
- Infrastructure
Reading:
Class Agenda
Introductions
- Garth (garthcoombs@fas.harvard.edu)
- Drop-in office hours Tuesdays 11am-12pm in WJH 840
- Meetings by appointment https://bit.ly/GarthOfficeHours (mix of in person & Zoom)
- Susan (susanbuck@fas.harvard.edu)
- Drop-in office hours Tuesdays 6-7pm WJH 960
- Zoom by appointment
- Students
- What’s a skill you’re excited to develop this semester (inside or outside of this course)?
- What is a problem you’ve faced recently (significant or insignificant) and what strategies did you use to address it?
Course Goals
- Build a foundation of psychology-relevant coding skills including how to think and problem-solve like a programmer, as well as organize and share work in an efficient and reproducible manner.
- Learn foundational skills in the programming languages JavaScript & R and understand how they can be utilized in psychological research.
- Implement these coding skills to create online behavioral experiments (JavaScript) and efficiently wrangle and analyze data (R).
- Practice productive collaboration by working with, and learning from, peers
Logistics
Syllabus, deliverables, etc...
AI Discussion
- RE: Between Tool and Trouble: Student Attitudes Toward AI in Programming Education - what was studied, procedure, findings/conclusions
- How has AI impacted your education and learning experiences so far?
- What is cognitive debt and are there areas of your life where you’ve felt its effects?
- Who has experience programming pre-AI and how would you compare it to programming with AI?
- Have you encountered examples where AI “lead you astray” with inaccurate or unhelpful information?
- What policies/strategies on AI have you encountered in other courses and how did you find them useful or not useful?
- Course policy/goals with AI:
- Scaffold
- Skill to be practiced
- Purpose of code chats
- Balance
Task Sets
- Complete via Gradescope
- Released Tuesdays at the start of class; submissions due Thursdays by 11:59pm.
- Contain questions that pull from the notes/videos/readings you worked through in preparation for class as well as exercises that allow you to practice with the material for that week
- You will work with a peer in class to complete the work, but each student will submit their own individual task set.
- Any portion of the task set not completed in class should be finished at home.
- Link to the Week 1 Task Set (Due Thu Sep 5 11:59pm)