Session 11 - The Grand Final
Wrapping it all up. Discussing AI use in university teaching.
Overview
| Topic | Duration | Notes |
|---|---|---|
| Consensus rating new writing assignment | 30 | |
| Look at some exploratory analyses | 20 | |
| Wrap-up / Final steps | 10 | |
| Open Q&A | 15 | |
| Feedback | 15 | |
| From shortcut to scaffold: AI use for learning, not just output | 90 | Slides |
Final steps
- Upload videos to OSF? –> licence unclear. Define instructor as contact person.
- Upload data, codebook, & scripts to OSF? When the data set is complete and final texts are coded. Instructor will do it.
Wrap-up
What have we done?
- Replication crisis & learned how to p-hack
- Doing a reproducibility check with the original data
- Doing a direct replication, including participant acquisition and creating a coding manual
- Actually reading a consent form; enabling open data
- Writing a preregistration with a good template
Skills:
- File versioning in git
- Collaboratively working in Github
- Work in OSF: Projects, open material, preregistration
- Doing a realistic power analysis (divide by 2 approach)
- Using formr to create an online study
- Good coding practices + file and folder organization
- Writing reproducible, dynamic manuscripts in Quarto
- Creating a state-of-the-art data dictionary (codebook)
- Positron preview
Course report
- Today’s data set version, as uploaded in my template repository is defined as the final version for your report. (For submitting our data to CREP, we will probably have a larger data set.)
- Create your individual Github repository with your data analysis. This can be based on my template.
- Can be public or private. If private, invite the instructor as collaborator.
- It should contain an individualized README with your contact information.
- Link to your repository at the beginning of the Methods section.
- It should contain one individual (exploratory) analysis, which also is described in the course report.