Purpose & Goals
- Anticipate and resolve the most common blockers before they derail the course.
- Create and document fixes to improve the next run.
What Faculty Should Do (Step‑by‑Step)
- Create a ‘Known Issues’ page: IRB status, tech access, printing, data validation rules.
- Schedule two optional 1:1 clinics (weeks 4 and 9) for students who are behind.
- Adopt a data‑quality checklist (missingness <10%, valid ranges, units, unique IDs).
- Establish a backup plan: if data collection fails, switch to a vetted open dataset (have one set as a Plan B from the very beginning without telling the students as knowing about a Plan B might decrease their motivation to collect data themselves).
Concrete Examples
- Use data validation in the spreadsheet to force units and allowed ranges.
- If one group fails to collect, redistribute variables so every student still graphs something.
Troubleshooting & Tips
- Equity: offer private alternative assignments for students unwilling to self‑measure.
- Accessibility: ensure all templates are screen‑reader compatible and color‑blind safe.
Targeted Resources
- Excel ‘basic statistics’ and Python programming quick‑start guides.
- Sample open datasets list.
Recent Comments