Checklist
Using student evaluations fairly for early-career staff

A ten-point checklist for faculty boards, hiring panels and quality teams that review the teaching of PhD students, seminar tutors and lecturers on fixed-term contracts. It turns the bias and small-sample evidence into concrete rules: aggregate, add context, separate tutor from module, add non-rating evidence and avoid ranking. Use it when writing renewal guidance or assessing teaching in job applications. Koji can help supply the mid-term and qualitative evidence it calls for.
What's in this checklist
- Pool scores across modules and terms before judging a person
- Show the number of responses next to every mean
- Flag or suppress means below a minimum response count
- Report module type, class size, quantitative content and response rate
- Compare only tutors who taught the same module in the same term
- Ask section items only about what the tutor controls
- Add peer observation, a teaching statement and feedback samples
- Read open comments for patterns across many students
- Run a mid-term check that goes to the tutor and mentor only
- Use bands, not rankings, and never act on gaps of a few tenths
Use this image
Free to use in your docs, decks and posts under CC BY 4.0, as long as you credit Koji with a link to this page. To embed it, paste this into your page:
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<a href="https://www.koji.so/visuals/checklist-fair-use-student-evaluations-early-career-teaching-staff"><img src="https://www.koji.so/visuals/checklist-fair-use-student-evaluations-early-career-teaching-staff/checklist-fair-use-student-evaluations-early-career-teaching-staff.png" alt="Checklist showing ten steps for using student evaluations fairly when judging PhD tutors, teaching assistants and fixed-term lecturers" width="1080" height="1080" /></a>
<p>Source: <a href="https://www.koji.so/visuals/checklist-fair-use-student-evaluations-early-career-teaching-staff">Using student evaluations fairly for early-career staff</a>, Koji</p>

