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Appendix 1: course attendance

Procedure

I went through all the courses I teach and checked for all courses that collect data on both the number of registrations and attendance. Then I copy-pasted the data that was easy to obtain to this document, including a link to where I copy-pasted the data from.

From this, I created the data file attendance_rates.csv (also, from a copy-paste, then some quick ruthless editing). The plot was created by the script create_attendence_plot.R.

Bianca workshops

Course Iteration Course date Registered Showing up Evaluated
Beginner 4 2025-03-19 24 11 (46%) 11 (100%)
Intermediate 4 2025-05-22 3 3 (100%) 2 (66%)
Beginner 5 2025-09-15 23 12 (52%) 8 (67%)
Intermediate 5 2025-11-18 7 2 (29%) 2 (100%)
Beginner 6 2026-02-06 43 9 (21%) 8 (89%)
Intermediate 6 2026-05-22 16 4 (25%) 2 (50%)
Beginner 7 2026-98-17 49 4 (8%) ~3 (~89%)

Intro to UPPMAX

No Date Registered Showing up Evaluated Notes
3 2025-10-15 15 6 (40%) 6 (100%) Online
4 2026-01-19 17 8 (47%) 5 (63%) Online

NAISS Transfer 102

No Date Registered Present and active Evaluated
1 2026-05-11 14 3 (21%) 3 (100%)

Linux Command Line 102

No Dates n_reg n_learn n_eval
1 2025-06-02 and 2025-06-03 40 11 (28%) 11 (100%)
2 2025-12-04 and 2025-12-05 74 26 (35%) 15 (71%)
3 2026-02-04 64 19 (30%) 13 (68%)
4 2026-06-03 55 13 (24%) 7 (54%)

Programming Formalisms

Date Number of registrations Present and active
Autumn 2024 23 ~7 (30%)
Autumn 2025 15 ~6 (40%)

Connect and File Transfer

No Date Registered Showing up Evaluated
1 2025-03-07 37 9 (24%) 8 (89%)
2 2025-05-16 15 4 (27%) 3 (75%)
3 2025-09-05 29 15 (52%) 10 (67%)
4 2025-11-14 22 6 (27%) 5 (83%)
5 2026-02-02 64 25 (41%) 15 (60%)
6 2026-06-01 59 20 (34%) 14 (70%)
7 2026-06-14 52 22 (42%) 13 (59%)