Interventions in the model

[parnumeric]

We do simulations of pupils' progress (math score) on different values of teacher_quality_mean (=tq_m) and teacher_control_mean (=tc_m) while keeping the best found values for the rest of parameters. We will change tq_m and tc_m by incrementing each of their values by 0.2*(tq_sd) or 0.2*(tc_sd) (increasing by a factor of their corresponding standard deviations) while keeping one of them constant and testing each combination of values 5 times (NUM_REPEATS=5). We will do every batch of incrementation (first, for one parameter, then for the other parameter, interchangeably) for 5 iterations (NUM_ITERATIONS=5) and see what happens with the math score of pupils at the end of a school year.

[parnumeric]

I'm also adding some new comments in the code to pave the way for future improvements of:

• maintainability,
• code modularisation,
• technical documentation.

For the sake of brevity, I'll use the following short names of the 19 parameters (an increase from 16 since I joined the project) we currently have for parameterisation:

1. tq_m for teacher quality mean,
2. tq_sd for teacher quality standard deviation,
3. tq_vsd for teacher quality variation standard deviation,
4. tq_cr for teacher quality convergence rate [NEW],
5. tq_ff for teacher quality feedback factor [NEW],
6. tc_m for teacher control mean,
7. tc_sd for teacher control standard deviation,
8. tc_vsd for teacher control variation standard deviation,
9. tc_cr for teacher control convergence rate [NEW],
10. rs for random select,
11. sl_f for school learn factor,
12. hl_f for home learn factor,
13. sl_md for school learn mean divisor,
14. sl_sd for school learn standard deviation,
15. sl_rp for school learn random proportion,
16. cf for conformity factor,
17. df for degradation factor,
18. mt_m for maths ticks mean,
19. mt_sd for maths ticks standard deviation.

[parnumeric]

So, our first intervention in the model will be modification of tq_m and tc_m as described in the beginning to see what happens with pupils' math score.

[parnumeric]

For the interventions, the outcome that we are interested in is the average maths score for the whole dataset. To be added in the table of parameters.