ISLAND · Wildfire drought task · Bayesian Knowledge Tracing

Fair-Test Mastery Tracer

Set up two zones and run the fire. Each run is coded the way the researchers code it, and BKT updates the estimated mastery of four skills live, as it could beside Hazbot in the browser.

Background reading

Model setup

Zone 1
Zone 2

This panel stands in for the model's Setup and spark tools. The page does not simulate fire spread; it codes and traces the setups. For the real model, use the live monitor.

Researchers' codes so far

level 2 —level 3 —sim_group 0

N nothing differs · O only drought differs · I one other setting · M several. Upper case = one spark in each zone. = identical rerun · * zones same, wind/sparks changed · + same comparison, tweaked. C = O then +.

BKT parameters (fitted on 852 students)

L0 prior mastery · T learning per attempt · G guess · S slip. The fair-test guess (0.01) and slip (0.30, at the fitting cap) show that standard BKT reads exploring after a fair test as forgetting.

Live estimate

Attempts
0
identical reruns are not counted
Fair-test mastery
13%
P(L), mastered at 95%
Next run is a fair test
13%
BKT prediction (AUC 0.72 on real data)
Trajectory
No attempts
 

Mastery by skill

Run log

#Zone 1 | Zone 2SparksWindCodeFair testP(L) after