Vocabulary Networks: Program-11
This simulation illustrates the effect of turning words OFF.
Use NTWK to set up a model vocabulary.
nEv controls the number of events in the in the simulation.
sEv controls the how many words are affected by an event.
rEv determines which words are affected by an event.
THINGS TO DO.
Find a network with a high level attractor state.
Set the value of nEv to 10 and set sEv to 5. This will
give you a simulation where your network experiences
10 events and 5 words are turned OFF in each event.
QUESTIONS TO ASK.
Is there any evidence for long term vocabulary loss
with these parameter values?
Does a larger number of events lead to long-term
vocabulary loss?
Do bigger events lead to long term vocabulary loss?
Can you find a combination of values for nEv and sEV
that always results in a permanent loss of activity
in the model vocabulary?
How long do the effects of an event typically last for?
What implications does this set of behaviours have
for theories of L2 vocabulary acquisition?