  The forgetting curve has been extensively explored by psychologists,
educationalists and cognitive scientists alike. In the context of Intelligent
Tutoring Systems, modelling the forgetting curve for each user and knowledge
component (e.g. vocabulary word) should enable us to develop optimal revision
strategies that counteract memory decay and ensure long-term retention. In this
study we explore a variety of forgetting curve models incorporating
psychological and linguistic features, and we use these models to predict the
probability of word recall by learners of English as a second language. We
evaluate the impact of the models and their features using data from an online
vocabulary teaching platform and find that word complexity is a highly
informative feature which may be successfully learned by a neural network
model.
