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Adaptive Forgetting Curves for Spaced Repetition Language Learning

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Zaidi, A 
Moore, R 
Buttery, P 

Abstract

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.

Description

Keywords

Spaced repetition, Language learning, Forgetting curve, Neural networks, Adaptive learning

Journal Title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Conference Name

The 21st International Conference on Artificial Intelligence in Education

Journal ISSN

0302-9743
1611-3349

Volume Title

12164 LNAI

Publisher

Springer International Publishing

Rights

All rights reserved
Sponsorship
Cambridge Assessment (unknown)
Cambridge Assessment