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Behavioural cloning of teachers for automatic homework selection

Accepted version
Peer-reviewed

Type

Conference Object

Change log

Authors

Moore, R 
Buttery, P 

Abstract

© Springer Nature Switzerland AG 2019. We describe a machine-learning system for supporting teachers through the selection of homework assignments. Our system uses behavioural cloning of teacher activity to generate personalised homework assignments for students. Classroom use is then supported through additional mechanisms to combine these predictions into group assignments. We train and evaluate our system against 50,065 homework assignments collected over two years by the Isaac Physics platform. We use baseline policies incorporating expert curriculum knowledge for evaluation and find that our technique improves on the strongest baseline policy by 18.5% in Year 1 and by 13.3% in Year 2.

Description

Keywords

Homework selection, Behavioural cloning, Deep learning

Journal Title

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

Conference Name

20th International Conference on Artificial Intelligence in Education

Journal ISSN

0302-9743
1611-3349

Volume Title

11625 LNAI

Publisher

Springer International Publishing
Sponsorship
Cambridge Assessment