Task-Independent Features for Automated Essay Grading

Citations Over TimeTop 10% of 2015 papers

Abstract

Automated scoring of student essays is increasingly used to reduce manual grading effort. State-of-the-art approaches use supervised machine learning which makes it complicated to transfer a system trained on one task to another. We investigate which currently used features are task-independent and evaluate their transferability on English and German datasets. We find that, by using our task-independent feature set, models transfer better between tasks. We also find that the transfer works even better between tasks of the same type.

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