Task-Independent Features for Automated Essay Grading
Torsten Zesch, Michael Wojatzki, Dirk Scholten-Akoun · 2015
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.