Regression or classification? Automated Essay Scoring for Norwegian

Stig Johan Berggren, Taraka Rama, Lilja Øvrelid


Abstract
In this paper we present first results for the task of Automated Essay Scoring for Norwegian learner language. We analyze a number of properties of this task experimentally and assess (i) the formulation of the task as either regression or classification, (ii) the use of various non-neural and neural machine learning architectures with various types of input representations, and (iii) applying multi-task learning for joint prediction of essay scoring and native language identification. We find that a GRU-based attention model trained in a single-task setting performs best at the AES task.
Anthology ID:
W19-4409
Volume:
Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | BEA | WS
SIG:
SIGEDU
Publisher:
Association for Computational Linguistics
Note:
Pages:
92–102
Language:
URL:
https://aclanthology.org/W19-4409
DOI:
10.18653/v1/W19-4409
Bibkey:
Cite (ACL):
Stig Johan Berggren, Taraka Rama, and Lilja Øvrelid. 2019. Regression or classification? Automated Essay Scoring for Norwegian. In Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 92–102, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Regression or classification? Automated Essay Scoring for Norwegian (Johan Berggren et al., 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-4409.pdf
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