@article{somasundaran-etal-2018-towards,
title = "Towards Evaluating Narrative Quality In Student Writing",
author = "Somasundaran, Swapna and
Flor, Michael and
Chodorow, Martin and
Molloy, Hillary and
Gyawali, Binod and
McCulla, Laura",
editor = "Lee, Lillian and
Johnson, Mark and
Toutanova, Kristina and
Roark, Brian",
journal = "Transactions of the Association for Computational Linguistics",
volume = "6",
year = "2018",
address = "Cambridge, MA",
publisher = "MIT Press",
url = "https://aclanthology.org/Q18-1007",
doi = "10.1162/tacl_a_00007",
pages = "91--106",
abstract = "This work lays the foundation for automated assessments of narrative quality in student writing. We first manually score essays for narrative-relevant traits and sub-traits, and measure inter-annotator agreement. We then explore linguistic features that are indicative of good narrative writing and use them to build an automated scoring system. Experiments show that our features are more effective in scoring specific aspects of narrative quality than a state-of-the-art feature set.",
}
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<abstract>This work lays the foundation for automated assessments of narrative quality in student writing. We first manually score essays for narrative-relevant traits and sub-traits, and measure inter-annotator agreement. We then explore linguistic features that are indicative of good narrative writing and use them to build an automated scoring system. Experiments show that our features are more effective in scoring specific aspects of narrative quality than a state-of-the-art feature set.</abstract>
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%0 Journal Article
%T Towards Evaluating Narrative Quality In Student Writing
%A Somasundaran, Swapna
%A Flor, Michael
%A Chodorow, Martin
%A Molloy, Hillary
%A Gyawali, Binod
%A McCulla, Laura
%J Transactions of the Association for Computational Linguistics
%D 2018
%V 6
%I MIT Press
%C Cambridge, MA
%F somasundaran-etal-2018-towards
%X This work lays the foundation for automated assessments of narrative quality in student writing. We first manually score essays for narrative-relevant traits and sub-traits, and measure inter-annotator agreement. We then explore linguistic features that are indicative of good narrative writing and use them to build an automated scoring system. Experiments show that our features are more effective in scoring specific aspects of narrative quality than a state-of-the-art feature set.
%R 10.1162/tacl_a_00007
%U https://aclanthology.org/Q18-1007
%U https://doi.org/10.1162/tacl_a_00007
%P 91-106
Markdown (Informal)
[Towards Evaluating Narrative Quality In Student Writing](https://aclanthology.org/Q18-1007) (Somasundaran et al., TACL 2018)
ACL