Towards evaluating narrative quality in student writing
Transactions of the Association for Computational Linguistics, 2018•direct.mit.edu
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.
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
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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