Detecting Off-topic Responses to Visual Prompts
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Authors
Rei, Marek
Publication Date
2017-09-08Conference Name
Workshop on Innovative Use of NLP for Building Educational Applications
Language
English
Type
Conference Object
This Version
AM
Metadata
Show full item recordCitation
Rei, M. (2017). Detecting Off-topic Responses to Visual Prompts. Workshop on Innovative Use of NLP for Building Educational Applications. https://doi.org/10.17863/CAM.21368
Abstract
Automated methods for essay scoring
have made great progress in recent years,
achieving accuracies very close to human
annotators. However, a known weakness
of such automated scorers is not taking
into account the semantic relevance of
the submitted text. While there is existing
work on detecting answer relevance
given a textual prompt, very little previous
research has been done to incorporate
visual writing prompts. We propose a
neural architecture and several extensions
for detecting off-topic responses to visual
prompts and evaluate it on a dataset of
texts written by language learners.
Sponsorship
Cambridge Assessment (unknown)
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.21368
This record's URL: https://www.repository.cam.ac.uk/handle/1810/294966
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