Detecting Off-topic Responses to Visual Prompts
Workshop on Innovative Use of NLP for Building Educational Applications
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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
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.
Cambridge Assessment (unknown)
This record's DOI: https://doi.org/10.17863/CAM.21368
This record's URL: https://www.repository.cam.ac.uk/handle/1810/294966