Generative Grading: Neural Approximate Parsing for Automated Student Feedback

Ali Malik
Ali Malik
Mike Wu
Mike Wu
Vrinda Vasavada
Vrinda Vasavada
Jinpeng Song
Jinpeng Song

arXiv: Learning, 2019.

Cited by: 2|Bibtex|Views21
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Open access to high-quality education is limited by the difficulty of providing student feedback. In this paper, we present Generative Grading with Neural Approximate Parsing (GG-NAP): a novel approach for providing feedback at scale that is capable of both accurately grading student work while also providing verifiability--a property w...More

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