Automatic Short Math Answer Grading via In-context Meta-learning. (arXiv:2205.15219v2 [cs.CL] UPDATED)

Automatic short answer grading is an important research direction in the
exploration of how to use artificial intelligence (AI)-based tools to improve
education. Current state-of-the-art approaches use neural language models to
create vectorized representations of students responses, followed by
classifiers to predict the score. However, these approaches have several key
limitations, including i) they use pre-trained language models that are not
well-adapted to educational subject domains and/or student-generated text and
ii) they almost always train one model per question, ignoring …

arxiv context learning math meta meta-learning