Paper Type

Short

Paper Number

1512

Description

This study aims to develop an automatic short-answer grading system. The focus is on achieving few-shot learning in short-answer grading, tackling the scarcity of labeled data. We utilize a two-head pseudo-Siamese neural network with an external knowledge model for transfer learning to enhance the system's ability to extract key information in the student answers for the automatic grading. The experiments are performed on real data, and the results show that the proposed system can effectively achieve the objective with a high accuracy.

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Jul 2nd, 12:00 AM

Automatic Short-Answer Grading with a Pseudo-Siamese Neural Network

This study aims to develop an automatic short-answer grading system. The focus is on achieving few-shot learning in short-answer grading, tackling the scarcity of labeled data. We utilize a two-head pseudo-Siamese neural network with an external knowledge model for transfer learning to enhance the system's ability to extract key information in the student answers for the automatic grading. The experiments are performed on real data, and the results show that the proposed system can effectively achieve the objective with a high accuracy.

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