Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer Grading

Understand

Automatic Short Answer Grading (ASAG) is the process of grading the student answers by computational approaches given a question and the desired answer.

• Previous works implemented the methods of concept mapping, facet mapping, and some used the conventional word embeddings for extracting semantic features.
• They extracted multiple features manually to train on the corresponding datasets.
• We use pretrained embeddings of the transfer learning models, ELMo, BERT, GPT, and GPT-2 to assess their efficiency on this task.