Deep Learning Based Automatic Answer Scoring Through Bi-Directional LSTM

Abstract

Due to population expansion and the increasing importance of education, it is becoming increasingly difficult for assessors to evaluate the correctness and relevance of the responses provided by students. The LSTM model was initially used to build the answer-scoring system. The Bi-LSTM model has been designed with callbacks to acquire the student answer scoring system due to the LSTM's limitations for optimal scoring. The proposed system has been implemented using the ASAP Short Answer Scoring dataset. The results show that the system developed using Bi-LSTM displays better performance than LSTM.