Hey AI Can You Grade My Essay?: Automatic Essay Grading
This addresses the problem of time-consuming manual essay grading for educators, but it is incremental as it builds on existing AEG methods with a hybrid approach.
The paper tackles automatic essay grading by introducing a model that uses collaborative and transfer learning to separate grammatical and idea-based scoring, achieving an accuracy of 85.50% and outperforming state-of-the-art models.
Automatic essay grading (AEG) has attracted the the attention of the NLP community because of its applications to several educational applications, such as scoring essays, short answers, etc. AEG systems can save significant time and money when grading essays. In the existing works, the essays are graded where a single network is responsible for the whole process, which may be ineffective because a single network may not be able to learn all the features of a human-written essay. In this work, we have introduced a new model that outperforms the state-of-the-art models in the field of AEG. We have used the concept of collaborative and transfer learning, where one network will be responsible for checking the grammatical and structural features of the sentences of an essay while another network is responsible for scoring the overall idea present in the essay. These learnings are transferred to another network to score the essay. We also compared the performances of the different models mentioned in our work, and our proposed model has shown the highest accuracy of 85.50%.