A Study on a Deep Learning-Based Approach for Automated Scoring Solutions of Korean L1 Essays

• 발행기관: 한국교원대학교 뇌기반교육연구소
• 저자명: Surim Kim Sookki Choi
• 간행물 정보: 『Brain, Digital, & Learning』제14권 제4호, 633~652쪽, 전체 20쪽
• 주제분류: 사회과학 > 교육학
• 파일형태: PDF
• 발행일자: 2024.12.31

국문 초록

The study utilized 401 data points categorized into upper, middle, and lower levels. The model development process included five stages: 1) data purification and preprocessing, 2) embedding, 3) data segmentation and shape conversion, 4) model training, and 5) model performance evaluation. The research employed BERT, a pre-trained model, to develop the grading model. Performance evaluation of the trained model yielded an accuracy of 0.7377, precision of 0.6514, recall of 0.7377, and an F1 score of 0.6717. These results demonstrate a relatively high level of performance compared to previous studies on scoring Korean written and essay answers by L1 learners. As a result, the feasibility of developing an automatic scoring model using the BERT language model with small-scale data from a specific domain. Also, the model’s performance shows some generalizability, but further exploration is needed for improvement. Limitations of the study include the use of writing samples graded without considering grade levels, limited test data, difficulties in processing unregistered tokens, and the inherent unexplainability of deep learning techniques. Further discussions and considerations on how to more effectively utilize artificial intelligence in Korean language education should continue. Ongoing research on automatic grading is necessary to provide accurate and detailed educational feedback to students. As automatic grading research in the field of Korean language education advances, it is expected that high-quality educational interventions for students will become possible in the future.

목차

Introduction

Background

Method

Results and Discussion

Discussion

Conclusions

References

키워드

Automated essay scoring Korean essay scoring L1 learner writing deep learning artificial intelligence automatic grading AI automatic grading