AUTOMATED SUBJECTIVE HANDWRITTEN ANSWER EVALUATION SYSTEM

The evaluation of handwritten subjective answers is a time-consuming and subjective process prone to inconsistencies and human bias. This paper introduces an Automated Subjective Handwritten Answer Evaluation System that utilizes Artificial Intelligence to enhance grading efficiency and precision. The suggested system uses Optical Character Recognition (OCR) to turn handwritten text into digital format and Bidirectional Encoder Representations from Transformers (BERT) to analyse the meaning of the text. The system compares student answers to pre-defined model answers to see how similar, relevant, and complete they are in context. The results of the experiment show that the new method is more consistent and takes less time to grade than the old method. The system can be used in large educational settings because it is scalable, gives quick feedback, and needs less human input. This method makes subjective answer evaluation much more fair, accurate, and efficient.