Automatic Scoring

Automatic scoring uses machine learning, particularly large language models (LLMs) and convolutional neural networks (CNNs), to automate the grading of various assessment types, including written responses, drawings, and even medical images. Current research focuses on improving accuracy and efficiency, often through techniques like parameter-efficient fine-tuning and knowledge distillation to adapt LLMs for specific tasks and reduce computational demands. This technology offers the potential to significantly reduce the time and cost associated with manual grading, enabling faster feedback for students and more efficient analysis of large datasets in education and other fields.