Based Assessment

Based assessment leverages artificial intelligence and machine learning to automate the evaluation of various data types, aiming for objective and efficient analysis that surpasses traditional methods. Current research focuses on developing robust models, including convolutional neural networks, generative adversarial networks, and large language models like GPT-3.5, to analyze diverse data such as medical images (e.g., radiographs, histopathology), student work (e.g., code, written responses), and other complex datasets. This approach holds significant promise for improving diagnostic accuracy in healthcare, enhancing educational feedback mechanisms, and streamlining data analysis across numerous scientific disciplines.