Science Assessment

Science assessment research is rapidly evolving, driven by the need for more effective and efficient methods to evaluate student understanding of scientific concepts and practices. Current efforts focus on leveraging artificial intelligence, particularly large language models (LLMs) like BERT and GPT variants, to automate scoring of open-ended responses and generate assessment questions, often incorporating techniques like chain-of-thought prompting and knowledge distillation to improve accuracy and efficiency. These advancements offer the potential to reduce teacher workload, provide timely feedback to students, and enable more nuanced assessments that better capture complex scientific reasoning.