Peer Assessment

Peer assessment, the process of using non-expert evaluations to judge work, is undergoing significant transformation driven by advancements in artificial intelligence. Current research focuses on improving the reliability and validity of peer assessments, particularly in massive online courses (MOOCs), by leveraging large language models (LLMs) and graph convolutional networks (GCNs) to automate grading and enhance accuracy. These methods aim to mitigate biases, strategic behavior, and the inherent noise in peer evaluations, ultimately leading to more efficient and equitable assessment processes across various fields. The resulting improvements in assessment accuracy and efficiency have significant implications for education, scientific publishing, and other domains relying on peer review.