Student performance prediction continues to be a focus of research in educational data mining due to its many potential benefits. While teachers’ assessment reports are a crucial part of the educational process, they have not been commonly used in performance prediction. We propose a model that uses similarity learning as an embedding-enhancing technique. Results outperform earlier research with an average accuracy of 73% for detecting strong performance.
CITATION STYLE
Fateen, M., & Mine, T. (2023). Using Similarity Learning with SBERT to Optimize Teacher Report Embeddings for Academic Performance Prediction. In Communications in Computer and Information Science (Vol. 1831 CCIS, pp. 720–726). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-36336-8_111
Mendeley helps you to discover research relevant for your work.