Research on Formative Evaluation Algorithm of Teaching Process Based on Algebraic Feature Analysis Model
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DOI: 10.25236/icemc.2019.092
Author(s)
Mu Yang, Yanmei Hu
Corresponding Author
Yanmei Hu
Abstract
In this paper, an analysis model for formative evaluation which based on fusion algebraic features from singular value decomposition and KL projection is constructed in the evaluation mechanism of teaching process. Firstly, the formative evaluation vector is used to describe the process of formative evaluation, and singular value decomposition (SVD) and KL transform are performed on the vectors. Then the transformed eigenvectors are linearly fused to form a new feature classification vector, which is used as the criterion of formative evaluation. The test results show that the method eliminates the influence of interference information in the evaluation process on the classification accuracy of final evaluation, and greatly improves the accuracy of formative evaluation in the teaching process.
Keywords
Formative evaluation, KL algorithm, SVD decomposition, Linear feature fusion