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- W3029171567 abstract "Objective To study the applicability of BP neural networks model in the Learning effects evaluation of the WPBL. Methods In this study, based on the data collected through questionnaires, we built the BP neural network model according the test samples and measured training samples according the model. Results The average error between the network output scores and the composite scores when using the test samples to build the model is less than the specified error （ E=0. 000031592〈0. 0001）. For the training samples, the average error between the network output scores and the composite scores very small. Conclusions BP neural network model can evaluate the WPBL learning effects accurately and quickly.Key words: Error back propagation algorithm（BP） ; Neural networks model; Web problem-basedlearning; Learning effects evaluation" @default.
- W3029171567 created "2020-06-05" @default.
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- W3029171567 date "2014-02-01" @default.
- W3029171567 modified "2023-09-25" @default.
- W3029171567 title "Learning effects evaluation of the WPBL based on BP neural networks model" @default.
- W3029171567 doi "https://doi.org/10.3760/cma.j.issn.1673-677x.2014.01.047" @default.
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