A method to predict whether middle school students will enter STEM careers in the future based on FC-Wide&Deep model

• Autores: Yidan Lou, Peng Peng, Lei Cao
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 8, Nº. 1, 2023, págs. 2995-3008
• Idioma: inglés
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• Resumen

  • STEM education is a hot issue in modern education, and it is important to study whether middle school students enterSTEM careers in the future in the early stage of career planning. In this paper, we collected students’ behavioral datathrough the online tutoring platform ASSISTments, divided the raw log data into five types: single-valued, binary-valued,multi-valued, continuous-valued and cumulative, and aggregated them using different data reconstruction methods. Then,a width & depth prediction model based on feature crossover is proposed to perform feature crossover on the aggregateddata, and then the depth and width models are jointly trained using. During the training process, the AUC of the FC-Wide&Deep model improved rapidly from 0.800 to 0.845 in the 1st to 16th training rounds, and then slowly climbed withthe increase of training rounds. By averaging the results of the three tests, the AUC index of the FC-Wide&Deep modeltest results improved by 1.29% compared to the DNN model, and the RMSE index improved by 2.08% compared to theBSN-FM model. The FC-Wide&Deep model is generalizable and generalizable, and can be applied to predict whetherstudents will enter STEM careers in the future, thus contributing to the cultivation and leadership of STEM talents in thefield of education