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Study of an Automatic Marking Algorithm for Subjective Questions in College English Exams Based on Deep Learning

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Abstract

Computer-assisted marking can reduce the work pressure on teachers. This paper briefly introduced the automatic English subjective question marking algorithm combined with the convolutional neural network + long short-term memory (CLSTM) algorithm. An attention mechanism was introduced to improve the CLSTM algorithm. The improved CLSTM-based automatic marking algorithm was simulated and tested, and it was compared with the convolutional recurrent neural network (CRNN)-based automatic marking algorithm and the traditional CLSTM-based automatic marking algorithm. The results indicated that the improved CLSTM-based automatic marking algorithm effectively recognized the text in the handwritten answer images and accurately graded answers to subjective questions.

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Authors and Affiliations

  1. College of Tourism Management, Henan Vocational College of Agriculture, 451450, Zhengzhou, Henan, China

    Mengyang Qin

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  1. Mengyang Qin
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Correspondence to Mengyang Qin.

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Mengyang Qin Study of an Automatic Marking Algorithm for Subjective Questions in College English Exams Based on Deep Learning. Aut. Control Comp. Sci. 57, 638–645 (2023). https://doi.org/10.3103/S0146411623060068

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