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A wireless network-enabled online english subjective assignment evaluation system using micro cloud environment

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Abstract

Wireless networks have various applications in different sectors of life, such as industries, entertainment, agriculture, education, etc. However, its role cannot be ignored in the education sector, particularly in online teaching content sharing and online assignment submission systems. Wireless networks can offer real-time progress tracking and insights into student involvement and participation, especially in group assignments, and also help teachers identify the students who need more supervision and assistance. Keeping the significance of wireless networks in consideration, in this study, we investigated the usage of wireless networks for online subjective English assignments. We find out that wireless network-based online assignments provide prompt feedback; however, they fall short when compared to offline assignments in terms of depth, coherence, reflection, and review. To solve this problem, we proposed a convolutional neural network (CNN)-based solution for better text recognition that can successfully extract and identify English assignments from uploaded photographs. To be more precise, we developed an object-based under-representation (OUR) CNN model for the classification or labeling of input data, i.e., an English assignment. These techniques allow us to develop a system that automatically rectify English assignments by combining data matching and information extraction approaches. For the deployment of the proposed system, we used a wireless remote micro-cloud platform, which allow us to create an efficient and comprehensive online learning environment for both teachers and students, which is more scalable and flexible in terms of adjusting new students, teachers, and teaching contents. The experimental results show that the proposed OUR-CNN and information extraction techniques, along with the usage of wireless networks and micro-cloud platforms, assist both the students in improving their learning skills and the teachers in identifying the weak students and helping them to increase their learning capabilities.

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The data used to support the findings of this study are available from the corresponding author upon request.

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  1. School of Foreign Studies, Henan Polytechnic University, Jiaozuo, 454000, China

    Xue Jingjing

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Jingjing, X. A wireless network-enabled online english subjective assignment evaluation system using micro cloud environment. Wireless Netw 29, 3693–3706 (2023). https://doi.org/10.1007/s11276-023-03433-2

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