Abstract
When the conventional course resource satisfaction evaluation model is used to evaluate the automobile maintenance major, the reliability of satisfaction evaluation is low due to the large volume of data. Therefore, a big data-based satisfaction assessment model for the automobile maintenance major is proposed. Based on the loading of teaching satisfaction relationship and sample quantification, the introduction of big data analysis technology, and the use of regression equations for big data evaluation, achieved a comprehensive evaluation of the satisfaction of course resources for automobile maintenance majors. The experimental data shows that the reliability of the proposed model is 15.73% higher than that of the conventional model, and the evaluation accuracy is higher.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Lu, S., Zhou, Y. (2020). The Satisfaction Evaluation Model of Course Resources of Automobile Maintenance Major Based on Big Data. In: Liu, S., Sun, G., Fu, W. (eds) e-Learning, e-Education, and Online Training. eLEOT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 339. Springer, Cham. https://doi.org/10.1007/978-3-030-63952-5_5
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DOI: https://doi.org/10.1007/978-3-030-63952-5_5
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