Research on the Realization Mechanism and Evaluation System of High-Quality Undergraduate Education in Private Universities Based on Deep Learning

Pub Date : 2023-06-30 DOI:10.17993/3ctic.2023.122.97-115
Jun Wang
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Abstract

Due to the new development stage, it is especially important to improve the education quality of private undergraduate universities. As a result, it is a new hot issue for the construction of a mechanism and assessment system for the quality improvement of private undergraduate education. In this paper, after analyzing and researching the quality of undergraduate education in present-day universities, the mechanism of deep learning is applied to the establishment of the assessment system. Finally, 1082 samples collected from the data center platform of a private university are analyzed as the research object. From the results, the final size of the combined weights of the seven evaluation items constituting the assessment system differed basically little. They were 12.81%, 15.78%, 15.28%, 14.38%, 12.83%, 12.81%, 15.01%, and 13.27%, respectively. In the comparison of this paper's method with FAHP+TOPSIS combined evaluation, euclidean map method, and genetic algorithm assignment, the difference between the seven weight values of the euclidean map method is larger, 5.56%. The evaluation times of the four methods were 41 s, 38 s, 47 s, and 118 s. Compared with the other three methods, the genetic algorithm assignment took the most time.
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基于深度学习的民办高校本科优质教育实现机制与评价体系研究
在新的发展阶段,提高民办本科院校的教育质量显得尤为重要。因此,构建民办本科教育质量提升的机制和评估体系成为一个新的热点问题。本文通过对当前高校本科教育质量的分析和研究,将深度学习的机制应用于本科教育质量评价体系的构建。最后以某民办高校数据中心平台采集的1082个样本作为研究对象进行分析。从结果看,构成评价体系的7个评价项目的综合权重最终大小相差基本不大。分别为12.81%、15.78%、15.28%、14.38%、12.83%、12.81%、15.01%、13.27%。将本文方法与FAHP+TOPSIS联合评价法、欧几里得图法、遗传算法分配法进行比较,欧几里得图法的7个权重值相差较大,为5.56%。4种方法的评价时间分别为41 s、38 s、47 s和118 s。与其他三种方法相比,遗传算法分配时间最长。
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