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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 9
2626-2630

Teaching evaluation data modeling based on discrete Poisson mixture model

Huang Hao
Yan Qian
Gan Ting
Li Shijun
School of Computer Science, Wuhan University, Wuhan 430072, China
DOI: 10.19734/j.issn.1001-3695.2022.01.0042

Abstract

Analyzing the evaluation data of students to teachers in the teaching evaluation system helps teachers understand the true attitudes of students to teachers, summarize teaching experience, improve subsequent teaching methods, and improve teaching quality. However, when evaluating teaching, random or malicious evaluations may occur among students, resulting in a large amount of noise in the evaluation data, which results in unsatisfactory feedback data. Therefore, this paper proposed a discrete Poisson mixture model to model the evaluation data of students with noise. Each discrete Poisson component in the mixture model corresponded a class of students with similar evaluation modes. The model parameters in the loose distribution represented the evaluation scores in the corresponding evaluation mode. It constructed the log-likelihood function to measure the degree of fit between the mixed model and the evaluation data, and used the gradient descent method to solve the model parameters with the highest degree of fit, to find the true evaluation of the students to the teacher, and to ensure the teacher-student relationship in the teaching evaluation system communicate effectively. A large number of experimental results show that the proposed model can quickly and accurately identify students with different evaluation modes from the evaluation data containing noise, and grasp the true evaluation of the students to teachers.

Foundation Support

国家自然科学基金资助项目(61976163,61902284)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.01.0042
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 9
Section: Algorithm Research & Explore
Pages: 2626-2630
Serial Number: 1001-3695(2022)09-010-2626-05

Publish History

[2022-04-15] Accepted Paper
[2022-09-05] Printed Article

Cite This Article

黄浩, 颜钱, 甘庭, 等. 基于离散泊松混合模型的教学评价数据建模 [J]. 计算机应用研究, 2022, 39 (9): 2626-2630. (Huang Hao, Yan Qian, Gan Ting, et al. Teaching evaluation data modeling based on discrete Poisson mixture model [J]. Application Research of Computers, 2022, 39 (9): 2626-2630. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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