Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 8
2305-2309

Peer grading algorithm against malicious evaluation for collaborative learning

Zhao Mingming1a
Wang Cong1b
Li Min1a,2
1. a. Computer Science College, b. College of Movie & Media, Sichuan Normal University, Chengdu 610068, China
2. Network & Data Security Key Laboratory of Sichuan Province, University of Electronic Science & Technology of China, Chengdu 610054, China
DOI: 10.19734/j.issn.1001-3695.2019.03.0055

Abstract

Influenced by subjective factors such as learner's ability and willingness, there is usually a significant gap between peer review results and real evaluation in a collaboration learning environment. In order to improve the quality of peer review and avoid the interest-driven malicious evaluation in the process of mutual evaluation, this paper introduced a small number of teachers' pre-scoring assignments as sentinels. Through the reviewer's review of the sentinel, it used the reviewer's reputation evaluation as the weight vector, and used the threshold for truncation, thus effectively separating the malicious evaluation. The experimental results on the real evaluation data prove that compared with other mainstream mutual evaluation algorithms, the algorithm can effectively filter malicious high evaluation or low evaluation, and can adapt to a larger number of learners to conduct mutual evaluation. In future research, an in-depth study will be conducted on the optimization of the reputation model.

Foundation Support

国家自然科学基金资助项目(61602331)
四川省重点实验室开放课题(NDSMS201606)
四川省教育厅重点项目(17ZA0322)
四川省教育厅科研项目(17ZB0361)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.03.0055
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 8
Section: Algorithm Research & Explore
Pages: 2305-2309
Serial Number: 1001-3695(2020)08-013-2305-05

Publish History

[2020-08-05] Printed Article

Cite This Article

赵鸣铭, 王聪, 李敏. 互助学习环境下可抗恶意评价的同伴互评算法 [J]. 计算机应用研究, 2020, 37 (8): 2305-2309. (Zhao Mingming, Wang Cong, Li Min. Peer grading algorithm against malicious evaluation for collaborative learning [J]. Application Research of Computers, 2020, 37 (8): 2305-2309. )

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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