Evidence map›Paper›PMID 35720913›Full record

ArticleComputational intelligence and neuroscience2022

Research on Discrete Dynamic Modeling of Learner Behavior Analysis in English Teaching.

Junru Fu, Lingmei Cao

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Junru FuDepartment of Foreign Languages, Shanghai University of Finance and Economics Zhejiang College, Jinhua, Zhejiang 321000, China.ORCID https://orcid.org/0000-0001-7125-2828
Lingmei CaoDepartment of Foreign Languages, Shanghai University of Finance and Economics Zhejiang College, Jinhua, Zhejiang 321000, China.ORCID https://orcid.org/0000-0002-5806-2699

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current English teaching mode focuses on the traditional offline teaching and online teaching. In order to solve the problems that some students are inefficient and cannot teach students according to their aptitude in the teaching process, this paper uses the big data analysis strategy based on a neural network algorithm. This paper studies the discrete dynamic modeling method of learner behavior analysis in English teaching. Firstly, it summarizes the current situation of English teaching and the research status of the hybrid application of discrete dynamic modeling technology. Secondly, combined with English teaching content and teaching objectives, through the analysis of various data of students' learning behavior, this paper evaluates students' English teaching quality from five aspects that affect the students' English teaching quality and puts forward a personalized English teaching quality evaluation model based on discrete dynamic modeling technology and learners' behavior analysis. Finally, through the practical teaching application in a university, the feasibility of the discrete dynamic English teaching model is verified. The results show that compared with the current innovative English teaching methods based on a dynamic iterative decision algorithm, the personalized discrete dynamic English teaching model based on learner behavior analysis significantly improves the quality of English teaching and students' academic performance.

Indexed as

LearningStudentsHumansTeachingUniversities

Identifiers

PMID35720913
PMCPMC9203174

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.