Evidence map›Paper›PMID 36124116›Full record

ArticleComputational intelligence and neuroscience2022

Cloud-Based English Multimedia for Universities Test Questions Modeling and Applications.

Yanping Wu, Changlong Zheng, Lele Xie, Meihui Hao

RetractedAbstract readRetracted Publication
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. It has been retracted, and should not be counted. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Yanping WuDepartment of Economic Management, Dongchang College of Liaocheng University, Liaocheng, Shandong 252000, China.ORCID https://orcid.org/0000-0002-8945-2040
Changlong ZhengLiaocheng Yucai School, Liaocheng, Shandong 252000, China.
Lele XieExperimental Primary School of Liaocheng Economic and Technological Development Zone, Liaocheng, Shandong 252000, China.
Meihui HaoDongchang Middle School of Liaocheng Economic and Technological Development Zone, Liaocheng, Shandong 252000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study constructs a cloud computing-based college English multimedia test question modeling and application through an in-depth study of cloud computing and college English multimedia test questions. The emergence of cloud computing technology undoubtedly provides a new and ideal method to solve test data and paper management problems. This study analyzes the advantages of the Hadoop computing platform and MapReduce computing model and builds a distributed computing platform based on Hadoop using universities' existing hardware and software resources. The study analyzes the advantages of the Hadoop computing platform and the MapReduce computing model. The UML model of the system is given, the system is implemented, the system is tested functionally, and the results of the analysis are given. Multimedia is the critical link to realizing the optimization of English test questions. The proper use of multimedia test questions will undoubtedly become an inevitable trend in the development of English test questions in the future, which requires every worker on the education front to continuously analyze and study the problems arising from multimedia teaching, summarize the experience of multimedia teaching, and explore new methods of multimedia teaching, so that multimedia teaching can better promote the optimization of English test questions in colleges and universities and better serve the education teaching.

Indexed as

Cloud ComputingMultimediaComputersHumansSoftwareUniversities

Identifiers

PMID36124116
PMCPMC9482472

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.