Evidence map›Paper›PMID 35571717›Full record

ArticleComputational intelligence and neuroscience2022

Research on the Design of Assistant Basketball Teaching System Based on Big Data.

Lin Wang, Xiaoyun Wei, Guoliang Yuan

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.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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

3 authors.

Lin WangDepartment of Physical Education, North China University of Science and Technology, Hebei, China.
Xiaoyun WeiCollege of Physical Education, Hengshui University, Hebei, China.ORCID https://orcid.org/0000-0002-6382-2103
Guoliang YuanCollege of Physical Education, Hengshui University, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Due to the limitations of the current teaching resources searched by the system, it is difficult to achieve good results in basketball teaching. For this reason, an auxiliary basketball teaching system based on big data is designed. On the basis of clarifying the basic principles of teaching system design, JSP (Java Server Pages) dynamic web page back-end technology and Tomcat 7.0 server are used as the system support structure. Take the big data environment as the source of teaching resources and match them to different databases according to the characteristics of the resources. And combined with real-time evaluation to achieve the assessment of teaching effects and the management of teaching resources, the test results show that the average score of the basketball technical action test under the guidance of this system is higher than 7.5 points when the experimental subjects have the same level of basketball skills. In the paired sample

Indexed as

BasketballBig DataDatabases, FactualHumansStudentsTechnology

Identifiers

PMID35571717
PMCPMC9106470

What OpenQuestion holds

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LicenceCC BY
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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.