Evidence map›Paper›PMID 34858265›Full record

ArticleFrontiers in psychology2021

Design and Implementation of Intelligent Learning System Based on Big Data and Artificial Intelligence.

Yawen Yang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in psychology, 2021. 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
0.9field-weighted citation impact, top 20% of its field
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, 6 citations in OpenAlex.

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

1 author at 1 institution in 1 country.

Yawen YangAcademy of Arts, Southwest Minzu University, Chengdu, China.
Southwest Minzu University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In order to improve the level of education development in remote areas of China, help minority schools to better play the advantages of multimedia network teaching resources provided by the state, and further improve the level of multimedia network management, a multimedia network teaching management system is studied and developed. The teaching information and business process of the school is analyzed, the division of the structure of the film and television multimedia information management system is completed, and the overall structure, functional structure, and database of the system are designed; Tornado technology, NoSQL database technology, jQuery technology, and Ajax technology are used to complete the development of the system. The results show that the real system can provide a highly automated platform for the school multimedia network-teaching management. The system makes the teaching staff work more efficiently and accurately. The results show that the system studied has a significant effect on the multimedia teaching of minority films and television. Using the characteristics of the combination of pictures, text, sound, image, and shadow, the knowledge can be shown to students intuitively, which is helpful to relaxed and happy learning of students and stimulate their desire to learn. Multimedia teaching has become an important teaching assistant tool. This exploration can provide theoretical support for the design of the network teaching information management system based on artificial intelligence, decentralize the complex network environment, and carry out decentralized management.

Indexed as

big datainformation management systeminformation technologymodule designmultimedia teachingmultimedia technology

Identifiers

PMID34858265
PMCPMC8632003
OpenAlexW3214171323

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.