Evidence map›Paper›PMID 35936263›Full record

ArticleFrontiers in psychology2022

Optimization design of international talent training model based on big data system.

Jing Wang

Abstract read
In one paragraph

Article in Frontiers in psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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.

Jing WangDepartment of International Communication and Cooperation, Zhejiang Yuexiu University, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the deepening of the concept of a "global village," the exchanges between countries in the world are deepening. This has led to ever-closer ties between countries and regions. They are more and more interdependent and mutually restrictive. Internationalization has become an inevitable trend and trend in the development of higher education in the process of globalization. Big data refer to a collection of data whose content cannot be captured, managed, and processed by conventional software tools within a certain period of time, and need to be processed to obtain the required information. Developed countries have developed earlier in the field of education internationalization and have more mature experience, which provides a reference for the development of other countries. This paper aims to study the optimization design of the international talent training model based on the big data system. In this paper, the system analysis method is used for theoretical discussion. It establishes an index system of graduate students' international talent training mode through AHP, and puts forward a breakthrough for international education in colleges and universities. Internationalized talents refer to high-level talents who have an international awareness and mind, a world-class knowledge structure, a vision and ability reaching an international level, and who are good at seizing opportunities and striving for initiative in global competition. This paper deeply studies the current situation of the international talent training model in colleges and universities, and finds out the deficiencies in the international talent training model. It also optimizes the path for the cultivation and development of international talents, which provides a basis for regional development and cultivation of international talents. The experimental results of this paper show that 20.1% of students believe that international education is to adapt to educational development, 25.4% of students believe that it is mainly to meet the needs of student development, and 62.2% of students believe that college majors lack internationalization characteristics.

Indexed as

AHPbig data systeminternational educationinternational talent training modelmodel optimizationtalent training

Identifiers

PMID35936263
PMCPMC9355548

What OpenQuestion holds

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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.