ArticleJournal of environmental and public health2022
Sentiment Grading and Evaluation of Network Resources of Ideological and Political Education in Colleges and Universities: A Research Based on Artificial Intelligence.
Article in Journal of environmental and public health, 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 It has been retracted, and should not be counted. Not yet cited in PubMed.
What it found
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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.
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Corrections and comments
- Retraction · 2023-06-28Concerns/Issues about Data · Concerns/Issues about Referencing/Attributions · Concerns/Issues about Peer Review · Investigation by Journal/Publisher · Investigation by Third Party · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The current new round of scientific and technological revolution represented by artificial intelligence is rapidly driving a new wave of development of the times, and the rapid iterative update of science and technology is triggering new changes in educational concepts and educational thinking methods. Only by deeply understanding the reshaping of education concept, teaching concept, and learning concept by the new generation of scientific and technological revolution, as well as the major opportunities and challenges brought to education, can we understand the future direction of the development of ideological and political education for college students. This study takes the ideological and political education and teaching of college students as the research object. It begins by defining artificial intelligence and the ideological and political education of college students and analyzes the new concepts of precise individualization, intelligent teaching, and evaluation brought by artificial intelligence to the ideological and political education of college students. Then, it selects the students who have studied ideological and political education network resources as the empirical objects, designs a questionnaire based on the emotional characteristics of the resources, implements a questionnaire survey, uses the Stata software to conduct a correlation analysis on the acceptance of the students, and finally verifies the resources. Combined with empirical results, this article analyzes the influence of emotional characteristics of resources on students' acceptance, reveals the carrier role of ideological and political network resources in school emotional education and students through mirror theory and student response theory, respectively, and establishes the principle of graded reading guidance.
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Registered trials
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