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Using Artificial Intelligence-Based Collaborative Teaching in Media Learning

With the advent of the 5G era, humans must not only learn the knowledge and skills of cross-border integration but must also get to grips with the breadth and efficiency of artificial intelligence (AI) technology in order to jointly overcome current difficulties and create a happy and beautiful life...

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Detalles Bibliográficos
Autores principales: Wang, Weijun, Liu, Zhenhuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548462/
https://www.ncbi.nlm.nih.gov/pubmed/34721159
http://dx.doi.org/10.3389/fpsyg.2021.713943
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author Wang, Weijun
Liu, Zhenhuan
author_facet Wang, Weijun
Liu, Zhenhuan
author_sort Wang, Weijun
collection PubMed
description With the advent of the 5G era, humans must not only learn the knowledge and skills of cross-border integration but must also get to grips with the breadth and efficiency of artificial intelligence (AI) technology in order to jointly overcome current difficulties and create a happy and beautiful life. In this article, we use the example of an elementary school to discuss the decision-making factors that influence teachers when choosing AI technology, where the digital content of schools is imported into artificial intelligence-based collaborative teaching. After discussing the relevant literature, this study will introduce the concept of digital media education, and then compare the development and application of smart technology and human-computer collaborative teaching methods, describing three key aspects and factors that influence elementary school teachers’ choice of AI technology. There are 12 evaluation criteria in total. After the completion of expert questionnaires and data analysis, it was found that the main factors affecting teachers’ choice of AI technology are “collaborative tasks,” “functional characteristics,” and “modeling characteristics.” In terms of evaluation criteria, the four most important aspects were found to be “learning assistance,” “security,” “teaching observation,” and “record review.” The results of this research analysis will help provide a reference for digital content development and individual recommendation services. In future work, this study can further discuss teaching innovations in digital media education, aimed at improving the quality and effectiveness of teaching and learning.
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spelling pubmed-85484622021-10-28 Using Artificial Intelligence-Based Collaborative Teaching in Media Learning Wang, Weijun Liu, Zhenhuan Front Psychol Psychology With the advent of the 5G era, humans must not only learn the knowledge and skills of cross-border integration but must also get to grips with the breadth and efficiency of artificial intelligence (AI) technology in order to jointly overcome current difficulties and create a happy and beautiful life. In this article, we use the example of an elementary school to discuss the decision-making factors that influence teachers when choosing AI technology, where the digital content of schools is imported into artificial intelligence-based collaborative teaching. After discussing the relevant literature, this study will introduce the concept of digital media education, and then compare the development and application of smart technology and human-computer collaborative teaching methods, describing three key aspects and factors that influence elementary school teachers’ choice of AI technology. There are 12 evaluation criteria in total. After the completion of expert questionnaires and data analysis, it was found that the main factors affecting teachers’ choice of AI technology are “collaborative tasks,” “functional characteristics,” and “modeling characteristics.” In terms of evaluation criteria, the four most important aspects were found to be “learning assistance,” “security,” “teaching observation,” and “record review.” The results of this research analysis will help provide a reference for digital content development and individual recommendation services. In future work, this study can further discuss teaching innovations in digital media education, aimed at improving the quality and effectiveness of teaching and learning. Frontiers Media S.A. 2021-10-13 /pmc/articles/PMC8548462/ /pubmed/34721159 http://dx.doi.org/10.3389/fpsyg.2021.713943 Text en Copyright © 2021 Wang and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Wang, Weijun
Liu, Zhenhuan
Using Artificial Intelligence-Based Collaborative Teaching in Media Learning
title Using Artificial Intelligence-Based Collaborative Teaching in Media Learning
title_full Using Artificial Intelligence-Based Collaborative Teaching in Media Learning
title_fullStr Using Artificial Intelligence-Based Collaborative Teaching in Media Learning
title_full_unstemmed Using Artificial Intelligence-Based Collaborative Teaching in Media Learning
title_short Using Artificial Intelligence-Based Collaborative Teaching in Media Learning
title_sort using artificial intelligence-based collaborative teaching in media learning
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8548462/
https://www.ncbi.nlm.nih.gov/pubmed/34721159
http://dx.doi.org/10.3389/fpsyg.2021.713943
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