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Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education
by
Paek, Seungsu
, Kim, Namhyoung
in
Algorithms
/ Artificial intelligence
/ Automation
/ Bibliometrics
/ Big Data
/ Core curriculum
/ Data mining
/ Education
/ Knowledge
/ Literacy
/ Natural language
/ Pedagogy
/ Research methodology
/ Students
/ Sustainability
/ Teaching
/ Transportation services
/ Trends
/ Tutoring
2021
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Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education
by
Paek, Seungsu
, Kim, Namhyoung
in
Algorithms
/ Artificial intelligence
/ Automation
/ Bibliometrics
/ Big Data
/ Core curriculum
/ Data mining
/ Education
/ Knowledge
/ Literacy
/ Natural language
/ Pedagogy
/ Research methodology
/ Students
/ Sustainability
/ Teaching
/ Transportation services
/ Trends
/ Tutoring
2021
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Do you wish to request the book?
Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education
by
Paek, Seungsu
, Kim, Namhyoung
in
Algorithms
/ Artificial intelligence
/ Automation
/ Bibliometrics
/ Big Data
/ Core curriculum
/ Data mining
/ Education
/ Knowledge
/ Literacy
/ Natural language
/ Pedagogy
/ Research methodology
/ Students
/ Sustainability
/ Teaching
/ Transportation services
/ Trends
/ Tutoring
2021
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Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education
Journal Article
Analysis of Worldwide Research Trends on the Impact of Artificial Intelligence in Education
2021
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Overview
In today’s world, artificial intelligence (AI) and human intelligence coexist, and no field is free from the impact of AI. At present, education cannot be discussed without mentioning AI, which has an omnidirectional impact on all its areas, including the purpose, content, method, and evaluation system. This study aimed to explore the future direction of education by examining the current impact and predicting future impacts of AI. It also examined research trends and collaboration status by country through network analysis, topic modeling and global research trends in AI in education (AIED), by applying the Latent Dirichlet Allocation algorithm. Over the past 20 years, the number of papers on AIED has steadily increased, with a dramatic rise since 2015. The research can be broadly classified into eight topics, including “changes in the content of teaching and learning.” Using a linear regression model, three hot topics, two cold topics and trend changes for each research topic were identified. The study found that AIED research should be more thematically diversified and in-depth; this directly applies AI algorithms and technologies to education, which should be further promoted. This study provides a reference for exploring the direction of future AIED research.
Publisher
MDPI AG
Subject
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