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Exploring the AI Topic Composition of K-12 Using NMF-based Topic Modeling

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@article{IJASEIT12787,
   author = {HoSung Woo and JaeHong Kim and JaMee Kim and WonGyu Lee},
   title = {Exploring the AI Topic Composition of K-12 Using NMF-based Topic Modeling},
   journal = {International Journal on Advanced Science, Engineering and Information Technology},
   volume = {10},
   number = {4},
   year = {2020},
   pages = {1471--1476},
   keywords = {K-12 AI curriculum; AI curriculum; topic model; topic analysis.},
   abstract = {

Recently, artificial intelligence has become more prevalent due to the combination of more data, faster processing power, and more powerful algorithms. AI technology has been introduced into almost all industries and is also affecting the education sector. The objective of this study was to explore AI topics through an analysis of literature related to AI education for grades K-12 and provide implications for the composition of a system for AI education. For this purpose, 27 materials released at the 2018 and 2019 AI4K12 Symposiums were collected. Besides, artificial intelligence integration across subjects and artificial intelligence curriculum published by CBSE of India were collected for analysis. The frequency of words, word cloud, and topic modeling was performed for each collected document. According to the analysis, content on the necessary future direction for AI education and introductions to educational tools were extracted from the 2018 symposium, whereas the 2019 symposium contained more concrete discussions on how to conduct AI education in schools. Meanwhile, content involving the principles of integration for how to integrate AI with other subjects and AI-based teaching and learning methods were extracted from Artificial Intelligence Integration Across Subjects. Finally, Artificial Intelligence Curriculum covered the theories and principles of AI. This study has significance in that it analyzed how much discussion about AI education is being conducted in K-12 based on topic modelling and suggested future directions for AI education.

},    issn = {2088-5334},    publisher = {INSIGHT - Indonesian Society for Knowledge and Human Development},    url = {http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12787},    doi = {10.18517/ijaseit.10.4.12787} }

EndNote

%A Woo, HoSung
%A Kim, JaeHong
%A Kim, JaMee
%A Lee, WonGyu
%D 2020
%T Exploring the AI Topic Composition of K-12 Using NMF-based Topic Modeling
%B 2020
%9 K-12 AI curriculum; AI curriculum; topic model; topic analysis.
%! Exploring the AI Topic Composition of K-12 Using NMF-based Topic Modeling
%K K-12 AI curriculum; AI curriculum; topic model; topic analysis.
%X 

Recently, artificial intelligence has become more prevalent due to the combination of more data, faster processing power, and more powerful algorithms. AI technology has been introduced into almost all industries and is also affecting the education sector. The objective of this study was to explore AI topics through an analysis of literature related to AI education for grades K-12 and provide implications for the composition of a system for AI education. For this purpose, 27 materials released at the 2018 and 2019 AI4K12 Symposiums were collected. Besides, artificial intelligence integration across subjects and artificial intelligence curriculum published by CBSE of India were collected for analysis. The frequency of words, word cloud, and topic modeling was performed for each collected document. According to the analysis, content on the necessary future direction for AI education and introductions to educational tools were extracted from the 2018 symposium, whereas the 2019 symposium contained more concrete discussions on how to conduct AI education in schools. Meanwhile, content involving the principles of integration for how to integrate AI with other subjects and AI-based teaching and learning methods were extracted from Artificial Intelligence Integration Across Subjects. Finally, Artificial Intelligence Curriculum covered the theories and principles of AI. This study has significance in that it analyzed how much discussion about AI education is being conducted in K-12 based on topic modelling and suggested future directions for AI education.

%U http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12787 %R doi:10.18517/ijaseit.10.4.12787 %J International Journal on Advanced Science, Engineering and Information Technology %V 10 %N 4 %@ 2088-5334

IEEE

HoSung Woo,JaeHong Kim,JaMee Kim and WonGyu Lee,"Exploring the AI Topic Composition of K-12 Using NMF-based Topic Modeling," International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 4, pp. 1471-1476, 2020. [Online]. Available: http://dx.doi.org/10.18517/ijaseit.10.4.12787.

RefMan/ProCite (RIS)

TY  - JOUR
AU  - Woo, HoSung
AU  - Kim, JaeHong
AU  - Kim, JaMee
AU  - Lee, WonGyu
PY  - 2020
TI  - Exploring the AI Topic Composition of K-12 Using NMF-based Topic Modeling
JF  - International Journal on Advanced Science, Engineering and Information Technology; Vol. 10 (2020) No. 4
Y2  - 2020
SP  - 1471
EP  - 1476
SN  - 2088-5334
PB  - INSIGHT - Indonesian Society for Knowledge and Human Development
KW  - K-12 AI curriculum; AI curriculum; topic model; topic analysis.
N2  - 

Recently, artificial intelligence has become more prevalent due to the combination of more data, faster processing power, and more powerful algorithms. AI technology has been introduced into almost all industries and is also affecting the education sector. The objective of this study was to explore AI topics through an analysis of literature related to AI education for grades K-12 and provide implications for the composition of a system for AI education. For this purpose, 27 materials released at the 2018 and 2019 AI4K12 Symposiums were collected. Besides, artificial intelligence integration across subjects and artificial intelligence curriculum published by CBSE of India were collected for analysis. The frequency of words, word cloud, and topic modeling was performed for each collected document. According to the analysis, content on the necessary future direction for AI education and introductions to educational tools were extracted from the 2018 symposium, whereas the 2019 symposium contained more concrete discussions on how to conduct AI education in schools. Meanwhile, content involving the principles of integration for how to integrate AI with other subjects and AI-based teaching and learning methods were extracted from Artificial Intelligence Integration Across Subjects. Finally, Artificial Intelligence Curriculum covered the theories and principles of AI. This study has significance in that it analyzed how much discussion about AI education is being conducted in K-12 based on topic modelling and suggested future directions for AI education.

UR - http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12787 DO - 10.18517/ijaseit.10.4.12787

RefWorks

RT Journal Article
ID 12787
A1 Woo, HoSung
A1 Kim, JaeHong
A1 Kim, JaMee
A1 Lee, WonGyu
T1 Exploring the AI Topic Composition of K-12 Using NMF-based Topic Modeling
JF International Journal on Advanced Science, Engineering and Information Technology
VO 10
IS 4
YR 2020
SP 1471
OP 1476
SN 2088-5334
PB INSIGHT - Indonesian Society for Knowledge and Human Development
K1 K-12 AI curriculum; AI curriculum; topic model; topic analysis.
AB 

Recently, artificial intelligence has become more prevalent due to the combination of more data, faster processing power, and more powerful algorithms. AI technology has been introduced into almost all industries and is also affecting the education sector. The objective of this study was to explore AI topics through an analysis of literature related to AI education for grades K-12 and provide implications for the composition of a system for AI education. For this purpose, 27 materials released at the 2018 and 2019 AI4K12 Symposiums were collected. Besides, artificial intelligence integration across subjects and artificial intelligence curriculum published by CBSE of India were collected for analysis. The frequency of words, word cloud, and topic modeling was performed for each collected document. According to the analysis, content on the necessary future direction for AI education and introductions to educational tools were extracted from the 2018 symposium, whereas the 2019 symposium contained more concrete discussions on how to conduct AI education in schools. Meanwhile, content involving the principles of integration for how to integrate AI with other subjects and AI-based teaching and learning methods were extracted from Artificial Intelligence Integration Across Subjects. Finally, Artificial Intelligence Curriculum covered the theories and principles of AI. This study has significance in that it analyzed how much discussion about AI education is being conducted in K-12 based on topic modelling and suggested future directions for AI education.

LK http://ijaseit.insightsociety.org/index.php?option=com_content&view=article&id=9&Itemid=1&article_id=12787 DO - 10.18517/ijaseit.10.4.12787