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<p>Humanities geography field practice is an important part of teaching, and this paper aims to study the design and practice of humanities geography field teaching in the era of big data. Starting from the application scenario of big data in geography teaching, this paper optimizes the GMM data clustering analysis by using the EM algorithm and analyzes the humanistic phenomena in Zhaotong City, Yunnan Province, based on the EM-GMM model, especially the rural economy and agricultural development of Zhaotong City, and then optimizes the field teaching design and practice based on the solid data support. From 2016 to 2020, the gross agricultural product of Zhaotong City increased by 4.40%, 9.62%, 14.86%, and 16.56% year by year, while the average annual decrease of crop sown area was 12,200 ha. At the same time, forestry, pastoralism, and fisheries, in general, are growing, with average annual growth rates of 17.18%, 7.95%, and 25.26%, respectively. Based on big data, we can establish a comprehensive and accurate data-based model of human phenomena in the study area to scientifically set up field practice routes, observation targets, and practice directions, which will help improve the effectiveness of students’ field practice.</p>
</abstract>

Humanities geography field practice is an important part of teaching, and this paper aims to study the design and practice of humanities geography field teaching in the era of big data. Starting from the application scenario of big data in geography teaching, this paper optimizes the GMM data clustering analysis by using the EM algorithm and analyzes the humanistic phenomena in Zhaotong City, Yunnan Province, based on the EM-GMM model, especially the rural economy and agricultural development of Zhaotong City, and then optimizes the field teaching design and practice based on the solid data support. From 2016 to 2020, the gross agricultural product of Zhaotong City increased by 4.40%, 9.62%, 14.86%, and 16.56% year by year, while the average annual decrease of crop sown area was 12,200 ha. At the same time, forestry, pastoralism, and fisheries, in general, are growing, with average annual growth rates of 17.18%, 7.95%, and 25.26%, respectively. Based on big data, we can establish a comprehensive and accurate data-based model of human phenomena in the study area to scientifically set up field practice routes, observation targets, and practice directions, which will help improve the effectiveness of students’ field practice.

Design and Practice of Human Geography Field Teaching in the Age of Big Data

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Design and Practice of Human Geography Field Teaching in the Age of Big Data"}

Humanities geography field practice is an important part of teaching, and this paper aims to study the design and practice of humanities geography field...

Design and Practice of Human Geography Field Teaching in the Age of Big Data

Publié en ligne: 02 juin 2023

Pages: -

Reçu: 16 mai 2022

Accepté: 10 oct. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00135

Mots clés
Big data, EM-GMM model, Field instructional design, Cluster analysis

© 2023 Yan Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Design and Practice of Human Geography Field Teaching in the Age of Big Data

Publié en ligne: 02 juin 2023

Pages: -

Reçu: 16 mai 2022

Accepté: 10 oct. 2022

DOI: https://doi.org/10.2478/amns.2023.1.00135

Mots clésBig data, EM-GMM model, Field instructional design, Cluster analysis

© 2023 Yan Liu, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Big data, EM-GMM model, Field instructional design, Cluster analysis