Research on the innovation path of teaching interior design majors in universities based on big data analysis
Presently, the teaching of interior design in most higher education institutions still uses more traditional and conservative teaching methods, which to some extent, hinders the reform of interior design teaching in the era of big data. Interior design originally required students to grasp the opera...
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| Format: | Article |
| Language: | English |
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Sciendo
2024-01-01
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| Series: | Applied Mathematics and Nonlinear Sciences |
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| Online Access: | https://doi.org/10.2478/amns.2023.1.00355 |
| _version_ | 1797340909381091328 |
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| author | Hou Weiwei |
| author_facet | Hou Weiwei |
| author_sort | Hou Weiwei |
| collection | DOAJ |
| description | Presently, the teaching of interior design in most higher education institutions still uses more traditional and conservative teaching methods, which to some extent, hinders the reform of interior design teaching in the era of big data. Interior design originally required students to grasp the operation fully and use CAD, 3D, and other design software, which makes the operation of complex commands, and model construction diversity, difficult for students to learn. This situation still uses the traditional lecture-based indoctrination teaching can play a very small role. This paper first focuses on the field of interior design education, based on the background of the times, provides a deep overview of the current situation of the relevant research involved in interior design, and explains the purpose, ideas, content, and methods of this paper. Secondly, we use data mining technology to build a smart classroom to visually present interior design. Finally, a comparison experiment between the traditional teaching mode of interior design and the smart teaching mode of big data is carried out, and three groups of experimental subjects are investigated after nearly one month of teaching experience. The results of this study show that the big data wisdom teaching model proposed in this paper compared with the traditional teaching model, through the one-month teaching experience post-test results, the average increase of 7 points in school A, 11 points in school K, and 14 points in school Z. The wisdom teaching system based on big data built in this paper enhanced the relevance and initiative of interior design students’ learning, improved students’ interest in learning and classroom efficiency and promoted students’ comprehensive ability while playing a positive and active role. |
| first_indexed | 2024-03-08T10:10:15Z |
| format | Article |
| id | doaj.art-ea3dac24de4143ccbdfe834a12a2a1c6 |
| institution | Directory Open Access Journal |
| issn | 2444-8656 |
| language | English |
| last_indexed | 2024-03-08T10:10:15Z |
| publishDate | 2024-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Applied Mathematics and Nonlinear Sciences |
| spelling | doaj.art-ea3dac24de4143ccbdfe834a12a2a1c62024-01-29T08:52:27ZengSciendoApplied Mathematics and Nonlinear Sciences2444-86562024-01-019110.2478/amns.2023.1.00355Research on the innovation path of teaching interior design majors in universities based on big data analysisHou Weiwei01School of art and design, Xuzhou University of Technology, Xuzhou, Jiangsu, 221000, ChinaPresently, the teaching of interior design in most higher education institutions still uses more traditional and conservative teaching methods, which to some extent, hinders the reform of interior design teaching in the era of big data. Interior design originally required students to grasp the operation fully and use CAD, 3D, and other design software, which makes the operation of complex commands, and model construction diversity, difficult for students to learn. This situation still uses the traditional lecture-based indoctrination teaching can play a very small role. This paper first focuses on the field of interior design education, based on the background of the times, provides a deep overview of the current situation of the relevant research involved in interior design, and explains the purpose, ideas, content, and methods of this paper. Secondly, we use data mining technology to build a smart classroom to visually present interior design. Finally, a comparison experiment between the traditional teaching mode of interior design and the smart teaching mode of big data is carried out, and three groups of experimental subjects are investigated after nearly one month of teaching experience. The results of this study show that the big data wisdom teaching model proposed in this paper compared with the traditional teaching model, through the one-month teaching experience post-test results, the average increase of 7 points in school A, 11 points in school K, and 14 points in school Z. The wisdom teaching system based on big data built in this paper enhanced the relevance and initiative of interior design students’ learning, improved students’ interest in learning and classroom efficiency and promoted students’ comprehensive ability while playing a positive and active role.https://doi.org/10.2478/amns.2023.1.00355interior designdata miningvisualizationbig datasmart classroom65j99 |
| spellingShingle | Hou Weiwei Research on the innovation path of teaching interior design majors in universities based on big data analysis Applied Mathematics and Nonlinear Sciences interior design data mining visualization big data smart classroom 65j99 |
| title | Research on the innovation path of teaching interior design majors in universities based on big data analysis |
| title_full | Research on the innovation path of teaching interior design majors in universities based on big data analysis |
| title_fullStr | Research on the innovation path of teaching interior design majors in universities based on big data analysis |
| title_full_unstemmed | Research on the innovation path of teaching interior design majors in universities based on big data analysis |
| title_short | Research on the innovation path of teaching interior design majors in universities based on big data analysis |
| title_sort | research on the innovation path of teaching interior design majors in universities based on big data analysis |
| topic | interior design data mining visualization big data smart classroom 65j99 |
| url | https://doi.org/10.2478/amns.2023.1.00355 |
| work_keys_str_mv | AT houweiwei researchontheinnovationpathofteachinginteriordesignmajorsinuniversitiesbasedonbigdataanalysis |