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<p>The article adopts Unity 3D and Leap Motion technology to develop the interaction scene and creates modules, including pottery knowledge learning, virtual pottery gesture teaching, and pottery work display. Pottery knowledge and gestures are taught to students through virtual teacher guidance and gesture interaction. At the same time, grid structure definition, vertex calculation, and feature representation techniques are used for modeling and extracting features from pottery works. In terms of knowledge point mastery and work creativity, students using the virtual pottery system perform significantly better than traditional teaching methods according to teaching practice. For example, the knowledge point mastery scores of the virtual group were considerably higher than those of the conventional paper-and-pencil and clay groups (P&lt;0.05), and the creativity scores of the works were significantly better than those of the control group (P&lt;0.001). In addition, students’ learning engagement (including cognitive, affective, and social engagement) was significantly improved in the virtual group. By combining big data technology and virtual reality technology, the teaching effectiveness of pottery education in higher vocational schools has improved dramatically. The virtual pottery teaching system enhances students’ mastery of knowledge points and creativity of works while also enhancing their learning engagement, demonstrating the significance and potential of technology in art education.</p>
</abstract>

The article adopts Unity 3D and Leap Motion technology to develop the interaction scene and creates modules, including pottery knowledge learning, virtual pottery gesture teaching, and pottery work display. Pottery knowledge and gestures are taught to students through virtual teacher guidance and gesture interaction. At the same time, grid structure definition, vertex calculation, and feature representation techniques are used for modeling and extracting features from pottery works. In terms of knowledge point mastery and work creativity, students using the virtual pottery system perform significantly better than traditional teaching methods according to teaching practice. For example, the knowledge point mastery scores of the virtual group were considerably higher than those of the conventional paper-and-pencil and clay groups (P<0.05), and the creativity scores of the works were significantly better than those of the control group (P<0.001). In addition, students’ learning engagement (including cognitive, affective, and social engagement) was significantly improved in the virtual group. By combining big data technology and virtual reality technology, the teaching effectiveness of pottery education in higher vocational schools has improved dramatically. The virtual pottery teaching system enhances students’ mastery of knowledge points and creativity of works while also enhancing their learning engagement, demonstrating the significance and potential of technology in art education.

Exploration of Precision Teaching Reform of Ceramics Education in Higher Vocational School under the Background of Big Data Technology

Applied Mathematics and Nonlinear Sciences

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

The article adopts Unity 3D and Leap Motion technology to develop the interaction scene and creates modules, including pottery knowledge learning, virtual...

Exploration of Precision Teaching Reform of Ceramics Education in Higher Vocational School under the Background of Big Data Technology

Online veröffentlicht: 30. Mai 2024

Seitenbereich: -

Eingereicht: 09. Feb. 2024

Akzeptiert: 13. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1213

Schlüsselwörter
Leap Motion, Mesh structure, Vertex computation, Feature representation, Pottery teaching

© 2024 Xing Yue, published by Sciendo

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

Exploration of Precision Teaching Reform of Ceramics Education in Higher Vocational School under the Background of Big Data Technology

Online veröffentlicht: 30. Mai 2024

Seitenbereich: -

Eingereicht: 09. Feb. 2024

Akzeptiert: 13. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1213

SchlüsselwörterLeap Motion, Mesh structure, Vertex computation, Feature representation, Pottery teaching

© 2024 Xing Yue, published by Sciendo

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

Schlüsselwörter
Leap Motion, Mesh structure, Vertex computation, Feature representation, Pottery teaching