Integration and application of data visualisation technology in a data analysis teaching platform

This study presents a WebGPU-based visualisation framework aimed at enhancing the processing, rendering, and interactivity of large-scale, multidimensional datasets in educational contexts.By integrating artificial intelligence (AI) tools with advanced visualisation techniques, the framework enables efficient data preprocessing, interpolation, and volume texture generation for seamless web-based visualisation.Utilising datasets from oceanographic simulations and educational performance metrics, the system demonstrates versatility across domains.Comparative experiments show that the WebGPU-based solution significantly outperforms previous WebGL-based implementations, reducing rendering time and increasing frame rates.User surveys report high satisfaction in functionality, personalisation, usability, and compatibility.These findings highlight the potential of AI-driven educational data analytics and visualisation tools to support decision-making, enhance user engagement, and promote data literacy in academic and professional training environments.

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Publication Details

Journal
International Journal of Information and Communication Technology
Published
2026-01-01
DOI
https://doi.org/10.1504/ijict.2026.152547
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
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article

Integration and application of data visualisation technology in a data analysis teaching platform

Minjun Xie
International Journal of Information and Communication Technology
Data Visualization and Analytics
article

Integration and application of data visualisation technology in a data analysis teaching platform

Minjun Xie
article en

Abstract

This study presents a WebGPU-based visualisation framework aimed at enhancing the processing, rendering, and interactivity of large-scale, multidimensional datasets in educational contexts.By integrating artificial intelligence (AI) tools with advanced visualisation techniques, the framework enables efficient data preprocessing, interpolation, and volume texture generation for seamless web-based visualisation.Utilising datasets from oceanographic simulations and educational performance metrics, the system demonstrates versatility across domains.Comparative experiments show that the WebGPU-based solution significantly outperforms previous WebGL-based implementations, reducing rendering time and increasing frame rates.User surveys report high satisfaction in functionality, personalisation, usability, and compatibility.These findings highlight the potential of AI-driven educational data analytics and visualisation tools to support decision-making, enhance user engagement, and promote data literacy in academic and professional training environments.

International Journal of Information and Communication TechnologyVol. 27(28)
Quality Education
Openalex Percentile: Top 5%
Data Visualization and Analytics
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