Article: Integration and application of data visualisation technology in a data analysis teaching platform Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.28 pp.1 - 24 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. Inderscience Publishers - linking academia, business and industry through research

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

Authors: Minjun Xie

Addresses: College of Computer and Information Engineering, Guangxi Vocational Normal University, Nanning, Guangxi, 530007, China

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.

Keywords: big data visualisation; web GPU; data analysis teaching platform; volume rendering; artificial intelligence in education; educational data analytics; visualisation framework; user satisfaction; data preprocessing; interactive visualisation.

DOI: 10.1504/IJICT.2026.152547

International Journal of Information and Communication Technology, 2026 Vol.27 No.28, pp.1 - 24

Received: 11 Aug 2025
Accepted: 30 Nov 2025
Published online: 26 Mar 2026 *

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

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