Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/121759
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Title: The role of AI in transforming education in spatial data science
Authors: Chen, W 
Liu, X 
Lai, Z 
Issue Date: 2026
Source: In Chen, J., Leung, A., Tsang, E., Ng, A., Chau, J., Kam, R., Patel, M., Lo, D., Tam, B., Chon, L., Cheung, K., Tang, E., & Ho, K. (Eds.). Collection of Selected Papers from the International Conference on GenAI and Pedagogical Innovations 2026, p. 247-254. Hong Kong : Educational Development Centre, Hong Kong Polytechnic University, 2026
Abstract: Rapid advancements in Artificial Intelligence (AI) are revolutionising education, particularly within Geomatics fields such as land surveying, remote sensing, and Geographic Information Systems (GIS). This work explores the integration of AI tools into educational frameworks to enhance spatial understanding, data analysis, and immersive learning. We introduce GeoAI Mentor, an intelligent tutoring system powered by the GeoDataGPT engine, which integrates Large Language Models (LLMs) with dynamic knowledge graphs and Retrieval-Augmented Generation (RAG). Functioning as a 24/7 intelligent partner, the system provides personalised guidance, equipping students with essential skills in geospatial processing and predictive modelling. Pilot evaluations using Hong Kong scenarios demonstrate that GeoAI Mentor effectively dismantles technical barriers by achieving high-precision semantic retrieval and automating complex multi-step spatial reasoning. By bypassing the steep learning curve of software syntax, this approach reallocates cognitive resources toward higher-order analytical intent, preparing graduates for the complexities of modern geospatial industries and the demands of the digital era.
Keywords: Education
Generative Artificial Intelligence
Geomatics
Description: International Conference on GenAI and Pedagogical Innovations (GaPI), Hong Kong, 20-22 May 2026
Rights: Copyright © 2026
Copyright of the papers is retained by the authors. No part of this collection may be reproduced by any process without prior written permission of the copyright holders.
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Appears in Collections:Conference Paper

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