Designing XR-based learning solutions for surveying engineering: insights from literature review and user requirements
Year: 2025
Type: conference-paper
Abstract: This manuscript presents the steps undertaken for the design of a robust educational solution to enhance learning outcomes for Surveying Engineering students, as part of the SURE-VFT (Immersive Exploration and Data Acquisition: XR Virtual Field Trips for 3D Photogrammetry and Remote Sensing) project. This project aims to enhance the learning experience of Surveying Engineering students through the development of three immersive virtual field trips (VFTs), based on a toolset available on an innovative, sustainable, on-demand education platform developed by the Horizon Europe’s XR4ED (Accelerating innovation in learning and education through EdTech and XR) project. The design of the VFTs builds upon existing best practices and tools in surveying engineering education and a broad-audience survey conducted through a web-based questionnaire to gather user requirements, focusing on simplicity, clarity, and relevance. The findings of the user requirements survey confirm a strong demand for XR-based Surveying Engineering training that combines usability, guided workflows, and relevant data export functionalities. By integrating the best practices uncovered in the literature with the user requirements (especially from novice learners), the SURE-VFT project will create VFTs that are effective, technically accessible, and scalable across different institutional and commercial contexts. This alignment will be instrumental in advancing the XR4ED platform and driving adoption of XR methodologies for Surveying Engineering education in Europe and beyond.
DOI: 10.1117/12.3073257
Authors: Petros Patias, Charalampos Georgiadis, Giorgos Mallinis, Anastasios Stamnas, Vasiliki Fragkoulidou, Themistoklis Roustanis, Patrick Bourdot, Marco Sacco
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4414363353
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