Author
Listed:
- Gamze Altun
(Landscape Architecture Department, Faculty of Agriculture, Bursa Uludağ University, Bursa 16059, Turkiye)
- Murat Zencirkıran
(Landscape Architecture Department, Faculty of Agriculture, Bursa Uludağ University, Bursa 16059, Turkiye)
Abstract
This study presents the development and evaluation of a Quick Response (QR) code-integrated, web-based, and GIS-supported interactive learning model designed to enhance field-based plant learning in landscape architecture education. Conducted on the Görükle Campus of Bursa Uludağ University (BUU), the research systematically inventoried 6869 individual woody plants belonging to 172 taxa, georeferenced them using GPS, and visualized the data on an interactive campus map. Unique QR codes were generated for each taxon, providing instant access to plant profiles via a web platform and the Landscape Plants mobile application. The pedagogical effectiveness of the system was evaluated through a survey administered to 158 students, yielding a high internal reliability (Cronbach’s Alpha = 0.969). The findings indicated a high level of student satisfaction and a strong positive correlation between web-based and QR code applications (r = 0.941, p ≤ 0.001). This research represents the most comprehensive campus-scale digital plant learning system in Turkey, in terms of both species diversity and individual count. It provides a scalable and sustainable smart campus model which is applicable to nature-based disciplines worldwide.
Suggested Citation
Gamze Altun & Murat Zencirkıran, 2025.
"A Web-Based Learning Model for Smart Campuses: A Case in Landscape Architecture Education,"
Sustainability, MDPI, vol. 17(24), pages 1-19, December.
Handle:
RePEc:gam:jsusta:v:17:y:2025:i:24:p:11203-:d:1817869
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