R or QGIS? A Case Study on Raster Analysis Efficiency in Agricultural Engineering Education
DOI:
https://doi.org/10.29076/issn.2528-7737vol19iss52.2026pp72-83pPalavras-chave:
Rstudio, Rmarkdown, GIS, spatial analysis, learning, rasterResumo
Geographic Information Systems (GIS) are essential in agricultural and environmental sciences, yet handling complex spatial data requires efficient, reproducible workflows. This study evaluated the operational efficiency and student perception of R (via R Markdown) versus QGIS for raster analysis. Fifty-two agronomic engineering students from the University of Cuenca completed a raster temperature extraction exercise using both platforms. Survey responses and completion times were analyzed using McNemar’s tests, exact binomial tests, and generalized linear models. Results showed that exercise completion was significantly higher in R (98%) than in QGIS (87%; P=0.031). R demonstrated superior time efficiency, with 65% of students finishing within three minutes compared to only 29% in QGIS. Additionally, students reported significantly greater self-perceived understanding of the workflow when using R (71% vs. 29%; P<0.01). While preference for a primary GIS teaching platform was evenly split (QGIS 52%, R 48%; P>0.05), an overwhelming majority (96%; P<0.001) indicated they would adopt R as a complementary tool due to execution speed and workflow transparency. Although instructional format asymmetry presents a potential confounding factor, these findings demonstrate that integrating reproducible scripting environments into GIS education enhances computational efficiency, user confidence, and procedural clarity in raster processing
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