GIS-Box Improving Data Literacy in Spatial Disciplines: Integrating spatial data modeling, processing and visualization in spatial study programs

Abstract

Data modelling, processing, and visualization are crucial competencies for geospatial study programs. Students of different geospatial study programs need to be strengthened in the use and application of digital tools of spatial analysis and visualization within the digitization of teaching. This paper presents an approach on how digital tools for spatial analysis and visualization can be introduced into the curricula of architecture, urban planning and geography studies, strengthening the interdisciplinary exchange and students’ data literacy. As a result, an interdisciplinary methodological teaching format for spatial analysis, the "GIS-Box" is introduced. The GIS-Box is developed as a modular toolbox to provide material for collaborative and self-taught learning in different Master and Bachelor degree programs. It offers video lectures as well as practical tutorials, including an introduction to data modelling and programming, with the aim of improving students' data literacy. Students also learn to use QGIS to create maps for applied spatial research. In order to provide a uniform technical basis for teaching Python programming, Jupyter Notebooks are used. The integration of Jupyter Notebooks allows combining theoretical and practical programming content interactively. In this paper, we present the implementation of the class, statistically assess student results and experiences from teaching. In addition, positive and negative aspects of integrating GIS-Box with digital tools in teaching are discussed and further opportunities to improving data literacy in teaching are outlined.