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RSS FeedsRemote Sensing, Vol. 12, Pages 735: Advancing Learning Assignments in Remote Sensing of the Environment Through Simulation Games (Remote Sensing)

 
 

22 february 2020 20:03:07

 
Remote Sensing, Vol. 12, Pages 735: Advancing Learning Assignments in Remote Sensing of the Environment Through Simulation Games (Remote Sensing)
 


Environmental remote sensing has faced increasing satellite data availability, advanced algorithms for thematic analysis, and novel concepts of ground truth. For that reason, contents and concepts of learning and teaching remote sensing are constantly evolving. This eventually leads to the intuition of methodologically linking academic learning assignments with case-related scopes of application. In order to render case-related learning possible, smart teaching and interactive learning contexts are appreciated and required for remote sensing. That is due to the fact that those contexts are considered promising to trigger and gradually foster students’ comprehensive interdisciplinary thinking. To this end, the following contribution introduces the case-related concept of applying simulation games as a promising didactic format in teaching/learning assignments of remote sensing. As to methodology, participating students have been invited to take on individual roles bound to technology-related profiles (e.g., satellite-mission planning, irrigation, etc.) Based on the scenario, stakeholder teams have been requested to elaborate, analyze and negotiate viable solutions for soil moisture monitoring in a defined context. Collaboration has been encouraged by providing the protected, specifically designed remoSSoil-incubator environment. This letter-type paper aims to introduce the simulation game technique in the context of remote sensing as a type of scholarly teaching; it evaluates learning outcomes by adopting certain techniques of scholarship of teaching and learning (SoTL); and it provides food for thought of replicating, adapting and enhancing simulation games as an innovative, disruptive next-generation learning environment in remote sensing.


 
161 viewsCategory: Geology, Physics
 
Remote Sensing, Vol. 12, Pages 734: Development of an Image De-Noising Method in Preparation for the Surface Water and Ocean Topography Satellite Mission (Remote Sensing)
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