By the end of the course, the students are able to:
- Describe and negotiate r-urban sustainability challenges by using computational and complex systems thinking and terminology.
- Analyse and evaluate r-urban sustainability challenges and intended solutions by applying a collaborative and co-creation process.
- Use a pool of complementary computational tools for examining challenges in the r-urban sustainability domain and for illustrating intended solutions.
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The course aims to develop—in a collaborative, interactive context and by using simulation-based serious gaming—the ability to simultaneously apply research, design, and organizational-consultancy skills in addressing sustainability challenges. The challenges-to-be-addressed stem from at least one of the three M-EEM domains (water, energy, environment) with a distinctive r-urban nexus angle. In terms of analytical methods, the objective is to engage in a serious simulation game by exposing the students to a pool of computational and systems thinking approaches. Exposure to these approaches aims not only to practice skills, but also to experience and understand the pros and cons of the tool(s) in use.
Additional information:
- Software utilised in the course: R-Studio, GeoDa, NetLogo.
- Methods taught in the course: Spatial statistics (hot-spot analysis, regression), space syntax, artificial intelligence approaches (cellular automata, agent-based models, fuzzy cognitive maps).
- The sustainability game follows the idea of Geodesign as the overarching collaborative mode.
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