EdX

Performative Modelling (edX)

Performative Modelling (edX)

This course focuses on evaluating alternative spatial configurations to support evidence-based decision making. You will learn methods for calculating various spatial performance metrics related to the built environment that can be used for comparative analysis of design options.

Class Deals by MOOC List - Click here and see EdX's Active Discounts, Deals, and Promo Codes.

This course is the last in our “Spatial Computational Thinking” program. This “Performative Modelling” course focuses on evaluating alternative spatial configurations to support evidence-based decision making. You will learn methods for calculating various spatial performance metrics related to the built environment that can be used for comparative analysis of design process.
This course will build on the previous three courses that covered procedural, semantic, and generative modelling. In this course, you will switch modes from generating to evaluating spatial performance. Thus, you will be creating procedures for evaluating alternative spatial configurations with respect to a set of performance indicators. This will once again require an increase in coding complexity, together with a new set of strategies for managing that complexity.
In this course, you will learn how to create your own reusable and customised function libraries. You will use this powerful technique to create a set of generative and performative functions. The generative functions will be used to generate alternative spatial configurations for building designs. The performative functions will be used to evaluate various performance metrics. You will then combine these functions, evaluating each spatial configuration against each performance metric. Finally, you will develop procedures for visualizing and exporting the performance results in order to support decision making.
In the process, you will learn a powerful technique, the ability to import one flowchart into another flowchart and to use it as a function. This allows you to execute larger computational processes with many more procedures hidden inside it.
The modelling exercises and assignments during this course will mainly focus on evaluating alternative spatial configurations for buildings within the urban environment. A site will be selected, and procedures will be developed for calculating performance metrics using morphological and raytracing analysis methods. The morphological analysis includes plot ratio, compacity ratio, passive zone proportion, etc, while the raytracing analysis includes sky view factor, sun exposure factor, viewsheds, etc. The various metrics will then be weighted and aggregated, in order to allow alternative options to be easily compared.
Completing the four courses that make up the “Spatial Computational Thinking” program will provide you with the fundamental knowledge and skills required to tackle a wide variety computational design challenges using digital technologies.
This course is part of the Spatial Computational Thinking Professional Certificate.

What you'll learn

Learning algorithmic thinking:

  • How to evaluate alternative spatial configurations using morphological attributes and performance indicators
  • Use abstraction as a way of selectively exposing the parameters that are most relevant to the problem being investigated
  • Use encapsulation as a way of managing problem complexity

Learning performative modelling:

  • Analysing performance indicators using morphological analysis and raytracing analysis
  • Understanding morphological analysis: plot ratio, compacity ratio, passive zone proportion, etc
  • Understanding raytracing analysis: sky view factor, sun exposure factor, viewsheds, etc
  • Evaluating alternative spatial configurations based on multiple performance metrics
  • Strategies for supporting decision making using weighted performance metrics
  • Integrating non-spatial data formats into spatial information modeling workflows
  • Strategies for data visualization

Learning coding:

  • Understanding how to break down large procedures into a set of smaller functions
  • Understanding how to document functions to support reuse
  • Understanding how to create and share libraries of functions that can be reused

Learning Möbius Modeller:

  • Difference between local and global functions
  • Creating flowcharts that can be imported as global functions
  • Strategies for implementing with global functions
  • Working with the geospatial viewer
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

JavaScript Interview Challenges (Coursera) Coursera
Scrimba

JavaScript Interview Challenges (Coursera)

Your essential tech interview preparation pack! Practice solving problems and honing the skills you need to succeed in a frontend coding interview. Are you applying for frontend developer roles? Do you wish to test out your JavaScript knowledge? Do you love solving code challenges? If any of the above applies to you, JavaScript Interview Challenges should be your next Scrimba course!

Sep 21st 2026
3 Weeks
Calculus through Data & Modelling: Integration Applications (Coursera) Coursera
Johns Hopkins University

Calculus through Data & Modelling: Integration Applications (Coursera)

This course continues your study of calculus by focusing on the applications of integration. The applications in this section have many common features. First, each is an example of a quantity that is computed by evaluating a definite integral. Second, the formula for that application is derived from Riemann sums. Rather than measure rates of change as we did with differential calculus, the definite integral allows us to measure the accumulation of a quantity over some interval of input values.

Sep 14th 2026
4 Weeks
Algorítmica Básica (edX) EdX
Tecnológico de Monterrey,TecdeMonterreyX

Algorítmica Básica (edX)

Aprende los fundamentos del pensamiento algorítmico, estructuras de datos y los principios básicos de programación con aplicación a los negocios. Los algoritmos pueden ser utilizados para la solución de problemas de negocio. En este curso aprenderás los conceptos básicos de algoritmos y el manejo de estructuras de datos.

Self Paced
Self-Paced
Statistics for Business Analytics: Modelling and Forecasting (edX) EdX
University of Queensland,UQx

Statistics for Business Analytics: Modelling and Forecasting (edX)

This is a great course for anyone who wants to gain foundational and critical analysis and statistics skills with no prior background. In this course, we explore statistical methods for examining the relationships between variables. We also consider how data from the past can be used to make forecasts about likely future trends.

Apr 7th 2023
4 Weeks
Gen AI for Code Generation for Python (Coursera) Coursera
Edureka

Gen AI for Code Generation for Python (Coursera)

Welcome to the 'Gen AI for Code Generation for Python' course, where you'll embark on a journey to explore and develop your skills in the art of code generation with Generative AI. Throughout this short course, you will delve into various techniques for generating Python code effortlessly, ranging from simple scripts to complete end-to-end projects.

Sep 14th 2026
1 Week
Recommender Systems: Behind the Screen (edX) EdX
Université de Montréal,UMontrealX

Recommender Systems: Behind the Screen (edX)

How are items recommended when you’re browsing for movies, jobs or clothing online? Register here and you’ll discover the fundamental concepts and methods allowing the most relevant item suggestions to users from e-commerce to online advertisement. In this course, you will explore and learn the best methods and practices in recommender systems, which are an essential component of the online ecosystem. This course was developed by IVADO and HEC Montréal as part of a workshop that took place in Montreal.

Self Paced
5-12 Weeks
Calculus through Data & Modelling: Series and Integration (Coursera) Coursera
Johns Hopkins University

Calculus through Data & Modelling: Series and Integration (Coursera)

This course continues your study of calculus by introducing the notions of series, sequences, and integration. These foundational tools allow us to develop the theory and applications of the second major tool of calculus: the integral. Rather than measure rates of change, the integral provides a means for measuring the accumulation of a quantity over some interval of input values. This notion of accumulation can be applied to different quantities, including money, populations, weight, area, volume, and air pollutants. The concepts in this course apply to many other disciplines outside of traditional mathematics.

Sep 14th 2026
5-12 Weeks
Computational Thinking and Big Data (edX) EdX
University of Adelaide,AdelaideX

Computational Thinking and Big Data (edX)

Learn the core concepts of computational thinking and how to collect, clean and consolidate large-scale datasets. Computational thinking is an invaluable skill that can be used across every industry, as it allows you to formulate a problem and express a solution in such a way that a computer can effectively carry it out.

Self Paced
Self-Paced