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

Unreal Engine Interactive 3D: Blueprints, Animation, Audio, & Environments (edX) EdX
Rochester Institute of Technology,RITx

Unreal Engine Interactive 3D: Blueprints, Animation, Audio, & Environments (edX)

Expand your interactive Unreal Engine 3D skills with Blueprints, Landscapes, Audio and AI. In this course, you’ll build on your knowledge from UNRL 101 by learning visual scripting using Blueprints. This node-based system based on C++ enables powerful programming without the syntax typically involved in coding. You will gain basic coding skills to use multiple tools for accelerating work and building immersive interactive functionality.

Self Paced
Self-Paced
Introduction to Java Programming: Starting to code in Java (edX) EdX
Universidad Carlos III de Madrid - UC3M,UC3Mx

Introduction to Java Programming: Starting to code in Java (edX)

Learn to program with Java in an easy and interactive way! In this introductory Java programming course, you will be introduced to powerful concepts such as functional abstraction, the object oriented programming (OOP) paradigm and Application Programming Interfaces (APIs). Examples and case studies will be provided so that you can implement simple programs on your own or collaborate with peers.

Self Paced
Self-Paced
Calculus through Data & Modelling: Techniques of Integration (Coursera) Coursera
Johns Hopkins University

Calculus through Data & Modelling: Techniques of Integration (Coursera)

In this course, we build on previously defined notions of the integral of a single-variable function over an interval. Now, we will extend our understanding of integrals to work with functions of more than one variable. First, we will learn how to integrate a real-valued multivariable function over different regions in the plane. Then, we will introduce vector functions, which assigns a point to a vector. This will prepare us for our final course in the specialization on vector calculus. Finally, we will introduce techniques to approximate definite integrals when working with discrete data and through a peer reviewed project on, apply these techniques real world problems.

Oct 26th 2026
4 Weeks
Excel for Everyone: Data Management (edX) EdX
The University of British Columbia,UBCx

Excel for Everyone: Data Management (edX)

Further your Excel skills to manage larger datasets and more complex data wrangling, management and modelling. This intermediate Excel course builds on the teachings of the introductory Core Foundations course, teaching you to leverage the power of data calculations and reports to make informed personal or organizational decisions.

Self Paced
Self-Paced
How to Win Coding Competitions: Secrets of Champions (edX) EdX
ITMO University,ITMOx

How to Win Coding Competitions: Secrets of Champions (edX)

Enhance programming skills to boost your career and win prizes led by ITMO University, the only 6-time winner of the world’s top coding cup. Want to be the programmer hot tech companies are looking for? Take your programming skills to the next level and prove your excellence by learning how to succeed in programming competitions.

No sessions available
5-12 Weeks
Calculus through Data & Modelling: Vector Calculus (Coursera) Coursera
Johns Hopkins University

Calculus through Data & Modelling: Vector Calculus (Coursera)

This course continues your study of calculus by focusing on the applications of integration to vector valued functions, or vector fields. These are functions that assign vectors to points in space, allowing us to develop advanced theories to then apply to real-world problems. We define line integrals, which can be used to fund the work done by a vector field. We culminate this course with Green's Theorem, which describes the relationship between certain kinds of line integrals on closed paths and double integrals.

Oct 26th 2026
3 Weeks
Algorithmic Thinking (Part 1) (Coursera) Coursera
Rice University

Algorithmic Thinking (Part 1) (Coursera)

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This two-part class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

Nov 2nd 2026
4 Weeks
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
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.

Nov 9th 2026
1 Week