Module Overview

Spatial Computational Thinking is increasingly being recognised as a fundamental method for various spatial disciplines. It involves idea formulation, algorithm development, and solution exploration, with a focus on the manipulation of geometric and semantic datasets. Students will use parametric modelling tools for generating and analysing building elements at varying scales. Such tools use visual programming interfaces to allow complex algorithms to be developed and tested. Students will learn how to structure their ideas as algorithmic procedures that integrate data-structures, functions, and control flow. Through this process, students will also become familiar with higher-level computational concepts, such as decomposition, encapsulation and abstraction.

The aim of this module is for the students to develop confidence in spatial computational thinking using parametric modelling tools.

The learning outcome is theoretical knowledge and practical skills in applying spatial computational thinking as a way of developing and exploring ideas, building upon elementary critical and logical thinking aptitude.

After completing the module, students should be able to:

• Formulate a design idea as an algorithm
• Decompose an algorithm into sub-procedures
• Build flexible and reusable algorithms
• Improve the robustness of an algorithms
• Apply algorithmic thinking in design exploration

The module is a Blended Learning module.

The module is broken down into an Introduction (week 1), five Exercises (weeks 2-5,7-8) and a Final Project (weeks 9-11). The Exercises introduce specific computational thinking concepts and programming skills, and build up in complexity over the course of the semester. At the end of each Exercise, you have to submit a progress-report which will demonstrates the knowledge and skills you have learnt. The Final Project will require you to develop a complex parametric model that integrates the conceptual knowledge and programming skills that you have acquired over the semester. 

The first introduction lecture will be the only lecture during the semester. After that, all the main content will be delivered via short online lectures and videos. You will be able to engage in discussion with tutors and TAs using various online platforms. If you desire face-to-face meetings, then you may attend the optional workshops on Wednedsay mornings. These workshops allow you to come and discuss issues and get help in the computer lab.

For each Exercise and for the Final Project, an Overview document and a series of short Programming Skills videos will be provided. The Overview document will give a high level overview of the exercise and will explain the pedagogical objectives and requirements. The Programming Skills videos will show screen recordings of various programming techniques using the Mobius Modeller. Each exercise will set a small problem to be solved, and you will be able to attempt the problem and upload the answer. 

During the module, you are encourarged to share your knowledge and help each other. For the work that you submit (the Execises and Final Project), you are expected to work individually. For each Exercises, you need to submit a progress report that explain what you have done that week (worth 5%). For the Final Project, you need to submit two Project Planning reports (worth 10% each) and a Final Report (worth 50%). There will also be a 5% participation grade. 

The module will use Mobius Modeller is an open-source online parametric modelling platform that allows you to work directly in the web browser. No complex software installations will be required and no software licences ned to be purchased. 

• link coming soon...

Online discussions will use Slack.com

• https://join.slack.com/t/mobius-modeller/signup

It is compulsory for you to join up and participate on this discussion forum.

Exercises:

• Week 2: Basic text programming
• Week 3: Basic geometry programming
• Week 4: Formulate problem and solution
• Week 5: Implement solution and test
• Week 7: Formulate problem and solution
• Week 8: implement solution and test

Final Project

• Week 9: Formulate problem
• Week 10: Formulate solution
• Week 11: Implement solution and test

Computational Thinking:

• Formulate an idea as an algorithm    
• Define the algorithmic steps and sub steps    
• Analysing the pros and cons of different approaches    
• Implement and test the algorithm

Parametric Modelling:

• Object-Based Parametric Modelling
• Associative Parametric Modelling
• Dataflow Parametric Modelling
• Procedural Parametric Modelling
• Hybrid Parametric Modelling

Programing with flowcharts in Möbius:

• Flowchart nodes, node instances, node types
• Node parameters and viewers
• Spliting and merging dataflow
• Flowcharts with nested nodes

Programming with procedures in Möbius:

• Variables, data types, and scope
• Arithmetic and relational operators
• Arrays and strings
• For-each loops and if conditions
• Functions and higher-order functions
• Geometry and topology
• Attributes and groups
• Encapsulation
• Debugging and errors

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Weightage

• Exercises: 5 x 5% (drop 1) = 25%
• Peer Review: 5% Activity on Slack.com
• Final Project: 10% + 10% + 50%

Deadlines

• Exercises will be sent out on Friday evening
• Deadline for submission, the following Friday at midnight

Holidays

• Chinese New Year 16 & 17 Feb 2018 (Fri & Sat)
• Good Friday 30 Mar 2018 (Fri)*