Overview of 73

Hello and Welcome!

Welcome to SP2273: Working on Interdisciplinary Science, Pythonically. Thank you for joining us in 73¹.
I am Chammika Udalagama, the course coordinator². This page offers a quick overview of the course’s key features.

1 Things you should know about 73

1. It’s about solving problems
   One of the key expectations of a university graduate is the ability to solve problems effectively. So a big part of my job is to help you become a confident and capable problem-solver.

   To do that, we will work on the following in 73:

   • tackling real-world problems in scientific and professional contexts,
   • developing self-directed learning habits,
   • strengthening collaboration and communication skills.

   So, 73 is designed to make you a super problem-solver.

2. Learning is not a spectator sport
   The design of 73 reflects my belief that learning happens through doing. This is a hands-on course with a healthy mix of individual and group work. We will focus on both foundational ideas and practical applications.

3. It’s not really about Python
   While Python is our main computational tool, this is not a course for learning Python in depth. Instead, Python serves a larger purpose: it is a way to explore how computational thinking can support and enrich scientific inquiry.

4. Transferable skills
   I also see 73 as a kind of service course. It helps you build transferable skills in computation, analysis, and communication—skills that are valuable across disciplines and careers.

2 Highlights

Let me first share some highlights of 73. I will explain these in greater depth later.

• The module is extensively hands-on in design,
  
• Ample support, scaffolding, and feedback will guide your learning journey,
  
• In Weeks 1 to 6, you can choose a pace and form of learning that suits you,
  
• A dedicated website hosts all course content,
  
• We use industry-standard platforms and tools (e.g. Git, GitHub, Jupyter),
  
• Differentiated learning,
• Mastery learning,
• Webcasting is available during Weeks 1 to 6.

The course is broadly split into two parts:

First Half (Weeks 1 to 6)

Weeks 1 to 6 focus on developing and practising fundamental skills through individual work. This part of the course is mostly self-paced and centres on the Learning Portfolio. I have outlined several options for how you can navigate this part of the course in the sections below.

Second Half (Weeks 7 to 13)

Weeks 7 to 13 involve group work, where you will apply your core skills to solve problems and broaden your learning.

In this second half of the course, you will collaborate with others on two key activities:

1. Application Challenge
   
2. Group Mini-Project

These experiences are designed to deepen your understanding, strengthen collaboration, and give you the opportunity to apply your skills in open-ended, interdisciplinary settings.

3 Course Material

3.1 Differentiated Content

You come from a variety of disciplines, with different levels of experience and motivation. Some of you will be eager to charge ahead, while others will prefer to explore the content at a steadier pace. Both approaches are valid.

To support this, we use a form of differentiated instruction (Tomlinson (2017)) that allows you to engage with the material in a way that suits you. The content is organised into modular units, some of which are optional.

Each unit in the first half of the course is labelled as:

1. Need-to-Know
   
2. Good-to-Know
   
3. Nice-to-Know

You are expected to fully understand everything in the Need-to-Know category and be comfortable with the Good-to-Know material. The Nice-to-Know sections are optional extras—icing on the cake for those who want more.

Remember

Nice-to-Know content is optional.

3.2 Where to Find the Content

Python is used extensively throughout the SPS journey. Because of this, we need a Python resource that is tailored to our context and accessible to all SPS students. To meet this need, the content is hosted on a dedicated website: sps.nus.edu.sg/python, designed specifically for the SPS community.

The material you will use in the first six weeks of 73 is found in the Python Basics section of that site. Your Learning Portfolio will be based on this content.

3.3 Recommended Way to Use the Notes

I have made the notes as simple and self-explanatory as possible. By “simple”, I mean that they contain only the essential material to get you started. There are three things you should do:

Step 1: Run the Example Code

The notes contain many example code snippets. Start by running the code. While you can copy and paste it, I strongly recommend typing it out yourself. This helps build motor memory.

Step 2: Experiment and Predict

Next, modify the code. Before running it, try to predict what will happen. Predicting outcomes engages you more deeply and helps solidify your understanding.

Step 3: Receive Feedback

Feedback is essential for learning. Here are two ways to get it:

1. Submit Your Topic Notebooks in Addition to the Exercises
   
2. Speak with Instructors. Use tutorial or lecture time to ask questions and get clarification.

Remember, learning is not a spectator sport. Research in cognitive science shows that real learning happens through active participation and deliberate practice (Ericsson, Krampe, and Tesch-Römer 1993). Learning something new is effortful; if it feels too easy, you may not be learning effectively.

4 Lectures and Tutorials

I will go through all the Need-to-Know and Good-to-Know material during the lectures. Exercises will be completed by you during tutorials. However, my pace may not work for everyone. You are encouraged to set your own pace. Below are three ways to approach the first six weeks and the Learning Portfolio, depending on your preferences. Regardless of your choice, please ensure all work is completed by the end of Week 5.

Option 1: Guided

Attend lectures and follow along. I will cover all the content, except for exercises, which you should complete during tutorials. This is ideal for those who prefer structured learning and consistent guidance.

Option 2: Semi-Autonomous

Attend both lectures and tutorials but manage your learning independently. If you need help, you can reach out to an instructor. This is for those who want a mix of support and independence.

Option 3: Autonomous

Choose not to attend lectures or tutorials and instead work through the material independently. This option requires strong self-motivation and discipline.

Caution

The downside of this option is that it may be harder to find group mates for the project. Unless you are confident in managing this, I recommend one of the first two approaches instead.

References

Ericsson, K. Anders, Ralf T. Krampe, and Clemens Tesch-Römer. 1993. “The Role of Deliberate Practice in the Acquisition of Expert Performance.” Psychological Review 100 (3): 363–406. https://doi.org/10.1037/0033-295X.100.3.363.

Tomlinson, Carol A. 2017. How to Differentiate Instruction in Academically Diverse Classrooms. Third edition. Alexandria, Virginia: ASCD.

Footnotes

1. We usually refer to our SPS modules by their last two digits.

2. If you are wondering, inspired by one of my favourite authors (David J. Griffiths), I write all my course notes in the first person.