Learning Portfolio (20%)

Quick Summary
Type Weight Deliverable
Individual 20% • Completed Learning Portfolio.
• Submitted through the Individual Repository.

1 The Learning Portfolio

1.1 What is the Learning Portfolio

The Learning Portfolio is a comprehensive record of what you will learn in the first six weeks of the course. Your Learning Portfolio will be maintained on your computer (locally) and a cloud platform called GitHub Classroom. The content of the Learning Portfolio will consist of various examples, walk-throughs, and exercises that I have incorporated into the learning units of the first half of the course. More specifically, you must work through and reproduce (no! not just copying and pasting) all this content in the form of Jupyter notebooks, a cool way to use Python for scientific work.

The material from your Learning Portfolio will also be revisited during the individual viva assessment.

1.2 Why this assessment good for you

In this assessment, the emphasis is on ‘learning by doing.’ You will actively engage with Python and computational concepts, enhancing your learning through hands-on activities. This approach will deepen your understanding and equip you with practical skills highly valued in the industry, like using Git, GitHub, and Jupyter; these will be good for your CV.

2 How to Develop Your Learning Portfolio

2.1 Standard Operating Procedure

The Learning Portfolio is a way for you to quickly learn how to talk and use Python. I have implemented several strategies to help you make the most of this learning process. Specifically, there is a standard procedure of Engage \(\longrightarrow\) Review \(\longrightarrow\) Revise \(\longrightarrow\) Finish, that you must follow in growing your Learning Portfolio.

Engage refers to engaging with the content and reproducing and working out the exercises of a learning unit. For instance, if you are on the unit Fundamentals(Need), you will work on a corresponding file called fundamentals_need.ipynb in your Learning Portfolio.

Review Once you have reproduced the content and worked on the exercises, you will submit it for review by a human reviewer. For this, you will use an interface called NBReviewer, embedded in GitHub Classroom.
This reviewing process should be initiated by you by submitting a commit of the form ‘READY FOR REVIEW FILE_NAME’ ‘COMPLETED FILE_NAME’.

Revise The reviewer will get back to you with suggestions and improvements. You must respond and adjust your notebook based on the feedback given to you by the reviewer.

Finish Once you have responded to the reviewer’s comments to her satisfaction, you will have completed that unit and can then move on to the next unit Fundamentals(Good).

Important

Everyone must complete all the Need-to-know and Good-to-know portions of the Learning Portfolio.

2.2 Practicalities

I will highlight three ways you can work on your Learning Portfolio, depending on your preferences.

Guided

Attend lectures and follow along. I will cover all content, barring exercises, which you should work on in the tutorials. This option is well-suited for those who prefer structured learning and continuous guidance.

Semi-Autonomous

Attend both lectures and tutorials, but manage your learning independently. Should you require assistance, speak to one of the instructors. This option is tailored for those seeking a blend of independence and some support.

Autonomous

Choose not to attend lectures or tutorials but work through the content independently. This option demands high self-motivation and discipline, ideal for those who prefer setting their own pace.

Caution

The downside of this option is that you might have a hard time identifying group mates. So, I recommend the previous two options instead.

2.3 You are not alone

There are several support systems in place to make this journey easy for you.

  1. Face-to-face feedback and assistance from the instructors during the lectures and tutorials.
  2. In class, Q & A is using PollEverywhere.
  3. Automated feedback from ChatGPT.

3 Grading

3.1 Rubric

# Criterion Needs Improvement Satisfactory Good Accomplished Distinguished
1 Completeness Notebooks are largely incomplete or missing. Many notebooks are incomplete or missing significant detail. Most notebooks are complete. Minor details missing in few notebooks. All notebooks are complete and thoroughly detailed.
2 Correctness Major errors; outputs are incorrect or missing. Frequent errors that hinder understanding. Some errors that affect the outcomes. Minor errors present but do not affect overall understanding. No errors in execution; all outputs are as expected.
3 Understanding Misunderstands or cannot apply concepts. Limited understanding; struggles to apply concepts. Basic understanding with noticeable gaps. Good understanding with minor misconceptions. Demonstrates deep understanding and ability to apply concepts.
4 Responses to Reviewer Does not address reviewer comments. Addresses some comments but misses key issues. Adequately addresses most comments. Addresses all comments with thoughtful responses. Engages deeply with comments, providing comprehensive and insightful responses.
5 Tool Proficiency Unable to use tools or does not use them at all. Limited use; struggles with basic features. Adequate use of tools; basic features are utilised. Good proficiency; uses most features effectively. Highly proficient with Git, GitHub, and Jupyter.

4 Instructions to the Graders/Reviewers

In the name of transparency

In the interest of complete transparency, I have made the grading instructions available to everyone. I hope this information about the behind-the-scenes workings will help to provide a clear understanding of our assessment process.

Graders… before proceeding

If you have not done so, please refer to the general grading instructions first.

4.1 Important!

The primary role of the Learning Portfolio is to quickly bring students up to speed with the basics of Python. The main goal of this course is to get students to think and solve problems in science using computers (i.e Python). The Learning Portfolio is a preparatory exercise to this end. The Learning Portfolio is not meant to be an exhaustive exploration of Python’s cool features and subtleties.

So, in summary, when giving feedback, please remember:

  • Focus on Essentials:
    • Your feedback should concentrate on the basics of Python, ensuring students grasp key concepts quickly and effectively.
    • Steer clear of advanced topics not covered in the course material. Please let me know if you identify any concepts you think are crucial that I have missed out.
  • Threshold Concepts:
    • Prioritize concepts that are critical for future application in Python. If a student struggles with such a concept, offer detailed guidance and request further revisions.
    • These foundational ideas are vital for practical coding and understanding computational methods in science. Some of these are:
  • Variable types,
  • Data Structures,
  • Loops,
  • Comprehensions,
  • Functions/encapsulation,
  • Branching and decisions,

4.2 Grading procedure

  1. Each Learning Portfolio mentor will be assigned a set of students and given access to their GitHub Classroom repositories.
  2. The students have been instructed to submit a commit ‘READY FOR REVIEW FILE_NAME’ ‘COMPLETED FILE_NAME’ once they are ready to revise the file.
  3. Please use NBReview to communicate your comments to the students.
  4. Please alert me or the teaching assistant if any student finds the content too challenging and requires additional help.
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