e-learning Python for Ocean Mapping - Empowering the next generation of ocean mappers with effective programming skills
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This document discusses an e-learning course called E-Learning Python for Ocean Mapping that teaches Python programming skills to students studying ocean mapping and related fields. The course aims to teach basic programming concepts and habits using Python, which was chosen as the language because it is simple to learn, increasingly popular, and freely available. It is not intended as a full Python course but will provide enough skills for lab assignments. The timeline outlines the development, beta testing, and rollout of the course between July 2019 and December 2019.
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e-learning Python for Ocean Mapping - Empowering the next generation of ocean mappers with effective programming skills
- 1. E-LEARNING PYTHON FOR OCEAN MAPPING EMPOWERING THE NEXT GENERATION OF OCEAN MAPPERS WITH EFFECTIVE PROGRAMMING SKILLS G. MASETTI, S. DIJKSTRA, R. WIGLEY, S. GREENAWAY, D. MANDA, A. ARMSTRONG, AND L. MAYER V3
- 2. OCEAN MAPPING MARINE BIOLOGY MARINE SCIENCES ENVIRONMENTAL ENGINEERING COMPUTER SCIENCE OCEAN ENGINEERING EARTH SCIENCE
- 4. WHICH LANGUAGE? •Simple to learn
- 5. “[..] the best choice in term of clarity and functionality of the language is provided by Python.”
- 7. WHICH LANGUAGE? •Simple to learn •Increasingly popular
- 10. WHICH LANGUAGE? •Simple to learn •Increasingly popular •Freely available after UNH!
- 11. TEACHING GOALS 11 Not a full course on how to program in Python, but … TO TEACH PROGRAMMING HABITS AND SKILLS TO FAMILIARIZE WITH KEY PROGRAMMING CONCEPTS TO INTRODUCE THE EFFECTIVE USE OF ONLINE RESOURCES TO PROVIDE ENOUGH PYTHON SKILLS FOR LAB ASSIGNMENTS
- 12. 9-Dec-2019 Fall Term ends INTRODUCTION TO OCEAN DATA SCIENCE TIMELINE PROGRAMMING BASICS WITH PYTHON 26-Aug-2019 Fall Term begins DEVELOPMENT & BETA TESTING 1-Jul-2019 Official Release 24-Jan-2019 1st Committee Meeting Online Learning Review Meeting 2 weeks 2 weeks
- 13. IMPLEMENTATION
- 15. IMPLEMENTATION
- 16. IMPLEMENTATION • KEY CONCEPTS • SUPPLEMENTARY INFO • EXERCISES WITH SOLUTIONS • LINK TO PIAZZA.COM
- 17. IMPLEMENTATION ⟶ USER EXPERIENCE
- 18. BETA TESTING ⟶ EVALUATION
- 19. FIRST CYCLE ⟶ STUDENTS FEEDBACK
- 20. EPOM IS ALSO AVAILABLE ON https://github.com/hydroffice/python_basics https://svn.pydro.noaa.gov/
- 21. THANKS! VISIT: https://www.hydroffice.org/epom CONTACT US: epom@ccom.unh.edu
Editor's Notes
- Good morning! My name is Giuseppe, and my talk today is about a new coding training that we have developed at the Center for Coastal and Ocean Mapping in collaboration with the NOAA’s Hydrographic Systems and Technology Branch. The training is named ePOM: e-learning Python for Ocean Mapping. This name is based on the facts that: - A large part of the training is done remotely (e-Learning). - Python is the programming language used. - The introduced concepts are tailored to ocean mapping students. I will start by identifying the motivations that have driven us to design and implement such a training [CLICK]
- Incoming students in Ocean Mapping (OM) courses come from very different backgrounds: ocean engineering, computer science, marine biology, earth science, … just to name a few of them.
- Some of these students have limited programming experience. [CLICK] Then, there is a need to ensure a minimum common level of programming skills. These programming skills are useful not only for the lab assignment, but as a powerful tool in their professional career.
- When we started to design the training, one of the first decisions to take was which programming language to use. [CLICK] The adopted solution was to use Python for three big reasons: [CLICK] 1. Python is simple to learn.
- The easiness of learning Python is also confirmed by a few papers. [CLICK] In a comparison with C and Matlab, Python was identified as the best choice in term of clarity and functionality.
- That is just one of several papers reinforcing the fitness of Python for new coders.
- Python is also increasingly popular
- It is the most selected language for teaching introductory courses in US computer science departments.
- And its popularity is confirmed by the increasingly high ranking in search engines.
- Last but not least, Python is freely available after the university studies.
- Once identified the programming language, we worked on the teaching goals. [CLICK] From the beginning, our target was NOT to put together a full course on how to program in Python, but [CLICK] we identified the following 4 teaching goals: - to teach students programming habits and skills that can be potentially translated to other programming languages - to familiarize OM students with key programming concepts (for loops, if statements, object oriented programming). - given the popularity of Python, there is a lot of material online about the language. This can be overwhelming. Thus, we want to help the students to effectively use online resources, and of course - to provide enough basic Python skills to help students with their first lab assignments. To reinforce the concept, we are not going to develop a full course on how to program in Python.
- Chronologically, we started the development of the training in January 2019. During the development, we worked on two lines of actions.[CLICK] The first one is called Programming Basics with Python, planned to happen before the beginning of the Fall Term.[CLICK] The second one, named Introduction to Ocean Data Science, during the Fall Term.[CLICK] The target of Programming Basics with Python is to teach basic programming concepts with a focus on OM applications. This line of action has 2 phases. A first phase that is asynchronous and it provides online learning through a remotely-hosted collection of Jupyter notebooks. The second phase consists of an in-person meeting during the orientation week. This meeting is mainly to answer students questions, to evaluate their understanding of the main concepts, and to stimulate collaboration among students.[CLICK] The Foundations of Ocean Mapping Data Science is intended to act as a connector to the OM courses. It consists of 2 modules that are part of Applied Tools for OM. The first module will be during the first 2 weeks of the Fall Term. It has a focus on data analysis and visualization using popular Python libraries. The second module will be at the end of the Fall Term. And it introduces the student to popular tools (like git) and approaches on how to develop research code.
- For the implementation, we used JupyterHub. What is JupyterHub? It is a Python environment that runs on a multi-user server. With JupyterHub, all the students get an identical computing environment.
- JupyterHub has been adopted for teaching by several univesities.
- A key feature of this solution is that there is no need install Python (and other third-party libraries) on the student’s computer. The students will only need a modern browser and an Internet connection.[CLICK] Once logged, the landing page provides a list of notebooks with a short description of the teaching tasks.[CLICK] The student then can click on the notebook of choice.
- To facilitate the learning, we visually mark the key concept [CLICK]. We identify what are the supplementary info [CLICK]. We provide exercises and related solutions that are shown by clicking on them [CLICK]. We also provide a link to Piazza.com where the students can interact with the instructor about doubts and clarifications.