The
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Lesson 1 is intended to introduce the basics of Argo, its + objectives and key elements, such as the structure of the Argo + floats and their operation in the open ocean.
+Lesson 2 focuses on the data coming from the Argo network, from + its organization to its accessibility. Data quality control is + also addressed through its two main modes: Real-Time and + Delayed-Mode.
+Lesson 3 is the AoS hands-on component, and it requires basic + knowledge of Python. It provides a set of instructions for + preparing a Python environment in case the user wants to run the + Python Jupyter Notebooks on a local machine. This environment + already includes recommended packages. The walk-through of Lesson + 3 shows how to work with the netCDF format, how to access and + process Argo data, and create visualizations to enhance + understanding of the information derived from Argo data.
+The target audience of the AoS is high school, undergraduate or + early graduate students. The programming content in Lesson 3 offers an + ideal opportunity to support students pursuing a technical or science + curriculum. Lessons 1 and 2 form a closed module and can be used + independently by learners who wish to focus solely on Argo. It is + recommended not to skip any lesson in the AoS, as the content is + carefully structured from simpler to more complex concepts, providing + a progressive learning experience. Users have the opportunity to + self-assess their learning progress through the proposed interactive + self-assessments in the AoS.
+The AoS has been designed to be expanded in the future to follow + the implementation of new features in the Argo program.
+Argo
+ (
Although data from Argo
+ (
The Argo Online School leverages the potential of e-learning tools
+ to provide a variety of resources to users, thereby promoting and
+ enhancing access to and use of Argo data. In this way, the AoS is
+ defined as an e-learning tool that offers an interactive environment
+ similar to other established educational platforms. It is a tool with
+ significant educational potential that aims not only to demonstrate
+ the basic steps for using Argo data but also to empower users to
+ tackle future
The AoS was presented at the
+
The AoS aims to teach the fundamental concepts needed to understand
+ and use Argo data. It does not seek to cover every aspect of the Argo
+ program, as comprehensive documentation is available from the Argo
+ Data Management Team
+ (
The AoS is a set of videos and hands-on Python-driven Jupyter + notebooks, designed for high school, undergraduate or graduate + students in any discipline, and it offers:
+-
+
An overview of the Argo program and an assessment of the need + for Argo.
+A description of how the Argo data is organized.
+A description of how to access the Argo data.
+A description of the main characteristics of the Argo data + format: the netCDF.
+A review of the main characteristics of the quality controls + used: Real-Time and Delayed-Mode.
+Step-by-step instructions on data access, processing, and + product generation, through the execution of commands based on the + programming language Python.
+All content is divided into three lessons: 1. The Argo Program, + that describes the basic concepts of this ocean observing network; 2. + The Argo Data, that describes how the data is organized; and 3. Using + the Argo data, that takes the knowledge of the previous sections and + Python-driven Jupyter notebooks to teach how to use the data. Finally, + a quiz section is included for self-assessment.
+Lessons 1 and 2 are designed for students with knowledge comparable + to that acquired in high school, this is, basic knowledge about the + relationships between the Earth’s processes, weather and climate; and + basic skills in interpreting maps, charts, and tables to organize and + analyze data
+These lessons are aimed at users with minimal or no knowledge of + the Argo network, and they are a closed module and could be used by a + learner without using Lesson 3, assuming the goal is simply to learn + about Argo. Lessons 1 and 2 contain 32 short videos and 14 chapters + and require about 5 hours to completed. Lesson 3 is intended for + advanced users, as it requires basic programming skills in + Python.However, Lesson 3 follows a step by step approach, to + facilitate the transition of users coming from Lessons 1 and 2. The + basic recommendations and instructions for configuring the hands-on + section of the AoS are also provided, whether the users want to work + online or if they want to work on their local computer. Specific + python libraries and packages are recommended to guarantee the correct + functioning of the AoS. Lesson 3 contains 8 short videos and 14 + chapters and requires about 10 hours to be completed, assuming basic + knowledge of Python.
+The AoS has been developed using markdown, Python driven Jupyter
+ notebooks
+ (
The AoS is accessible through the Euro-Argo webpage
+ https://www.euro-argo.eu/argo-online-school, but all the content that
+ makes it up is hosted in a public GitHub repository.:
+
Given the structure of the AoS, it could be used for educational + purposes. For high school students, Lessons 1 and 2 could be a project + to identify scientific questions that ocean observations, like those + from Argo, may help address while developing essential know-how. For + students with a curriculum that includes programming in Python, other + projects could involve finding the seasonal change in surface + temperature at a specific ocean and comparing it with changes at 1,000 + m or 2,000 m, or explaining the trajectory of a given float, which can + be quite challenging. Teachers are welcome to open an issue in the + github repository to get assistance in how to develop new + projects.
+As part of the Argo community, the AoS follows the same philosophy + regarding data access. To ensure barrier-free learning, the + information and data provided in the AoS is open access to the public + and free of charge and therefore, no subscription is required
+The AoS has been possible thanks to the collaboration of the
+ Euro-Argo members, the Argo Steering Team
+ (
The audiovisual work has been recorded and edited by Rafael Méndez
+ Pérez
+ (