This LabVenture Professional Learning Module is composed of 4 parts that focus on building your knowledge of climate and ecosystem change and the components of data and science inquiry that help us investigate those changes - from strong connections to locally focused and globally relevant background knowledge, to the tentative nature of scientific conclusions. You will engage with materials, activities, and reflections that highlight how collaborative, emergent, and cyclical science is. Each part seeks to support you to bring data, data skills, and dispositions back to your learners by featuring local datasets that add to the story of climate driven ecosystem change in the Gulf of Maine while also probing you to consider how these changes may relate to changes at the global scale.
This work is made possible through the funding provided by NASA for our Real World, Real Science Project, and this module was designed specifically to support educators looking to build on the LabVenture experience and use the LabVenture Curriculum modules. We also designed this to help build educator comfort around an array of topics and skills that are more broadly relevant. The parts of this module were designed to be done in sequence.
Each part of the module builds content knowledge and comfort with data and science inquiry learning themes and connects you with resources you can bring back to your learners and is designed to take 1 to 1.5 hours.
Part 1 - Climate and Ecosystem Change in the Gulf of Maine
- You feel empowered and prepared with a current scientific understanding of changes in the Gulf of Maine ecosystem, and how changes in the Gulf of Maine are a local instance of global change.
- You feel empowered with an understanding of science as a collaborative process that includes a range of people, skills, activities, and data sources.
- You have increased comfort and resources to support learners engage in the data and context surrounding a changing Gulf of Maine ecosystem.
Part 2 - Data Literacy First Steps
- You recognize that a key component of data literacy is using tools that allow you to make data moves - work with the data in ways that help you make sense of it.
- You understand how to visualize data in the best way to see the story it is telling and can do this for multiple datasets.
- You can explain why certain data moves elicit different understanding of data and can summarize why different organizations of data and visualizations provide different information.
- You feel prepared to bring a tool like CODAP and the idea of making data moves back to your learners.
Part 3 - Variability and Distributional Thinking
- You feel comfortable having meaningful conversations with learners about and with data using informal statistical thinking and language.
- You feel confident supporting your learners in being able to visualize and describe variability in data and to compare distributions.
- You understand the importance of engaging learners in a progression of learning about data that starts with informal statistical thinking focused on variability within one dataset and ends with comparing two distributions.
Part 4 - Patterns and Trends
- You develop comfort in identifying trends and patterns in datasets while understanding the tentative nature of this understanding
- You build comfort representing and organizing data in different ways in order to answer different questions and reveal patterns and relationships with the data
- You feel comfortable using information from multiple graphs to describe changes within a system