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Product: Watershed Classroom and Data Lab

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Watershed Classroom and Data Lab Learning Platform

Watershed Data Lab provides schools with web-based tools to easily incorporate data science and watershed into existing NGSS curriculum. Data management, geographic information systems, cataloguing, programming, experimental design, field data collection techniques and protocols are all skills needed by our future workforce and can be learned using standard concepts like watershed science. The core components of the WDL platform include visual catalogs (for images, videos, documents), a mapping application (for learning GIS, viewing data and map features), wiki (for definitions and references), a data services engine (for aggregating and using public data) and data analysis tools. Schools can use education modules and user templates for teaching data science fundamentals, collecting and analyzing data, making assessments and telling stories. The extensive and flexible content management system allows schools to retain and archive valuable content while also safeguarding the security and privacy of students from external online threats. The WDL platform fosters student inquiry into the natural world that enforces key principles of data management and analysis environmental sustainability and natural resource management, while fostering environmental stewards from a young age.

Student Learn Data Science Concepts Through Watershed Science

Today’s data tools are designed for scientific or business analysis (SAS,R, Python, SQL,Scipy). The complicated and abstract nature of these tools make it difficult to integrate data science into K-12 curricula. K-12 classrooms can benefit from a generalized data learning platform that can supplement existing curriculum and enhance real world experiences. We see an emerging opportunity to develop such a platform for schools focusing on the watershed science disciplines. Watershed science is a familiar, data rich and complex system that requires a multidisciplinary approach to analyze and problem solve. These qualities combined with the proliferation of publicly available environmental data services from local, state, federal government and NGOs create the ideal market opportunity to bring a Watershed Data Lab (WDL) to America’s school’s.
The WDL Platform Works with Schools and Students to Better Understand Your Needs:
How do students learn data science concepts through watershed science investigations involving field studies, data analysis and watershed assessment? | How much data is required for impactful comprehension of watershed health? How early can students synthesize data to make reasonable assessments? | How do teachers learn to integrate data tools into their experiential learning instructional approaches? | Does exposure to a comprehensive data picture improve multidisciplinary understanding of a watershed or impact stewardship? Based on experiential learning and uses next generation science standards (NGSS) | Supports project based learning and field studies

  • 34 North hosts hundreds of datasets and extensive knowledgebase to establish baseline data understanding of the California environment
  • Students gather, present and synthesize data to tell the story of our watersheds
  • Students learn by building interactive maps, wikis, discovering data and digging deeper into topics
  • Data collected by students allow for analyses that culminate as stories about field studies, watershed health and local ecosystems
  • Stories are used to communicate science to their peers and community

Data Program Development

  • Students learn data management, geographic information systems, cataloguing, programming, experimental design, field data collection techniques and protocols, and data QA/QC procedures
  • Students are taught how to develop a data program that produces quality data that can be used by peers and colleagues
  • Students learn how to analyze and tell stories using data

Watershed Data Lab Product Features

  • Comprehensive Watershed Data Data Library
  • Curriculum review and integration with platform
  • Introduction to existing curriculum and templates supported by the platform
  • Integrate existing reference libraries and knowledgebase
  • Public facing project templates
  • Reporting dashboards

Customize the Platform for Your School or Program

  • Customize application for participating school(s) to include: data, maps, documents, images, wikis and data analysis tools
  • Set up learning modules
  • Archive current knowledge

Extensive Data Analysis

Using Next Generation Science Standards

Science and Engineering practices:

  • Design, evaluate, and/or refine a solution to a complex real-world problem, based on scientific knowledge, student-generated sources of evidence, prioritized criteria, and tradeoff considerations (experiment design and field data collection, in addition to data standards, field protocols, and QAQC procedures)

Cross Cutting Concepts:
  • Environmental Feedback to stabilize or destabilize a system (restoration, water quality contamination)
  • Cause and effect relationships, suggest and predict, if x then y

Disciplinary Core Ideas:
  • Human Impacts on Earth Systems- environmental sustainability and biodiversity, responsible natural resources management
  • Ecosystem Dynamics, Functioning and Resilience- climate change, awareness and understanding
  • Biodiversity and Humans- how we depend on our living world for living and resources. How we effect and change our watershed/environment Performance Expectations
  • students learn how to change/decrease/mitigate their impact on the environment. Increase or maintain biodiversity. (learning and application, reports, presentation, education of their peers, parents, other community members).