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Guided learning journeys that build knowledge step by step.
category · Learning · slug · learning · 7816 Paths
7816 Paths · page 487 / 782
This learning path introduces high school students to numerical methods for solving environmental models. Starting with basic calculus, it covers the Euler method, finite difference approximations, and essential concepts of convergence and stability, enabling learners to apply these techniques to simple environmental models.
This learning path introduces high school students to the concepts and methods of sensitivity and uncertainty analysis in environmental models. Starting with statistics and modeling basics, it progresses to local and global sensitivity analysis, uncertainty propagation, and Monte Carlo methods, culminating in practical application and interpretation.
This learning path introduces high school students to the concepts and practices of calibrating and validating environmental models. It covers essential statistics and modeling foundations, parameter estimation, sensitivity analysis, and goodness-of-fit measures, culminating in a structured approach to model validation.
This learning path equips high school students with the essential knowledge and skills to understand and prepare environmental data for modeling. It covers data types, sources, quality, preprocessing, and basic statistics, culminating in the integration of data into environmental models.
A beginner-friendly path introducing core programming concepts using Python, tailored for high school students interested in environmental modeling. Learn variables, loops, conditionals, and functions, and apply them to simple environmental data tasks.
This learning path introduces high school students to the practice of building conceptual models of environmental systems. Starting with foundational concepts of systems and environmental problems, learners will develop skills in defining problems, identifying variables, and creating conceptual diagrams that capture system relationships.
A beginner-friendly path introducing systems thinking concepts and their application to environmental issues. Learners will explore systems, feedback loops, stocks and flows, causal loop diagrams, and dynamic behavior through practical examples.
This learning path introduces high school students to the fundamental mathematical concepts needed to model environmental phenomena. Starting with basic algebra, it progresses through functions and equations to linear and difference equation models, culminating in a simple environmental modeling project. The path emphasizes practical applications and builds a strong foundation for further study.
This learning path introduces high school students to the purpose and types of environmental models. It covers what a model is, why models are used, different types of models, their applications, and the basic modeling process.
This learning path equips graduate students with the knowledge and skills to design and conduct rigorous research in soil science. It covers research design, field and laboratory methods, data analysis, literature review, and research ethics, emphasizing the integration of soil science and statistics.