This project is creating a new instructional strategy and new learning materials using data- and modeling-based modules that are enabling undergraduate students to better understand cause-effect relationships, form and test hypotheses, and learn how to integrate the latest tools for better understanding of hydrologic theory and processes. Collaborators at two research universities, a liberal arts college, and Chandler/Gilbert Community College are developing and testing the educational modules, and an editorial board comprising geosciences and engineering faculty from around the USA is supervising module development and formative evaluation. The project is creating an organized community of practice to develop, share, and publish data- and modeling-driven hydrology educational modules made available through the Science Education Research Center (SERC) website.
This project is using a structured process of collaborative community curriculum development to bring together a core user community and design a system to meet the needs of a broad range of hydrology educators. It is rigorously assessing the effectiveness of the technology on students' learning outcomes by comparing traditional lecture-based instruction with data- and modeling-driven instruction designed to enhance hydrologic learning among students. This project is achieving a broad impact by piloting a model of community development, evaluation, and dissemination of hydrologic cyberlearning modules.
The goal of this research is to improve the technical depth and professional breadth of training that hydrologists receive in their undergraduate degrees, by incorporating formal use of hydrology data, modeling, and visualization techniques into the classroom. This work is important because hydrologists protect the public from flooding and do the fundamental work to protect and provide water supplies. That work is increasingly difficult owing to climate change and much higher demands on water supplies in the 21st century, because hydrologists cannot rely on historical records of flooding and streamflow to guide their decisions as in the past. We need hydrologists with a more holistic and integrated understanding of water and climate systems, and more complete mastery of modeling concepts, along with the ability to make use of the best available current scientific data. This can be achieved by using models and data in the classroom, in coordination with the best of traditional conceptual instructional methods. Using controlled classroom experiments, this research has demonstrated that data and modeling driven techniques go beyond traditional lecture methods to improve both students’ mastery of the conceptual fundamentals and also the professional roles of hydrologists, along with (of course) their practical computer skills. We have also made advances in the creation of the web-based system and communities of practice that will author and publish data and modeling based curriculum materials. In coming years, we hope that his work will provide the foundation for a 21st century approach to hydrology education in the University.
