I-Corps L: A User-Discovery, Hypothesis-Driven Exploration of Potential Scaling and Sustainability of Innovations in Water Education

University Of Louisiana At Lafayette, Lafayette LA

Investigators

Abstract

The objective of this project is to engage in a hypothesis-driven, customer-discovery process to inform the scalability and sustainability of educational innovations in the field of hydrology and water resources education. The HydroViz educational innovation was developed as a set of web-based, active-learning modules for undergraduate hydrology and water resources education with extensive use of water data and modeling resources. The project responds to the increasing calls by the water education communities for a broad reform in hydrologic education as a requisite for making significant advances in the theory and practices of water resources engineering and earth sciences. While the immediate end users of the potential development is in the field of water resources and hydrology, the outcomes of this I-Corps L effort will have an impact on the broader community of users who can benefit from place-based education and who can take advantage of geospatial technologies, web-based resources, and scientific data sharing. The project will also contribute to resolving lasting challenges that confront digital learning and cyber-education efforts that often fail to achieve fully scalable and sustainable outcomes. The project will produce knowledge on how to scale and sustain educational innovations that are presented in the form of digital learning resources. The hypothesis, developed based on classroom implementation and assessment data, as well as feedback from instructors, indicates that there is a user need for developments such as those initiated in this project and that there is an opportunity for the project to engage in a scaling effort that is guided by a rigorous process of customer discovery and hypothesis validation. A hypothesized scalability and sustainability solution is to establish a general platform for the learning modules to connect to and interoperate with community-based hydrologic data and model sharing resources, and thus provide a user capability by which independent users can develop their own modules. The envisioned solution will go through a hypothesis validation and customer discovery process as part of this project.