Better understanding of hydrologic process through data-driven learning
facilitated by collaborative open web-based platforms
- Belize Lane,
- Irene Garousi-Nejad,
- Melissa Gallagher,
- Dave Tarboton,
- Emad Habib
Belize Lane
Utah State University
Corresponding Author:belize.lane@usu.edu
Author ProfileAbstract
The era of "big data'' promises to provide new hydrologic insights, and
open web-based platforms are being developed and adopted by the
hydrologic science community to harness these datasets and data
services. This shift accompanies advances in hydrology education and the
growth of web-based hydrology learning modules, but their capacity to
utilize emerging open platforms and data services to enhance student
learning through data-driven activities remains largely untapped. Given
that generic equations may not easily translate into local or regional
solutions, teaching students to explore how well models or equations
work in particular settings or to answer specific problems using real
data is essential. This paper introduces an open web-based learning
module developed to advance data-driven hydrologic process learning,
targeting upper level undergraduate and early graduate students in
hydrology and engineering. The module was developed and deployed on the
HydroLearn open educational platform, which provides a formal
pedagogical structure for developing effective problem-based learning
activities. We found that data-driven learning activities utilizing
collaborative open web platforms like HydroShare and CUAHSI JupyterHub
computational notebooks allowed students to access and work with
datasets for systems of personal interest and promoted critical
evaluation of results and assumptions. Initial student feedback was
generally positive, but also highlights challenges including
trouble-shooting and future-proofing difficulties and some resistance to
open-source software and programming. Opportunities to further enhance
hydrology learning include better articulating the myriad benefits of
open web platforms upfront, incorporating additional user-support tools,
and focusing methods and questions on implementing and adapting
notebooks to explore fundamental processes rather than tools and syntax.
The profound shift in the field of hydrology toward big data, open data
services and reproducible research practices requires hydrology
instructors to rethink traditional content delivery and focus
instruction on harnessing these datasets and practices in the
preparation of future hydrologists and engineers.18 Mar 2021Submitted to Hydrological Processes 22 Mar 2021Submission Checks Completed
22 Mar 2021Assigned to Editor
23 Mar 2021Reviewer(s) Assigned
05 May 2021Review(s) Completed, Editorial Evaluation Pending
18 May 2021Editorial Decision: Revise Minor
07 Jun 20211st Revision Received
18 Jun 2021Submission Checks Completed
18 Jun 2021Assigned to Editor
18 Jun 2021Reviewer(s) Assigned
18 Jun 2021Review(s) Completed, Editorial Evaluation Pending
18 Jun 2021Editorial Decision: Accept