The need to adapt quickly to online or remote instruction has been a challenge for instructors during the COVID pandemic. A common issue instructors face is finding high-quality curricular materials that can enhance student learning by engaging them in solving complex, real-world problems. The current study evaluates a set of 15 web-based learning modules that promote the use of authentic, high-cognitive demand tasks. The modules were developed collaboratively by a group of instructors during a HydroLearn hackathon-workshop program. The modules cover various topics in hydrology and water resources, including physical hydrology, hydraulics, climate change, groundwater flow and quality, fluid mechanics, open channel flow, remote sensing, frequency analysis, data science, and evapotranspiration. The study evaluates the impact of the modules on students’ learning in terms of two primary aspects: understanding of fundamental concepts and improving technical skills. The study uses a practical instrument to measure students’ perceived changes in concepts and technical skills known as the Student Assessment of Learning Gains (SALG) survey. The survey was used at two-time points in this study: before the students participated in the module (pre) and at the conclusion of the module (post). The surveys were modified to capture the concepts and skills aligned with the learning objectives of each module. We calculated the learning gains by examining differences in students’ self-reported understanding of concepts and skills from pre- to post-implementation on the SALG using paired samples t -tests. The majority of the findings were statistically at the 0.05 level and practically significant. As measured by effect size, practical significance is a means for identifying the strength of the conclusions about a group of differences or the relationship between variables in a study. The average effect size in educational research is d = 0.4. The effect sizes from this study [0.45, 1.54] suggest that the modules play an important role in supporting students’ gains in conceptual understanding and technical skills. The evidence from this study suggests that these learning modules can be a promising way to deliver complex subjects to students in a timely and effective manner.
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Building an Online Learning Module for Satellite Remote Sensing Applications in Hydrologic Science
This article presents an online teaching tool that introduces students to basic concepts of remote sensing and its applications in hydrology. The learning module is intended for junior/senior undergraduate students or junior graduate students with no (or little) prior experience in remote sensing, but with some basic background of environmental science, hydrology, statistics, and programming. This e-learning environment offers background content on the fundamentals of remote sensing, but also integrates a set of existing online tools for visualization and analysis of satellite observations. Specifically, students are introduced to a variety of satellite products and techniques that can be used to monitor and analyze changes in the hydrological cycle. At completion of the module, students are able to visualize remote sensing data (both in terms of time series and spatial maps), detect temporal trends, interpret satellite images, and assess errors and uncertainties in a remote sensing product. Students are given the opportunity to check their understanding as they progress through the module and also tackle complex real-life problems using remote sensing observations that professionals and scientists commonly use in practice. The learning tool is implemented in HydroLearn, an open-source, online platform for instructors to find and share learning modules and collaborate on developing teaching resources in hydrology and water resources.
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- NSF-PAR ID:
- 10289515
- Date Published:
- Journal Name:
- Remote Sensing
- Volume:
- 12
- Issue:
- 18
- ISSN:
- 2072-4292
- Page Range / eLocation ID:
- 3009
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/rs12183009
