Development and Evaluation of the Online Watershed Learning System (OWLS)

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Virginia Tech


Cyberlearning has the ability to connect learners from diverse settings to educational resources regardless of the learners' proximities to traditional classroom environments. Prior research has shown that hybrid learning systems more effectively improve student learning than do either traditional or cyberlearning approaches used individually. The Online Watershed Learning System (OWLS) is an interactive cyberlearning system for use in hybrid education. It serves as the end user interface of the Learning Enhanced Watershed Assessment System (LEWAS), a watershed monitoring system for use in research and education. The LEWAS/OWLS has been integrated into 26 courses. Within the theoretical framework of situated learning, the OWLS uses data and imagery to situate users at the LEWAS site. The current research has the dual goals of developing the OWLS and evaluating its effectiveness within a hybrid learning environment as part of watershed monitoring education. Within goal 1, HTML5, CSS and JavaScript code (11,112 lines) were used to achieve platform independence, and student and faculty feedback suggests a hierarchy of cyberlearning interface features, where anywhere/anytime access is the most important class of features for these users followed by real-time data visualization, system background information and how-to-use information in descending order. For students at the community college freshmen, university senior and graduate levels, goal 2 investigated how much the OWLS increases student learning of environmental monitoring topics and motivates them to study these topics. For this goal, use of the LEWAS/OWLS increased learning and motivation for most students with the caveats that the these gains were not always statistically significant and that these gains may be caused by use of the LEWAS in general rather than by the OWLS component of it. Additional studies are needed to resolve these issues. Additionally, a pilot test of anonymous user tracking (11,231 page views) showed how it can be used to obtain general information about which groups of users are accessing a cyberlearning system, how they are accessing it, and how navigation through the system can be improved to better match user goals. The full results and their limitations are included along with areas for future work.



Watershed Monitoring, Cyberlearning, Remote Labs, Situated Learning