June 14, 2015
June 14, 2015
June 17, 2015
26.238.1 - 26.238.15
Assessing Cognitive Development and Motivation with the Online Watershed Learning System (OWLS)A recent report on Challenges and Opportunities in the Hydrologic Sciences by the NationalAcademy of Sciences states that the solutions to the complex water-related challenges facingsociety today begin with education. The Learning Enhanced Watershed Assessment System(LEWAS) is a real-time watershed monitoring lab that seeks to address these complex-waterrelated challenges by improving water-related education at the community college and four yearuniversity levels. The Online Watershed Learning System (OWLS), the data sharing andvisualization component of the LEWAS, is an environmental exploration tool that gives usersaccess to historical and live LEWAS data, watershed-specific case studies, and virtual tours ofthe LEWAS watershed. By using an HTML5-driven web interface, the OWLS interactivelydelivers integrated live and/or historical remote system data (visual, environmental,geographical, etc.) to end users regardless of the hardware (desktop, laptop, tablet, smartphone,etc.) and software (Windows, Linux, iOS, Android, etc.) platforms of their choice..We have built upon a prior study that used the expectancy-value theory of motivation to showthat exposure to live watershed data via the LEWAS increased students’ levels of motivation. Apilot test of the OWLS has demonstrated positive learning gains in engineering seniors and wasoverwhelmingly viewed by students as having helped them learn hydrology concepts. The pilottest also revealed the strengths of the OWLS to be anywhere, anytime access to live system dataand interactive graphical representations of the data. Using the framework of situated learning,the current research implements the OWLS as a remote lab for both freshmen community collegestudents in general engineering courses as well as senior university students in a hydrologycourse. We seek to determine: (i) how the OWLS influences student learning with respect tocourse learning objectives, and (ii) how the use of OWLS in engineering courses impactsmotivation in students. The assessment follows an experimental design with pre- and post-testquestions that include both Likert-style motivation questions and concept inventory-stylecognitive learning questions that have been developed by content experts for each course leveland are scaled using Bloom’s Revised Cognitive Taxonomy. Results from fall 2014 freshmencourses and from both levels in the spring 2015 semester will be analyzed and presented.
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