My Approach to Teaching and Learning in the Classroom

The instructional model I developed and used for designing undergraduate science courses in Stream Ecology and Ichthyology, and a graduate seminar course in Translational Behavioral Ecology.

My approach to course delivery incorporates both proven and innovative practices to maximize learning outcomes for diverse learners. Examples include: (a)using communication theory to create visual and auditory complementarity in course material to account for differences in dominant learning modalities across students and to promote accessibility; (b)designing courses as a sequence of activities that map onto the progression of cognitive abilities observed in humans via application of Bloom’s Taxonomy; (c)using High-Impact Practices (HIPs) including collaborative assignments, collaborative evaluations, and a capstone exercise that models a professional conservation activity; and (d)designing low-stakes high-impact take-home exams that intentionally generate learning outcomes and afford students the opportunity to demonstrate individual creativity and mastery of the subject without the cognitive impediment of time-stress.

My teaching assignment includes instructing an advanced undergraduate course each year (FW420: Stream Ecology), and a course of my choosing (or in response to departmental need) every other year. I also provide several guest lectures each year on topics related to animal behavior, invasion ecology, and the visual design of effective scientific communication tools.

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WaterCube: An Innovative Approach to Graduate Education

Water resources and aquatic ecosystems around the world face increasing challenges and risks from climate change, natural and anthropogenic disasters, harmful algal blooms, and changes in land use.  Recent advances in sensors, robotics, genomics, and computational modeling generate an amount and variety of data related to water at all scales. These data offer a tremendous opportunity for revolutionizing scientific understanding and management of water resources; however, the challenges associated with the volume, heterogeneity, and uncertainty of the data pose a significant barrier for translating science into action. To meet this challenge we designed the WaterCube program to:

• Train Ph.D. students who are: 
  • competent in the knowledge, understanding, and practice of issues at the intersection of data science, water science, and social science;
  • well-versed in cross-disciplinary research collaboration; and
  • well prepared for diverse career options.
• Create a convergent research paradigm that enables breakthroughs in addressing challenging, pressing water problems by merging the expertise and talent from broad backgrounds, and conversely, propels advancement of disciplines in data science, water science, and social science.
• Establish and disseminate a novel, generalizable approach to graduate training in big data-enabled water sustainability and equity.
  

WaterCube is a National Research Traineeship (NRT) program funded by the National Science Foundation. If you are interested in applying to the program, please reach out to Dr. Wagner at any time.