Abstract

Authentic learning experiences are a valuable way for students to gain an in-depth understanding of the scientific process. However, implementing such experiences in large enrollment courses can be challenging. Here, we present a community ecology lab module that uses data from a long-term camera trap study to allow students to design and conduct their own scientific inquiries. "Snapshot Serengeti" is a 10+ year wildlife monitoring survey in Serengeti National Park, Tanzania. Over 200 camera traps continuously collect fine-scale spatial and temporal data on the dynamics of ~50 animal species. The charismatic subject matter (large African animals) engages students, encouraging excitement about the topic, while the ample amount of processed data enables students to conduct real ecological research. In this lab, students collaborate in all stages of the research process. We present two lab variations: a four-week in-person and five-week remote-learning online option. From this module, students learn to generate testable research questions, produce and interpret graphs, participate in peer review, and communicate their results in both oral and written format. While originally developed for a 1000-level introduction biology course for non-majors, this material could easily be adapted to provide authentic hypothesis testing and data analysis experience to biology majors. In addition to a greater awareness of community ecology principles, students will come away from this lab with a better understanding of how exploratory research fits into the scientific process and confidence in their own ability to engage in the process of science. <em>Primary image: </em>Captured by camera trap - a wildebeest and zebra grazing in the Serengeti: Using camera trap images such as this from the long-term camera trapping program “Snapshot Serengeti”, students will analyze real data on Serengeti ecosystem dynamics and generate their own questions to explore African animal behavior and ecology. This image is available under a Creative Commons 4.0 International License.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.