Teaching Module
Remote sensing data processing – NEON airborne data
I developed this teaching module in NEON Faculty Mentoring Network in 2020 spring. Concepts of remote sensing and data logistics, and NEON remote sensing data are introduced. Students learn how to apply spatial data processing and visualization skills using R coding program to process NEON airborne data to address scientific questions.
Field trip
Plant Phenology Observation:
Where: Chicago Botanic Garden
When: May 5, 2019
What:
o Learn and practice on plant phenology observation
o Report observation records
o Write reflection on what is learned
Activities:
Plant identifications;
Animal searching and collections of invertebrate animal samples;
Animal identifications in the lab.
Lab practical exam
Here are a few of my designed questions for the laboratory practical exam (Principles of Biology in 2016 spring). These questions combined multiple types of materials learning in the lab, such as plant samples, insect specimens, animal dissection, microscope slides. The exam tested not only the concepts, but also the application of knowledge in a real problem and students’ hand-on work.
Reflection: Students’ performance in this exam clearly reflect their learning outcomes in the laboratory sections, such as applying learned concepts and skills in experiental design, specimen identifications, results interpretation, and other hands-on work procedures. In the future, I will improve my questions and settings by providing more directions and information in the question part to clarify what the students need to answer. For example, I can make cleaer demonstrations for different types of labels (letters or numbers) on the stations. It would be better if more dissecting specimen were available for students to do more hands-on work during the exam.
