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The Role Of Machine Learning And Network Analyses In Understanding Microbial Composition In An Experimental Prairie, Ali Eastman Oku
The Role Of Machine Learning And Network Analyses In Understanding Microbial Composition In An Experimental Prairie, Ali Eastman Oku
Graduate Research Theses & Dissertations
Machine learning and network analyses are powerful modern tools can process and map out connections between large amount of ecological data from complex environmental communities. Random forests, an ensemble machine learning algorithm, are particularly powerful as they can capture complex patterns in data while remaining easily interpretable. These tools are specifically useful in experimental settings where different types of data are collected. The aim of this study was to demonstrate the utility of machine learning models and network analyses at analyzing diverse ecological data from dynamic plant-soil microbial communities in a prairie ecosystem. Our experimental system is an experimental prairie …
Cultivating A Stem Investigation: Reading And Task Expectations For Introductory Biology Courses, Tina M. Ballard
Cultivating A Stem Investigation: Reading And Task Expectations For Introductory Biology Courses, Tina M. Ballard
Graduate Research Theses & Dissertations
College completion is an important discussion in today’s world with only about 30% of community college students completing their degrees within three years of starting their programs. Especially in the Science, Technology, Engineering, and Math (STEM) fields, students are changing their majors or not completing their degrees for a variety of reasons. Previous research has established that there are high attrition and failure rates for introductory biology courses which may be causing some students to change their majors or not complete their degrees. This multicase study investigated the reading and task demands for introductory biology courses designed for STEM majors …