Dataset Information

Teaching Microbiome Analysis: From Design to Computation Through Inquiry.

ABSTRACT: In this article, we present our three-class course sequence to educate students about microbiome analysis and metagenomics through experiential learning by taking them from inquiry to analysis of the microbiome: Molecular Ecology Lab, Bioinformatics, and Computational Microbiome Analysis. Students developed hypotheses, designed lab experiments, sequenced the DNA from microbiomes, learned basic python/R scripting, became proficient in at least one microbiome analysis software, and were able to analyze data generated from the microbiome experiments. While over 150 students (graduate and undergraduate) were impacted by the development of the series of courses, our assessment was only on undergraduate learning, where 45 students enrolled in at least one of the three courses and 4 students took all three. Students gained skills in bioinformatics through the courses, and several positive comments were received through surveys and private correspondence. Through a summative assessment, general trends show that students became more proficient in comparative genomic techniques and had positive attitudes toward their abilities to bridge biology and bioinformatics. While most students took individual or 2 of the courses, we show that pre- and post-surveys of these individual classes still showed progress toward learning objectives. It is expected that students trained will enter the workforce with skills needed to innovate in the biotechnology, health, and environmental industries. Students are trained to maximize impact and tackle real world problems in biology and medicine with their learned knowledge of data science and machine learning. The course materials for the new microbiome analysis course are available on Github: https://github.com/EESI/Comp_Metagenomics_resources.

SUBMITTER: Rosen GL

PROVIDER: S-EPMC7658192 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Teaching Microbiome Analysis: From Design to Computation Through Inquiry.

Rosen Gail L GL Hammrich Penny P

Frontiers in microbiology 20201029

In this article, we present our three-class course sequence to educate students about microbiome analysis and metagenomics through experiential learning by taking them from inquiry to analysis of the microbiome: Molecular Ecology Lab, Bioinformatics, and Computational Microbiome Analysis. Students developed hypotheses, designed lab experiments, sequenced the DNA from microbiomes, learned basic python/R scripting, became proficient in at least one microbiome analysis software, and were able to an ...[more]

PMID: 33193120

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Project description:The gut microbiome and its physiological impacts on human and animal health is an area of research emphasis. Microbes themselves are invisible and may therefore be abstract and challenging to understand. It is therefore important to infuse this topic into undergraduate curricula, including Anatomy and Physiology courses, ideally through an active learning approach. To accomplish this, we developed a novel tactile teaching tool with guided-inquiry (TTT-GI) activity where students explored how the gut microbiome ferments carbohydrates to produce short chain fatty acids (SCFAs). This activity was implemented in two sections of a large-enrollment Human Anatomy and Physiology course at a research intensive (R1) university in the Spring of 2022 that was taught using a hyflex format. Students who attended class in person used commonly available building toys to assemble representative carbohydrates of varying structural complexity, whereas students who attended class virtually made these carbohydrate structures using a digital learning tool. Students then predicted how microbes within the gut would ferment different carbohydrates into SCFAs, as well as the physiological implications of the SCFAs. We assessed this activity to address three research questions, with 182 students comprising our sample. First, we evaluated if the activity learning objectives were achieved through implementation of a pre-and post-assessment schema. Our results revealed that all three learning objectives of this activity were attained. Next, we evaluated if the format in which this TTT-GI activity was implemented impacted student learning. While we found minimal and nonsignificant differences in student learning between those who attended in-person and those who attended remotely, we did find significant differences between the two course sections, which differed in length and spacing of the activity. Finally, we evaluated if this TTT-GI approach was impactful for diverse students. We observed modest and nonsignificant positive learning gains for some populations of students traditionally underrepresented in STEM (first-generation students and students with one or more disabilities). That said, we found that the greatest learning gains associated with this TTT-GI activity were observed in students who had taken previous upper-level biology coursework.

Dataset Information

Teaching Microbiome Analysis: From Design to Computation Through Inquiry.

Publications

Teaching Microbiome Analysis: From Design to Computation Through Inquiry.

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