Teaching and Learning via Undergraduate Research: Notes from the Harvard Forestry Data Science Lab

Abstract Number:

3097 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Speed 

Participants:

Grayson White (1), Kelly McConville (2)

Institutions:

(1) N/A, N/A, (2) Harvard University, N/A

Co-Author:

Kelly McConville  
Harvard University

First Author:

Grayson White  
N/A

Presenting Author:

Grayson White  
N/A

Abstract Text:


The Harvard Undergraduate Forestry Data Science Lab (UFDS), in collaboration with the US Forest Service, provides undergraduates the opportunity to learn and apply statistical and data science skills to real-world research projects. The ten-week UFDS summer program provides collaborative research experiences that focus on: working with peers from different backgrounds, project stakeholders, and Forest Service Research Scientists; presenting science to technical and non-technical audiences; developing data science skills such as data visualization, model diagnostics, data wrangling, and code reviews; and reading and writing scientific documents and articles. This talk provides an overview of the training program, lessons learned about providing meaningful and impactful learning experiences to undergraduate students in data science, working withn undergraduates with diverse backgrounds and skills, and building environments in which students can strengthen their identity and confidence as a statistician, data scientist, and human.

Keywords:

undergraduate research|collaboration|sense of belonging|code reviews|small area estimation|survey statistics

Sponsors:

Section on Statistics and Data Science Education

Tracks:

Miscellaneous

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I have read and understand that JSM participants must abide by the Participant Guidelines.

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I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

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