Suggestions and comments on JOSE draft #40
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scottyhq
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Jan 28, 2025
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| Machine learning (ML) has rapidly emerged as a transformative tool in the analysis of big data and scientific discovery across disciplines, especially since 2010. Geosciences, with its inherently large, complex, and multidimensional datasets, is particularly poised to benefit from ML's capabilities [@karpatne2018machine, @bergen2019, @dramsch202070,@sun2022review,@mousavi2022deep]. Yet, despite the explosion of ML applications in geoscientific research, there is no established curriculum in higher education that focuses on equipping students with practical ML skills tailored to the unique needs of geosciences. Most textbooks are dedicated to statistical learning [@petrelli2021introduction,wang2023data], and courses dedicated to data sciences (e.g., Colorado University- Boulder Earth Data Science Program or University of California - Santa Barbara Master's in Environmental Data Science). |
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The CU boulder course could probably get its own paragraph. How is it different from ESS 469?
mdenolle
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Jan 28, 2025
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Addressed in #41 |
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Thanks for putting this together @mdenolle ! I provided some suggestions (see commit messages), and main comments are here:
Introduction is a bit repetitive, paragraphs could be combined
Include a figure or two? Maybe from student projects?
“Homework” section mentions “Chapter 3”, consider laying out the full chapter structure somewhere earlier?
Final project is “group-based” How many students per group? randomly assigned?
I suggest moving “Technology Integration” before Final Project? Feels like an awkward transition currently. Also “Content Delivery” could come earlier?
Interested to hear more about how Co-pilot is used by students! (ok to use on homework assignments?)
last paragraph of conclusion could be more specific about desirable future improvements