This document will help you review courses for culturally sound design, as well as design courses with better awareness.
This resource includes a selected list of OERs dealing with diversity, equity, and inclusion, including materials on accessibility, culturally responsive teaching, inclusive education, gender diversity, and multiculturalism.
From OpenStax, a review framework and set of prose guidelines for development of diversity and representation in OERs. While the entire conception and approach of a textbook should consider all populations, even a well informed and well-meaning author or editor can misstate or misconceive diversity/representation issues.
For example, even a member of a certain group can use an archaic term to define that group. To focus on the practical, OpenStax has worked with experts to identify specific areas of course materials that reflect inclusivity or a lack thereof. They have evaluated their existing textbooks on these elements, and the community has agreed that the resulting changes have been effective and positive.
This starter kit has been created to provide instructors with an introduction to the use and creation of open educational resources (OER). The text is broken into five sections: Getting Started, Copyright, Finding OER, Teaching with OER, and Creating OER. Although some chapters contain more advanced content, the starter kit is primarily intended for users who are entirely new to Open Education. [Version 1.1. Revised September 5th, 2019.]
This tutorial introduces the reader to some of the amazing capabilities of R to work with and map geographic data. Geographic data are data that contain spatial attributes (or spatial data) that define a geographic space (location, area, elevation, etc.) and non spatial attributes (f.e., population density, pollutant concentrations, temperature).
This tutorial was developed for one the units of the course “ENVS 420: Research Seminar in Environmental Sciences” offered at the University of Baltimore. However, it is hoped that readers outside of ENVS 420 who are interested in geospatial analysis and with a basic familiarity of R find this tutorial useful.
The use of an integrated developer environment (IDE) or an IDE like configuration such as the IDE RStudio (https://rstudio.com/) or the Nvim-R plug-in for the integration of vim/neovim and R (https://github.com/ jalvesaq/Nvim-R/tree/stable) is recommended but not necessary.
The tutorial was written with RMarkdown (v. 2.6) (Allaire et al., 2020; Xie et al., 2018, 2020) in R (v. 4.2.3) (R Core Team, 2020).