Dogucu, M;
Johnson, AA;
Ott, M;
(2023)
Framework for Accessible and Inclusive Teaching Materials for Statistics and Data Science Courses.
Journal of Statistics and Data Science Education
10.1080/26939169.2023.2165988.
(In press).
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Abstract
Despite rapid growth in the data science workforce, people of color, women, those with disabilities, and others remain underrepresented in, underserved by, and sometimes excluded from the field. This pattern prevents equal opportunities for individuals, while also creating products and policies that perpetuate inequality. Thus, it is critical that, as statistics and data science educators of the next generation, we center accessibility and inclusion throughout our curriculum, classroom environment, modes of assessment, course materials, and more. Though some common strategies apply across these areas, this article focuses on providing a framework for developing accessible and inclusive course materials (e.g., in-class activities, course manuals, lecture slides, etc.), with examples drawn from our experience co-writing a statistics textbook. In turn, this framework establishes a structure for holding ourselves accountable to these principles.
| Type: | Article |
|---|---|
| Title: | Framework for Accessible and Inclusive Teaching Materials for Statistics and Data Science Courses |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/26939169.2023.2165988 |
| Publisher version: | https://doi.org/10.1080/26939169.2023.2165988 |
| Language: | English |
| Additional information: | © 2023 The Author(s). Published with license by Taylor and Francis Group, LLC. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The moral rights of the named author(s) have been asserted. |
| Keywords: | Accessibility; Curriculum; Inclusion; Textbooks |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10166161 |
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