Teaching Accessibly and Teaching Accessibility in Data-Intensive Courses

Talk at AAAS-IUSE Workshop

Mine Dogucu
University of California Irvine

2024-04-18

Some statistics from tech world

  • Only 4.8 % of technical roles are held by Hispanic employees, 2.4 % by Black employees and 25.8 % by women at Meta (2022)

  • Of Google’s technical roles in the US, 1.2 % are held by Black women, 1.3 % by Latina women, and 0.2 % by Native American women (2023)

  • Only 6.5% of Google’s global employees(technical and nontechnical) report having a disability, whereas World Health Organization estimates that 16% of the world’s population experience significant disability (2023).

Some Problems with Tech Tools

  • Statistical translation tools (e.g., Google Translate) yield male pronoun defaults more frequently (Prates et al., 2019).
  • Facial recognition algorithms are much less accurate in identifying women than men, and darker-skinned people than lighter-skinned people(Raji and Buolamwini, 2019).
  • Autonomous vehicles fail to recognize behaviors of people with disabilities (Disability Rights UK, 2021).

We must design accessible and inclusive data-intensive courses to prepare a future data workforce that is diverse.

Teaching Accessibly

Goal:

Write a Book on Bayesian Statistics that is Accessible and Inclusive

a hex shaped logo with shiny green-pink disco ball and purple starry background. There is text that says Bayes Rules!

Dogucu, M., Johnson, A. A., & Ott, M. (2023). Framework for Accessible and Inclusive Teaching Materials for Statistics and Data Science Courses. Journal of Statistics and Data Science Education. 31(2), 144-150.

Open-Access

  • Cost of books and supplies for a student at a four-year university in 2021 was estimated to be $1240 per year (Hanson, 2021).

  • About 11% of the students indicated that they skipped meals in order to afford books and course materials (Hanson, 2021).

  • The bayesrulesbook.com page has been accessed from more than 150 countries.

Assistive Technology

Assistive Technology is any form of technology (software, device) that helps people with disabilities perform certain activities.

Examples:

  • walking sticks
  • wheel chairs
  • screen readers

Screen reader

A screen reader is an assistive technology that supports blind or visually impaired people in using their computer.

The video shows use of a screen reader briefly.

Alternate Text

  • “Alt text” describes contents of an image.
  • It is used in HTML pages.
  • Screen-readers cannot read images but can read alt text.
  • Alt text has to be provided.

GitHub issue created on RStudio's RMarkdown repo asking for fig.alt option to be created

Making math accessible

  • Should calculus be a prerequisite?
  • Checking intuition with active learning quizzes.
  • Supporting mathematical concepts with computing.

Making learning fun

How can we live if we don’t change? —Beyoncé. Lyric from “Satellites.”

vs.

What is probability?

Embracing mistakes as part of learning

As you read the book and put Bayesian methodology into practice, you will make mistakes. Many mistakes. Making and learning from mistakes is simply part of learning. We hope that you persist through the struggle of learning so that you can contribute your unique insights, perspectives, and experiences to the Bayesian community.

v.s.

The proof is obvious.

Making learning relevant with diverse set of applications

  • Weather
  • LGBTQ+ anti-discrimination laws
  • Spotify data
  • Hotel bookings
  • Penguins

Teaching Accessibility

A timeline titled brief history of knitr. That points out that the initial commit was in October 2011, first download from CRAN was in October 2012, alt-text feature was requested in July 2020, feature was made available in January 2021

Between first CRAN download and alt-text feature request, there were 22,622,426 CRAN downloads of knitr.

Developers Create Tools with no Accessibility Support

Data Scientists Create Inacessible Products

Curriculum Does Not Teach Accessibility

Developers Create Tools with no Accessibility Support

Data Scientists Create Inacessible Products



Teach Access logo that is an illustration of a bridge

Supported by the Teach Access network.


NSF logo

Supported by NSF HDR DSC award #2123366

A headshot of a man with short, straight, dark hair. He is wearing a white button up shirt and black rectangular glasses.

JooYoung Seo
University of Illinois Urbana-Champaign

jooyoungseo.github.io/
jooyoungseo
seo_jooyoung

introdata.science logo with a human figure juggling charts, a computer, a database and a book

Curriculum Goal

As educators, we have to ensure that the current and the next generation of data scientists, provide public-facing outputs (websites, analysis reports, etc.) that are accessible.

Learning Objectives

  • Students should get familiar with Americans with Disabilities Act and/or United Nations Convention on the Rights of Persons with Disabilities.
  • Students should use at least one assistive technology (i.e. screen reader).
  • Students should consider different representations of data.

Data Visualization - Colors

Three separate scatterplots in three rows showing bill depth and bill length of three separate species of penguins Adelie, Chinstrap, and Gentoo respectively and the  points representing each observation are red, green, and blue respectively.

Color Blindness Simulator

A 2 by 2 grid of four scatterplots. The scatterplots are the same as the scatterplot in the previous figure except for colors. From left to right and top to bottom the plots read deutanomly, protanomly, tritanomly, and desaturated

Okabe-Ito Color Palette

Three separate scatterplots in three rows showing bill depth and bill length of three separate species of penguins Adelie, Chinstrap, and Gentoo respectively and the  points representing each observation are orange, blue, and green respectively.

Resources

Color Blindness Simulator You can upload any image and in return get an image with colors that would be visible to color-blind people with specific color vision deficiency.

Okabe-Ito 2008 Color Universal Design. Color palette that is color-blind friendly.

Okabe-Ito color-palette Color codes for Okabe-Ito palette.

Data Verbalization

We can verbalize data via alternate text.

The scatterplot shows speed ranging from about 0 to 25 mph on the x-axis and dist ranging from 0 to 120 ft on the y-axis. There is a moderate positive linear relationship.

The speed of cars (mph) and the distances (ft) taken to stop

```{r}
#| fig-cap: "The speed of cars (mph) and the distances (ft) taken to stop"
#| fig-alt: "The scatterplot shows speed ranging from about 0 to 25 mph on the x-axis and dist ranging from 0 to 120 ft on the y-axis. There is a moderate positive linear relationship."
plot(cars)
```
The scatterplot shows speed ranging from about 0 to 25 mph on the x-axis and dist ranging from 0 to 120 ft on the y-axis. There is a moderate positive linear relationship.

The speed of cars (mph) and the distances (ft) taken to stop

Best Practices for Alternate Text in Data Science Context

Alternate Texts are Under Utilized in the Data Science Community

“Over the 3 years of TidyTuesday, there were 7,136 data viz tweets and only 215 (3%) of them had alt-text”

Canelón & Hare, 2021

Data Sonification

Data sonification is the presentation of data as sound.

Data Tactualization

Data tactulization refers to making data visualization in a form so that it can be touchable. The video shows printing of a tactile boxplot.

Data Tactualization

library(tactileR)
brl_begin(file = 'tactile.pdf', 
          pt = 11, 
          paper = 'special', font='BRL')
hist(airquality$Ozone)
brl_end()

A histogram with x and y labels, title displayed in Braille.

Different representations of data is one way of introducing accessibility to students but it is not meant to be a complete introduction to accessibility.

Seo, J. & Dogucu, M. (2023) Teaching Visual Accessibility in Introductory Data Science Classes with Multi-Modal Data Representations Journal of Data Science. 21(2), 428-441.

Accessibility is for everyone.

THANK YOU

minedogucu.com
mdogucu
MineDogucu
mastodon.social/@MineDogucu
minedogucu.bsky.social
minedogucu

References

Prates, M. O., Avelar, P. H., and Lamb, L. C. (2019), “Assessing Gender Biasin Machine Translation: A Case Study with Google Translate,” NeuralComputing and Applications, 32, 6363–6381.

Raji, I. D., and Buolamwini, J. (2019), “Actionable Auditing: Investigatingthe Impact of Publicly Naming Biased Performance Results of Commer-cial AI Products,” in Proceedings of the 2019 AAAI/ACM Conference onAI, Ethics, and Society, pp. 429–435.

Disability Rights UK. (2021), “Self-Driving Cars Pose Threat for DisabledPeople,” Available at https://www.disabilityrightsuk.org/news/2021/april/self-driving-cars-pose-threat-disabled-people.

Meta Diversity Report (2022) “Embracing Change Through Inclusion: Meta’s 2022 Diversity Report” Available at https://about.fb.com/wp-content/uploads/2022/07/Meta_Embracing-Change-Through-Inclusion_2022-Diversity-Report.pdf.

Google Diversity Annual Report (2023) Available at https://static.googleusercontent.com/media/about.google/en//belonging/diversity-annual-report/2023/static/pdfs/google_2023_diversity_annual_report.pdf?cachebust=2943cac.

World Health Organization (2023). “Disability” Available at https://www.who.int/news-room/fact-sheets/detail/disability-and-health.