As part of my coursework for EDAT 524: Universal Design for Learning at George Mason University, I curated a resource notebook for using technology to incorporate Universal Design for learning (UDL) for introductory computational and data sciences coursework at the high school and/or college level, informed by my background in computational and data sciences and assistive technology. Here is an edited version to support the implementation of UDL for data science lessons for students with disabilities, including but not limited to visually impaired students. Note that inclusion of an application on this list is not an endorsement or guarantee that it will be suitable for a particular classroom environment and availability of applications/accessibility features are subject to change.
Note: CAST UDL 2.2 Guidelines are noted throughout this document. The most recent CAST UDL Guidelines can be found at CAST Universal Design for Learning Guidelines
Textbooks and Required Reading
Immersive Reader
Microsoft Immersive Reader provides a simplified reading display, applying a consistent font size, font style, and background color to digital text. This makes it easier to read content without having to zoom in on a page, edit content, or enabling other accessibility settings, and comes built into several Microsoft applications, including the Edge web browser, Outlook, Word, and several third-party educational technology applications (e.g. Wakelet).
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information by providing options for adjusting font size, line spacing, background colors, font style, and other visual elements
- 1.3: Offer alternatives for visual information via text-to-speech and read aloud tools
- 3.3: Guide information processing and visualization by removing distractions on a page and providing options for sequentially releasing information a few lines at a time
Potential uses
Immersive Reader and other simplified reading displays are valuable for learners with print disabilities such as low vision, dyslexia, and other conditions that make traditional text difficult or impossible to read. Students can use Immersive Reader for reading web content or documents with their preferred visual settings or have text read out loud, which is useful for class readings or checking emails. Instructors can also use Immersive Reader when presenting information on the board to reduce visual distractions and increase the font size for improved readability without having to use display scaling or zoom.
Related links
- Immersive Reader
- How I Use Microsoft Immersive Reader With Low Vision
- Wakelet Accessibility Features For Low Vision
Digital textbooks (eTextbooks)
Digital textbooks (eTextbooks) can be used in lieu of or in addition to physical textbooks and can provide an enhanced reading experience with features such as full-text search, hyperlinks to additional resources or readings, options for highlighting and annotating text, or interactive code snippets that can be copied into another application.
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information with options for changing font style, font size, line spacing, page/text color, and other visual settings for multiple types of content.
- 1.3: Offer alternatives for visual information with options for using read aloud or text-to-speech. Titles can also be accessed with smart speakers in addition to the app. This can be especially useful for reading textbooks that support text-to-speech.
- 2.1: Clarify vocabulary and symbols with the built-in dictionary tool for looking up words or phrases, with options for searching for additional definitions or explanations in a web browser pop up window.
- 2.3: Support decoding of text by offering audio-supported reading options for listening to and reading text at the same time.
- 4.2: Optimize access to tools and assistive technologies by offering full keyboard support and integration with screen readers such as VoiceOver and JAWS.
Potential uses
Digital textbooks can serve as an alternative to physical copies of textbooks for students that have print disabilities and provide additional reading supports such as text-to-speech for interacting with content, as well as options for implementing customized reading settings across multiple titles. In addition, sideloading features (e.g. Send to Kindle) can be used to import and display the content with the user’s pre-defined display settings, which can be helpful for required readings or other text-based content.
Related links
- Ten Questions To Ask When Buying Digital Textbooks
- How To Request Accessible Textbooks In College
- Mainstream eReader Apps and Low Vision Accessibility
- How I Listen To Textbooks With Low Vision
Cheat Sheets for Programming Languages
Programming language cheat sheets provide a list of common features and tasks for different languages and instructions on how to implement them. Professors and professionals alike encourage the use of cheat sheets for streamlining the coding process and making it easier to read and write code.
UDL checkpoints addressed
- 2.1: Clarify vocabulary and symbols through embedded supports for vocabulary and language, such as hyperlinks, definitions of common terms, and illustrations.
- 2.2: Clarify syntax and structure of programming languages that highlight structural relationships and links between different properties of a code snippet.
- 3.1: Activate or supply background knowledge by providing a list of key terms and definitions that can be used in multiple contexts.
- 3.4: Maximize transfer and generalization for concepts that can be used with multiple projects
- 5.2: Use multiple tools for construction and composition by providing code snippets and templates for creating content.
- 5.3: Build fluencies with graduated levels of support by providing different ways to solve problems or display information
Potential uses
Cheat sheets are a helpful way to support beginners when learning a new programming language as well as providing a guide for all learners on how to display information or complete specific tasks using a given language or application. Many professors also allow for cheat sheets to be used during open-book exams, similar to formula sheets for a math test— this can help with reducing anxiety in these contexts as students are able to interact with the cheat sheet prior to taking the exam.
Related links
- Tips For Teaching R Programming To A Low Vision Student
- Free Accessible Coding Resources With Large Print Options
- How To Create An Accessible Formula Sheet
PDF to HTML and HTML articles
Although PDFs can be made accessible for users with visual impairments through the use of semantic structure, fixed layout formats like PDFs are typically considered less accessible (or entirely inaccessible) file formats for low vision and print disabilities. However, PDFs can be converted to responsive layout file formats using tools such as Paper to HTML, or by searching for HTML copies of articles within library databases or online repositories (e.g. arXiv)
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information by customizing the layout or other visual elements of PDF content.
- 4.2: Optimize access to tools and assistive technologies so that documents can be navigated with a keyboard or read out loud with a screen reader.
Potential uses
When completing required readings or background research for a project, students can use tools like Paper to HTML or HTML articles to provide a single-column reading experience that offers improved compatibility for assistive technologies, browser zoom, and other display features. Instructors can also display in-class readings on the projector using this tool to provide an improved visual experience that makes it easier for students to read information presented at a distance.
Related links
- Paper to HTML | Allen Institute for AI
- HTML papers on arXiv: why it’s important, and how we made it happen
- Using YuJa Panorama and Anthology Ally With Low Vision
- How I Find Research Sources In Accessible Formats
- File Formats For Low Vision and Print Disabilities
Introduction to Data Science
CODAP and Dynamic Data Science
The Common Online Data Analysis Platform (CODAP) is a free open-source software for data analysis that provides several structured activities and sample datasets through the built-in Dynamic Data Science platform, with options for uploading datasets from a CSV or TXT format and conducting exploratory data analysis. CODAP requires no downloads and can be accessed within the web browser on a computer, tablet, or phone.
UDL checkpoints addressed
- 3.1: Activate or supply background knowledge by making explicit cross-curricular connections from information shared in dataset
- 3.3: Guide information processing and visualization by providing interactive models for exploring data and providing multiple options for organizing data
- 4.1: Vary the methods for response and navigation by including options for using computer and mouse, keyboard shortcuts, touchscreen, etc.
- 7.1: Optimize individual choice and autonomy through multiple options for customizing the appearance and layouts of visualizations
- 7.2: Optimize relevance, value, and authenticity by providing datasets related to “real-world” topics and providing users with the option to choose or locate their own datasets for analysis that is relevant to their own interests.
Potential uses
When first learning about exploratory data analysis (summarize, visualize, and interpret data), students may benefit from a low-code approach that focuses on teaching students the background knowledge they will need to successfully use more advanced software and programming languages in the future.
Related links
- Dynamic Data Science | learn.concord.org
- Five Apps I Use In Statistics Classes As A Low Vision Student
What’s Going On in This Graph?
What’s Going on in This Graph is a collaboration between the American Statistical Association (ASA) and The New York Times that teaches students how to read, interpret, and analyze graphs, and provides opportunities for student discussion moderated by ASA member teachers. The weekly column encourages students to think critically about how information is presented, what they want to know about it, and how this information may have an impact on their community.
UDL checkpoints addressed
- 2.2: Clarify syntax and structure through the use of Stat Nuggets, which clarify the underlying structure of the graph shared and other vocabulary.
- 2.5: Illustrate through multiple media by providing a free link to a New York Times article that features the weekly graph, with prompts to make connections between the text and accompanying visuals
- 7.1: Optimize individual choice and autonomy through providing options for participation. Students may prefer to write down answers and share with teacher, participate in a small-group or whole-class discussion, or participate in the larger moderated discussion online
- 7.2: Optimize relevance, value, and authenticity by providing visualizations and data related to “real-world” topics that affect students and their communities
- 8.3: Foster collaboration and community by sharing an opportunity to connect with other learners from around the world during the weekly moderated discussions
Potential uses
When learning about how to create and interpret data visualizations, learners benefit from viewing well-constructed examples and prompts for organizing their questions and thoughts about a given graph. In addition, this can serve as an introduction to data journalism and provide specific examples via accompanying news articles for how data analysis is used across various contexts. Students who are more hesitant to participate verbally in group settings may prefer the asynchronous approach to writing or typing comments to participate in a discussion as well.
Related links
- What’s Going On in This Graph? – The New York Times
- Purposes of Media Descriptions for Visual Impairment
Hour of Code (Hour of AI)
Hour of Code is an initiative that encourages people of all ages to learn about computer science and artificial intelligence through free activities. Hour of Code offers over 700 activities tailored to learners of all ages, with options for browser-based games, “unplugged” activities that don’t require a computer, and toolkits for incorporating content across a variety of subject areas.
Note: Hour of Code has since been rebranded as Hour of AI
UDL checkpoints addressed
- 1.2: Offer alternatives for auditory information through the use of captions for video content and activities that contain audio tracks
- 3.1: Activate or supply background knowledge by offering activities that make explicit cross-curricular connections, such as building an animal classifier for a biology activity
- 4.2: Optimize access to tools and assistive technologies by selecting activities that indicate support for keyboard access, screen reader, etc
- 7.1: Optimize individual choice and autonomy through providing options for students to select their own activity, with options for applying search filters to display a list of relevant and appropriate activities they can choose from.
- 7.2: Optimize relevance, value, and authenticity by providing visualizations and data related to “real-world” topics that affect students and their communities
- 7.3: Minimize threats and distractions by allowing students to work at their own pace and vary levels of sensory stimulation (such as turning background music on/off)
- 8.2: Vary demands and resources to optimize challenges by varying the degree of complexity for activities, with options for choosing activities for beginner or comfortable learners.
Potential uses
Hour of Code activities offer an interactive visual experience for introducing students to new programming languages and concepts, which are especially useful as an introduction to languages that will be used in future data science coursework like Python. Hour of Code activities can be implemented in the classroom or as an at-home activity, with options for incorporating assistive technology, choice of device, and time spent on the activity. Students can also return to an activity at a later time or participate in extension activities to learn more about a topic that interests them and use the assistive technologies or accessibility settings that they already use for other subjects.
Related links
General Programming and Coding
The Quorum Programming Language
Quorum is described as the world’s first evidence-oriented programming language that was created with accessibility in mind, providing an intuitive yet powerful interface for data science education that is deliberately designed with assistive technology users and people with disabilities in mind. Quorum may be accessed in a web browser application, but works best in the free Quorum Studio program available for download on the website. Quorum is written and performs very similar to the R programming language, except Quorum has additional accessibility features specifically for nonvisual and low visual access.
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information by customizing visual settings for font size, spacing, style, color, visual layout, and display modes (e.g. dark mode)
- 1.3: Provide alternatives for visual information through the use of audio cues, earcons, and options for data sonification that can be used to construct and evaluate visualizations
- 2.2: Clarifies syntax and structure by using colored labels and nested spacing to highlight relationships between elements, which can improve readability and help with the debugging process
- 4.2: Optimize access to tools and assistive technologies by providing full support for keyboard access and hotkeys, as well as support for screen reader users. Alternatively, users may access Quorum using an alternative keyboard or pointing device.
- 5.2: Use multiple tools for construction and composition by enabling features such as spell check, text-to-speech, example code blocks, and automatic formatting to minimize runtime errors
- 7.2: Optimize relevance, value, and authenticity by empowering learners to create their own programs and explore datasets of interest, as well as create accessible visualizations that can be explored with a screen reader, sonification, and custom color schemes. Quorum can also be used as a bridge to learning more powerful languages such as R in future modules or classes.
Potential uses
Quorum provides all learners with the tools to explore datasets and create their own visualizations, and is especially useful for users with visual impairments or other print disabilities who often face barriers when using other IDEs with assistive technology. With Quorum, students can focus on learning valuable skills related to data science and analysis, and not on trying to get software to work with a screen reader.
Related links
Jupyter Notebook
Used by students and professionals alike, Jupyter Notebook is a web-based interactive computing platform that allows users to create and share documents that contain live code, equations, visualizations, narrative text, and more. It is frequently used for data analysis and can organize anything from class notes to homework to projects. Jupyter is free to access, and many students access it as part of the Anaconda Distribution package for learning Python and R.
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information through options for adjusting font size, display scaling, and additional display settings such as dark mode.
- 1.3: Offer alternatives for visual information by using the browser application with text-to-speech for reading sections of documents out loud.
- 3.3: Guide information processing and visualization by breaking down assignments or problems into smaller chunks and notebook sections, and embedding interactive models for teaching different concepts
- 3.4: Maximize transfer and generalization through the use of structured notetaking and assignments created with the Jupyter program.
- 5.3: Build fluencies with graduated levels of support for practice and performance by offering starter code templates and providing assignments and class notes in a Jupyter Notebook format so that students can interact with code at their own pace and on their own computers
- 7.3: Minimize threats and distractions by using the Jupyter application with multiple programming languages, which can reduce the need for students to learn new languages and programs simultaneously. While additional languages will require the installation of kernels, Jupyter can be used with other languages used in data science such as Matlab, R, SQL, Julia, and more.
- 9.3: Develop self-assessment and reflection by encouraging students to write narrative text and answer questions about their live code, as well as document how their code works (or doesn’t work as expected).
Potential uses
Jupyter Notebook templates can be used to break down assignments or notes into smaller chunks and help students understand how and why a given block works the way it does, as well as provide opportunities for organizing documentation, questions, and code blocks into one document. While Jupyter Notebook is still expanding its support for screen reader users, Jupyter supports browser zoom and supporting large print and text-to-speech, and offers a more interactive experience than copying code snippets from a textbook or assignment into another program; everything runs in one place.
Related links
Google Colab
Colab is a browser-based IDE that allows users to write code and create programs directly from their browser, without any additional downloads or configurations required. Colab can be used on any operating system or internet connected device and allows users to save programs to their Google account, as well as connect to GitHub and similar platforms. There are several different programming languages supported, including popular languages for data science courses like Python, R, Markdown, LaTex, and Fortran.
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information through options for adjusting font size, display scaling, and additional display settings such as dark mode.
- 1.3: Offer alternatives for visual information by supporting web browser extensions for read aloud or text-to-speech, which can be used to proofread code
- 4.2: Optimize access to tools and assistive technologies by supporting keyboard shortcuts, use of alternative keyboards, and screen reader access, with posted workarounds for known screen reader compatibility issues
- 7.3: Minimize threats and distractions by synchronizing display settings across documents/files and having new files automatically configured so students can start writing code immediately. Since settings are synchronized to user accounts, they can be enabled on any device that the student is using
- 8.3: Foster collaboration and community by sharing Colab workspaces with other peers and mentors, who can contribute to code and provide feedback on group projects. Each student can view the Colab workspace in real time, on their own device, and with their own custom visual settings configured
Potential uses
Colab can be used on any internet connected device with a free account that can save files and customized display settings. Instead of downloading an IDE and installing software on multiple computers, students can store their code in a public or private repository and access it from their computer, tablet, or smartphone, providing options for flexible use
Related links
AI-powered tutoring
AI-powered programming tutoring websites such as Python Tutor offer an online compiler designed to help students learn to write and debug Python, Java, C, C++, and JavaScript. These types of tools provide a visual debugger that is powered by AI and helps students debug their code and correct errors, as well as provide a step-by-step guide for understanding how different code blocks work within a given environment.
UDL checkpoints addressed
- 2.2: Clarify syntax and structure by highlighting different elements of a code block line-by-line, and highlighting the relationship between different elements and lines within the program
- 2.5: Illustrate through multiple media by pairing written code with visualizations of output in the form of tables, graphs, etc.
- 3.3: Guide information processing and visualization by breaking code sections down line-by-line, progressively releasing information and chunking it into smaller elements so students can focus on a single line
- 9.3: Develop self-assessment and reflection by providing feedback on code and suggestions on how to correct, improve, or optimize student-written code to create more effective solutions.
Potential uses
Many compilers and IDEs do not provide specific feedback when it comes to error messages or helping users understand why their code isn’t working, which can lead to frustration. Websites like Python Tutor provides enhanced feedback and options for creating permanent links to code snippets, which can be used to support students when reading or working with teacher starter code or examples in the classroom.
Related links
Data Visualization
Tuva Tools
Tuva Tools is a suite of free web-based applications for exploratory data analysis, data visualizations, and exploring/interpreting data uploaded from a user-provided dataset or from their data library. Tuva can be used for introductory data science and statistics classes, empowering users to create their own graphs and charts with a drag and drop interface.
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information within the application UI and visualizations, including data color, contrast, and font sizes
- 1.3: Offer alternatives for visual information through the use of web accessibility features for screen reader users, options for keyboard access, and data sonification
- 2.4: Promote understanding across languages by supporting 10 different (spoken/written, not programming) languages in the Data Exploration Tools interface, providing options for translation tools and making key information available
- 3.2: Highlight patterns, critical features, big ideas, and relationships by using visual emphasis and drawing attention to critical or interesting features by pairing text labels with visualizations
- 4.2: Optimize access to tools and assistive technologies by providing options for screen reader and keyboard access, with options for printing or accessing a list of keyboard shortcuts within the application
- 7.1: Optimize individual choice and autonomy with multiple options for student-directed activities and independent learning, as well as options for students to experiment with different types of visualizations
- 7.2: Optimize relevance, value, and authenticity by selecting real-world datasets that apply to the lives of students and their communities, increasing engagement with information shared
- 7.3: Minimize threats and distractions by providing users with the option to customize visuals and animations, which is especially important for students with motion sensitivity or that experience vertigo. Disabling animation can also be beneficial for recording screenshares or videos, which may show visuals on a delay.
Potential uses
For activities that focus on statistics and data analysis over writing in a specific programming language, Tuva provides a simple interface that can be used to assist students with exploring datasets, quickly visualizing data, and creating class assignments that can be submitted for teacher feedback and grading directly from the application. This is helpful for students who are looking for a simple interface to explore data while also using meaningful datasets that can help them understand the world around them.
Related links
R Graph Gallery
The R Graph Gallery showcases a collection of charts created with the R Programming language and several different libraries that are frequently used by professional and novice users alike, including ggplot2 and the tidyverse. Users can browse different types of charts and view reproducible code to incorporate the same templates into their own projects.
UDL checkpoints addressed
- 2.2: Clarify syntax and structure by providing definitions of key terms and underlying structures that are used to create different types of charts with the R language.
- 3.2: Highlight patterns, critical features, big ideas, and relationships by using visual emphasis and drawing attention to critical or interesting features that change the appearance of visualizations, such as indicating where to insert different elements or acceptable inputs for changing settings.
- 5.2 Use multiple tools for construction and composition by providing example code snippets next to visualizations, which can be manipulated in real time to observe visual changes
- 5.3: Build fluencies with graduated levels of support for practice and performance by providing a wide array of code snippets that provide differentiated models and options for increasing/decreasing scaffolding as students become more proficient at writing their own code.
- 7.1: Optimize individual choice and autonomy with multiple options for visualizing data through the use of different charts, libraries, and visual layouts.
Potential uses:
Trying to choose the “right” chart for data can be challenging when designing a dashboard or creating visualizations from scratch, and the R Graph Gallery can provide users with the option to compare multiple types of charts at once and learn how they are used to visualize different types of data. This can also help with breaking down tasks for creating visualizations into smaller steps, allowing students to interact with code snippets line-by-line to achieve desired results.
Related links
- The R Graph Gallery – Help and inspiration for R charts
- How To Create Accessible Diagrams For Low Vision
From Data to Viz | Find the graphic you need
From Data to Viz is a decision tree tool that helps users to choose what chart type will work best for the data they are presenting, and view example code in Python, R, and other languages. Users can also learn about different use cases for charts and read about common mistakes or features to try out when creating data visualizations in the application of their choice.
UDL checkpoints addressed
- 2.1: Clarifies vocabulary and symbols by providing definitions for different types of data and graphs, as well as embedded links to learn more about data analytics concepts.
- 2.2: Clarify syntax and structure by providing visual examples of data organization and graphs in addition to written explanations, as well as explanations of the structure of different graphs
- 2.5: Illustrate through multiple media through the use of accompanying images and visuals along with written explanations and code snippets
- 3.3: Guide information processing and visualization by providing step-by-step instructions on how to use different visualizations and progressively releasing information sequentially vs displaying all of the chart types at once
- 6.2: Support planning and strategy development through the use of prompts, checklists, and templates for creating visualizations with different languages and software
- 6.3: Facilitate managing information and resources by using a decision tree to organize different types of charts by data type and provide a consistent text format and layout to aid with notetaking and comparing different types of charts and use cases.
- 6.4: Enhance capacity for monitoring progress by using the decision tree to self-reflect and self-assess on why a particular visualization works or doesn’t work for the provided data, and receive guidance on how to find a solution that does work.
Potential uses
From Data to Viz provides a breakdown of how to choose a chart that will work well with a specific set or subset of data, and can serve as a planning support when creating dashboards or data visualizations for a given project. Besides explaining why a given chart type works well for a given example, it also shares why a chart type may not work for certain types of data, and offer alternatives that users can explore, instead of making them feel “stuck” and not providing alternatives. Students can also use the information as a checklist to ensure that all of the required information is included when constructing a visual and see an example of how it should be formatted.
Related links
- From data to Viz | Find the graphic you need
- Adapting Accessible Charts: Math Problems and Low Vision
Analyze Data in Excel
Analyze Data is an Excel feature that allows users to ask questions using natural language processing, generate summaries, and highlight trends/patterns to help them better understand their data through the use of recommended PivotTables, charts, visualizations, and more. Instead of using complicated formulas or building visualizations from scratch, Analyze Data helps answer questions about different fields and provides templates that highlight significant patterns or trends that can serve as a template for further customization or as a guide for further data exploration.
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information within the Excel UI, spreadsheets/source data, and individual visualizations.
- Excel UI: Customize display colors and application color scheme and visual layout and location of items on toolbars
- Spreadsheets/source data: Customize font size of information within cells and the use of color for emphasis/information (such as conditional formatting)
- Visualizations: Change size of content, customize colors and background contrast, visual layout of graph/chart, and fonts used
- 1.3: Offer alternatives for visual information through the use of auditory feedback, earcons, and including alt text/descriptions for visual content
- 2.2: Clarify syntax and structure of a given selection by highlighting structural relations and connections between different fields and datapoints.
- 3.2: Highlight patterns, critical features, big ideas, and relationships by using visual emphasis and drawing attention to critical or interesting features by pairing text labels with visualizations
- 4.2: Optimize access to tools and assistive technologies by providing options for screen reader and keyboard access, as well as automatically generated alt text when available
- 5.1: Use multiple media for communication by pairing spreadsheet data or datasets with customizable charts and visualizations.
- 5.3: Build fluencies with graduated levels of support for practice and performance by sharing multiple examples for modeling selected data and starter templates that can be modified further or left as-is.
- 7.1: Optimize individual choice and autonomy with multiple customization options for graphics, including the type of chart, color scheme, visual layout, and amount of information displayed
- 7.2: Optimize relevance, value, and authenticity by providing customized data insights that encourage experimentation and further exploration, as well as engaging in data storytelling
Potential uses
When students open a new dataset in Excel for the first time, they often have a lot of questions about what they are looking at that go beyond summary statistics like the mean, median, or mode, and may not even know where to start with finding out more. This is especially true for students that are impacted by visually cluttered spaces or large blocks of text. Analyze Data provides a “roadmap” for further exploration by answering questions about specific fields or high-level summaries, as well as recommended templates that can be further edited or customized to create dashboards or embedded charts and graphs.
Related links
Project Management and Organization
Microsoft Whiteboard
Microsoft Whiteboard is a free web and mobile digital whiteboard application available for all users with a Microsoft account; no 365/Office subscription required. Microsoft Whiteboard offers multiple input options for users, including stylus, drawing with a finger, drawing with a computer mouse, and keyboard access, as well as options for inserting multimedia content. Microsoft Whiteboard can be accessed by downloading applications for Apple/iOS, Android, or Windows devices, or accessed via web application.
UDL checkpoints addressed
- 1.1: Offer ways of customizing the display of information through options for adjusting font size, display scaling, and additional display settings such as dark mode.
- 1.3: Offer alternatives for visual information by providing alt text/image descriptions for all visual content included on the whiteboard, with options for enabling accessibility checker to ensure all areas are labeled
- 3.3: Guide information processing and visualization during the notetaking or project organization phases by breaking down information into smaller parts and using templates
- 4.1: Vary methods for response and navigation by providing multiple input options; including stylus, drawing with a finger, touchscreen keyboard, drawing with a computer mouse, and physical keyboard access, as well as options for inserting multimedia content
- 4.2: Optimize access to tools and assistive technologies by supporting keyboard shortcuts/keyboard access and screen reader access
- 6.3: Facilitate managing information and resources through the use of templates and organizers for gathering information and project notes
- 7.3: Minimize threats and distractions by having content automatically saved to the whiteboard and available from any device, along with unlimited workspace, compared to fixed size of whiteboard which can lead to students writing small or running out of room.
- 8.3: Foster collaboration and community by sharing whiteboards with other peers and mentors, who can contribute to ideas and provide feedback on group projects. Each student can view the workspace in real time and on their own device
Potential uses
Microsoft Whiteboard can be used to outline project ideas, using visual organizer templates, and during the notetaking process, with options for students to view whiteboards in real time as they are being edited. This can make it easier to see visual content (no faded markers or whiteboard glare), as well as provide a virtually unlimited amount of space for writing.
Related links
- Microsoft Whiteboard
- How I Use Microsoft Whiteboard With Low Vision
- Creating Audio Narrated Images For Low Vision
Rubber duck debugging
Also known as rubberducking, rubber duck debugging is a method for finding issues in code (“debugging”) where the user talks or writes about their problem in natural language, essentially explaining their code line-by-line to the duck. During this process, many users are able to come up with a solution or identify the issue as they explain what their code is supposed to do and what it is currently doing.
UDL checkpoints addressed
- 3.3: Guide information processing, visualization, and manipulation by reading/talking out loud and describing code/bugs in terms that make sense for the student, which can be technical or non-technical
- 6.4: Enhance capacity for monitoring progress by providing explicit opportunities for self-reflection and ongoing support during the debugging process
- 9.1: Promote expectations and beliefs that optimize motivation by encouraging self-reflection at different stages of a project, highlighting areas that can be improved or reconfigured
- 9.2: Facilitate coping skills and strategies for managing frustration with debugging and providing an opportunity to solve problems independently by talking them out. Make sure that students know not to throw ducks out of frustration!
Potential uses
Students can utilize rubberducking strategies during in-class labs or activities so that they can try solving problems on their own before asking a teacher or peer for additional assistance, or while working on homework/projects outside of the classroom. Students may choose to talk out loud to an actual duck, type out their problem or write it on a whiteboard, or use a virtual manipulative like QuackOverflow.
Related links
Pomofocus
Pomofocus is a web-based app that provides a customized Pomodoro timer that can be used to optimize focus and productivity when working on tasks, including tasks related to data analysis and schoolwork. Users can create a list of tasks, set timers for breaks, and track their progress for various goals.
UDL checkpoints addressed
- 3.3: Guide information processing and visualization by creating explicit prompts for each task by breaking them down into steps
- 6.1: Guide appropriate goal-setting through the use of checklists and prompts that can be used to help students stay on task and work towards desired goals or outcomes.
- 8.1: Heighten salience of goals and objectives by creating task breakdowns and setting goals for learning and productivity, as well as the use of a scheduling aid for budgeting time
- 8.2: Vary demands and resource to optimize challenge by customizing the time limits for breaks, work sessions, and break intervals for students who may need additional/longer breaks
- 9.1: Promote expectations and beliefs that optimize motivation by providing options for students to monitor their own progress for completing various tasks and displaying reminders that can help students remain focused on tasks
Potential uses
Students may get distracted when working on technical assignments or activities, or may hyperfocus and forget to take breaks, both of which can have an impact on their finished program and their mental health. Using techniques like the Pomodoro method can help provide additional support for focusing and paying attention, while honoring the need for breaks and time away from screens.
Related links
More resources on UDL for data science
- Pre-Teaching Programming Languages To Visually Impaired Students
- Tips For Teaching R Programming To A Low Vision Student
- Free Accessible Coding Resources With Large Print Options
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Published April 24, 2024. Updated March 2026