Captioning video content is an essential part of creating high-quality educational resources that improve student outcomes and user engagement. Captions and transcripts provide a text alternative to audio that provides viewers with additional ways to access content, improves overall comprehension, and supports audience variability. Captions improve comprehension by removing common miscommunications stemming from variations in:
- hearing ability,
- speaker accent,
- audio quality,
- listener’s primary language,
- complexity of the subject matter, and
- missed audio content.
- Closed Captions
- Closed captions are a text alternative to video that can be enabled or disabled by an end user.
- Machine Captions
- Machine captions use a combination of automatic speech recognition and artificial Intelligence to convert audio to text. These can be streamed in real time or requested afterwards for a video recording.
- Live Captioning (CART)
- Live captions are a synchrounous, text alternative to video that can be streamed in real time to users either through the closed caption functionality of a video conferencing tool or in a separate browser window.
- Open Captions
- Open captions are a text alternative that is "always on" and cannot be disabled by an end user, such as might be displayed during a live performance.
- A text alternative to audio that is typically unsynchronized to an audio recording and provided as a separate document.
- Interactive transcript
- An interactive transcript is a transcript that acts like a link. Selecting the text will cause the video or audio playback to move to that location.
Virginia Tech is proud to commit to inclusive media for faculty, staff, students, and all audiences who consume video content across our digital platforms. By proactively considering the need for captions, the university aligns efforts with legal requirements. These include the Americans with Disabilities Act (as amended) including Title II of the Americans with Disabilities Act (as amended) Section 504 of the Rehabilitation Act of 1973, and Section 508 of the Rehabilitation Act of 1973 as required by Virginia State Law. Additionally, captions support Virginia Tech’s Keep C.A.L.M and Caption-On campaign. By making closed captioning a priority, we successfully meet Web Content Accessibility Guidelines 2.0 (WCAG) criterion 1.2.2. and further demonstrate commitment to IT Accessibility Policy 7215.
For all of these reasons, Virginia Tech requires that all public-facing videos and live events produced by the university include closed captioning. Captioning provides universal benefit to increase engagement and message clarity and aligns with Virginia Tech’s commitment to inclusion and access as outlined in the Virginia Tech Difference - Advancing Beyond Boundaries. This commitment has been enabled by senior leaders across the university, resulting in the allocation of centralized funds to provide both live and post-production closed captions to advance the university mission.
Live captioning is required for any live, digital, public-facing event across the university (e.g., webinars, seminars, and town halls). Class meetings are supported through accommodations from Services for Students with Disabilities. Internal meetings for Virginia Tech employees may not require live captions unless requested as an accommodation. Events that are exclusive to Virginia Tech students may not require live captions unless they are open to the entire campus or requested as an accommodation. University sponsored events should use a registration process that includes an accommodation request statement to help determine if live captions or other accommodations are required. The synchronous live captions can be integrated into Zoom or provided via a separate browser window for the end user. Live Captioning is a requestable service for university faculty and staff.
For pre-recorded videos, such as news announcements or course lectures, post-production captions are legally required for creating inclusive media. Currently, any Zoom cloud recordings will be automatically captioned using machine generated captions (70-90% accuracy rate). Any recordings that will be shared through a public facing website or Canvas course should be edited for accuracy using the Captioning Key Guidelines and built-in captioning editor in Kaltura. Video owners, if desired, can hide the automatic captions while they are being edited for accuracy.
Videos for instruction that will be re-used for multiple semesters are eligible for 99% accurate professional captioning and can be pre-approved by completing the request form. Any videos that do not qualify for the centralized captioning service can still be professionally captioned at the rates listed in 4help. Videos stored in a location outside of Kaltura (e.g., YouTube, Vimeo, et. cetera) can leverage the capabilities of those systems to create captions or download the output from Kaltura and upload it to the host location.
Transcripts are required for audio-only content like podcasts. Previously, transcripts had to be downloaded and made available to viewers as a separate document. While that is still an acceptable solution, videos within Kaltura now have an interactive transcript widget that appears as soon as the automatic machine generated captions or professional captions finish processing. When using the Kaltura video player in Canvas or Ensemble, the link to the interactive transcript will appear beneath the video player. When using Live Captioning services integrated with Zoom, a live transcript is also available. Providing a transcript for systems outside of Zoom and Kaltura depends on the capabilities of the video player.
Morris, K. K., Frechette, C., Dukes, L., Stowell, N., Topping, N. E., & Brodosi, D. (2016). Closed Captioning Matters: Examining the Value of Closed Captions for “All” Students. Journal of Postsecondary Education and Disability, 29(3), 231–238.
Tisdell, C., & Loch, B. (2017). How useful are closed captions for learning mathematics via online video? International Journal of Mathematical Education in Science and Technology, 48(2), 229–243. https://doi.org/10.1080/0020739X.2016.1238518
Whitney, M., & Dallas, B. (2019). Captioning Online Course Videos: An Investigation into Knowledge Retention and Student Perception. Proceedings of the 50th ACM Technical Symposium on Computer Science Education, 511–517. https://doi.org/10.1145/3287324.3287347