Minor LTI 1.3 Changes: New OIDC Auth Endpoint, Support for Platform Storage
Canvas is changing its LTI 1.3 OIDC Auth domain to align with security practices and to support the new LTI 1.3 Platform Storage specification. This specification lets LTI tools function when browsers disable cross-site 3rd-party cookies. LTI 1.3 tool developers, read on for an implementation guide ...
Engineerica Keynote Series: Teaching Students How to Study, Learn, and Grow
Call us at 407.366.7700 or email us at info@engineerica.com to set up a free demo or appointment.In this session, Correy Hammond discusses how to coach stude...
What is the Canvas release schedule for beta, production, and test environments?
Instructure is committed to consistently improving the Canvas user experience. The cloud-based platform maintains an agile production cycle with bug fixes, enhancements, and new features in three Canvas environments: beta, production, and test. All Canvas environments are also available on any mobi...
Hi all, Despite in Canvas Documentation says that "Delete a user" process cannot be undone (How do I delete a user from an account?) , we have the situation where a user was deleted but when an application tried to create it again with the same SIS_USER_ID the API response is "The SIS_ID i...
DCMP's Captioning Key provides guidelines, examples, and resources for captioning educational media, and is used by professionals and amateurs around the globe.
If enabled by your institution, you can use Course Pacing to define a pace in which students must complete course tasks. This allows students with different start dates to have the same time frame in which they must complete course tasks.. Notes: The Course Pacing feature preview is in active devel...
Summary In Courses, Course Pacing distributes due dates on a defined pace for rolling enrollments. This feature preview allows magical distribution of due dates for students with different start dates based on an instructor’s defined pace. Availability To learn about managing feature option states, ...
This book will teach you how to do data science with R: You’ll learn how to get your data into R, get it into the most useful structure, transform it, visualise it and model it. In this book, you will find a practicum of skills for data science. Just as a chemist learns how to clean test tubes and stock a lab, you’ll learn how to clean data and draw plots—and many other things besides. These are the skills that allow data science to happen, and here you will find the best practices for doing each of these things with R. You’ll learn how to use the grammar of graphics, literate programming, and reproducible research to save time. You’ll also learn how to manage cognitive resources to facilitate discoveries when wrangling, visualising, and exploring data.
What happens to higher education curriculum in a world revised by AI?This week the Forum continues our exploration of AI's impact with a great guest, profess...
Introducing LLaMA: A foundational, 65-billion-parameter language model
Today, we’re releasing our LLaMA (Large Language Model Meta AI) foundational model with a gated release. LLaMA is more efficient and competitive with previously published models of a similar size on existing benchmarks.
Ph.D. in Higher Education Leadership (April 2011) Western Michigan University (Kalamazoo, MI) Dissertation: Knowledge, Attitudes, and Instructional Practices of Community College Math Instructors: The Search for a KAP Gap in Collegiate Math M.S. Mathematics (May 2002) University of Wyoming (Laramie, WY) Thesis: Max-Plus Algebra Properties and Applications M.B.A. (August 2001) University of Wyoming (Laramie, WY) […]