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If you’re developing a course with synchronous and asynchronous elements, you have a host of options for engaging students and delivering content. Research suggests that incorporating multiple modalities increases accessibility, engagement, and learning (Mick and Middlebrook, 2015; Margolis et al., 2017). With that said, it is important to be intentional about multimodal course design. Both synchronous and asynchronous methods of delivery are effective, but activities can be better suited to one or the other modality and synchronous time is often limited. Delivering selected content asynchronously can support students’ understanding of how information is organized and leave more time for interactivity in synchronous sessions.

Use inclusive language across course content and communications to reach every learner. “Inclusive education must be cultivated deliberately if we want to advance in its implementation” (Márquez & Melero-Aguilar, 2022, p. 842). Inclusion entails creating an environment of open participation for all individuals. Inclusive course design works to ensure that all students feel heard, valued, and validated. The thoughtful use of language can establish an environment of inclusion in online learning.

From time to time instructors may want to include in their courses copyrighted materials like images, print content, audio recordings, or videos. The University of Minnesota Libraries define copyright as “the area of law that deals with creation, ownership, sale, and use of creative and expressive works.”

With the help of tools like Canvas New Analytics, faculty can leverage learning management system (LMS) data to hone their instructional techniques and improve their online students' experience. In this piece, we provide an introduction to learning analytics in online higher education and detail some analytics best practices.

At the end of 2019, Canvas rolled out New Analytics, a new version of their former analytics tool, Course Analytics. By Canvas' own description, New Analytics retains the core functionality of Course Analytics while offering a simplified user experience. In this post we share our recommendations for leveraging New Analytics to support students.

For many people, “online learning” conjures images of successive videos, shot in a studio or perhaps on location, featuring high production value and expert, polished speakers, interspersed with short quizzes or activities. Indeed, strongholds such as MasterClass, LinkedIn Learning, and Coursera have mastered this formula and led many to believe that it is the recipe for success. While the economic success of these companies is undeniable, the effectiveness of an online course is measured by student success. When done well, video can have a positive impact on student learning (Clark & Mayer, 2011). Rather than designing your course according to the economic model, follow the evidence and research-based principles of visual communication, cognitive science, and online learning to decide when and how to create instructional videos. Through careful consideration of your learners, your objectives, your constraints, and the following best practices, you can spend your time and resources creating only the most essential videos. For a visual aid that accompanies this article, see the Video Planning Decision Tree.