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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.

Case-based learning allows students to develop higher-order critical thinking, problem-solving, synthesis, analysis, and communication skills by engaging with a realistic scenario in service of practicing course skills and concepts. Case studies are valuable tools for any class that combines asynchronous and synchronous learning. Indeed, some research (e.g., Webb, Gill, & Poe, 2005) suggests that a multimodal delivery model may be ideal for case study-based work, with the combination of synchronous and asynchronous elements enabling students to participate more fully in cases. In the first half of this piece, we outline some key considerations for using case studies in a multimodal course. In the second half, we make targeted recommendations for effectively prepping, facilitating, and reflecting on your multimodal case studies.

Case studies are an effective and powerful pedagogical tool. They present realistic narratives to students and require them to analyze possible outcomes or solve a dilemma or challenge associated with the narrative, and they are often followed by a series of questions or prompts that ask students to demonstrate their learning. Case studies can be based on real-world situations or fictional scenarios modeled on authentic occurrences. Regardless of the source and format, case studies provide students an opportunity to practice solving problems that they might encounter in the future.

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.

Halfway through the term isn't a great time to change around a bunch of materials or assignments in your course. However, it is a useful moment to evaluate how the course is going, realign to match the goals you set out at the beginning of the term, and determine what you may be able to tweak to make your course work more effectively for you and for your students. This piece suggests actions you can take at midterm to help shape the second half of the course.