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Representation in Course Images
How many times have you looked at an image and thought, “Have I seen this before?” Chances are, if you are browsing a stock photo site, it’s often. That feeling of déjà vu occurs because images reflect an amalgam of artistic, cultural, and ideological influences (Hall, 2015).
Written Assignment Best Practices Guide
Formal writing requires sustained focus on content and close attention to detail. For these reasons, written assignments can be an effective assessment tool in graduate courses when they are thoughtfully and purposefully designed. This guide provides recommendations for faculty who are looking to harness the pedagogical benefits of written assignments.
Selecting Images: Personal Experience Insights
In our Personal Experience Insights series, members of the Everspring Learning Design department share first-hand accounts of creating online learning content and meaningful takeaways from their professional experiences.
LMS Analytics: Supporting Your Students With Data
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.
Navigating Canvas New Analytics
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.
Enhancing Quantitative Courses With Varied Learning Approaches
Employing a variety of modes of instruction and assessment, as recommended by Universal Design for Learning (UDL) principles, can enhance the learning experience for students in quantitative courses. Diverse elements such as visual aids, interactive features, and real-world applications can complement, extend, or replace traditional lectures and exams. Since classes consist of students with varying learning preferences and strategies, using multiple modes of representation in a course promotes deeper understanding, engagement, and skill development. This piece details design elements that can be particularly impactful in quantitative courses.
Taking Stock at the Midpoint of the Term
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.
Student Support in a Multimodal Course
Multimodal courses allow for exciting opportunities in course content and activities but can be, by design, less flexible than asynchronous courses and less predictable than synchronous courses. These opportunities thus come with needs for additional logistical support and flexibility, as students need both to be able to take advantage of the opportunities of synchrony and asynchrony equitably. How can you best support students in a multimodal course, providing guidance through multiple forms of interaction? This piece gives insight into what kinds of support benefit students in multimodal courses and how to provide them. We’ll end with five quick tips for supporting students that apply to almost any multimodal course.
Multimodal Models
Designing a successful multimodal course means, at each step of the process, considering what each format does well—structuring the course such that each piece of content, each activity, each interaction uses the most effective delivery method available. But what does that look like in practice? This piece describes three approaches to structuring a multimodal course. In each model, asynchronous and synchronous time complement one another and further module and course objectives. Where the models differ is in the relative importance of asynchronous activities in enabling students to complete synchronous activities and vice versa.