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Incorporating Multimedia in Your Course
Multimedia, which helps create an engaging and interactive online learning environment, has been shown to contribute to improved student performance (Cheng et al., 2009, p. 1). Though many online courses incorporate videos, they neglect to feature other forms of multimedia. And, while videos are a staple of multimedia use, there are other exciting options to consider: podcast episodes, graphics, and animations can all enhance course content, enriching the student experience. To maximize the benefits multimedia can provide, consider including these underutilized forms of multimedia in your course.
Backward Design
Backward design is, as the name suggests, a process for designing curricula, courses, and lectures by working backwards from big-picture learning goals. The concept, introduced by Grant Wiggins and Jay McTighe (2005), suggests that instructors create assessments, activities, and course content that are explicitly aligned with the broader learning goals of the unit. This is different from the traditional content-driven approach to learning design, which focuses on course content first and only secondarily tries to align that content with learning goals.
Implementing Social Media
Many students use social media platforms in their daily lives, and “emerging evidence indicates that students express positive attitudes toward using social media for learning in general” (Baisley-Nodine, Ritzhaupt & Antonenko, 2018). However, there are also many concerns connected with using social media in an educational setting. These include issues related to a lack of familiarity with the platform, the potential for distraction, and privacy concerns. Therefore, it is important to carefully plan the use of social media in a course to address any potential issues or concerns.
Artificial Intelligence and Online Learning
Higher education institutions are racing to keep pace with the disruption caused by artificial intelligence (AI) tools. A 2023 QuickPoll survey by Educause found that 83% of higher education stakeholders believe generative AI will "profoundly change" the sector over the next three to five years. Additionally, 65% agreed that "the use of generative AI in higher ed has more benefits than drawbacks" (McCormack, 2023, Table 1). While institutions are exploring AI's potential in areas such as admissions, enrollment, administrative duties, scheduling, and institutional data research, this piece focuses on the overarching risks and rewards AI presents in teaching and learning.
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.
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.
Rubrics as a Tool to Support Equity and Inclusion
While student populations have become increasingly diverse, many groups, including first-generation, non-native English speakers, and individuals with disabilities, still face barriers and bias that can derail their success in college (Super et al., 2020). Traditional grading practices—including penalties for late work, writing in dialects other than standard English, and even plagiarism— are prone to bias and only perpetuate disparities, the research says (Feldman, 2019; Savini, 2021).