Search
There are 25 results.
Category
Tag
Tag
All (86)
Active Learning (3)
Analytics (4)
Animations (1)
Assessments (5)
Asynchrony (6)
Authentic Activities (2)
Backwards Design (2)
Belonging (2)
Canvas (7)
Case Studies (2)
Collaboration (4)
Communication (8)
Community (7)
Content Creation (2)
Copyright (2)
Course Maintenance (1)
Course Materials (3)
Course Preparation (5)
Discussions (5)
Diversity (3)
Equity (1)
Faculty Presence (3)
Faculty Support (1)
Feedback (8)
Formative Assessments (6)
Game-Based Learning (2)
Gamification (1)
Generative AI (2)
Grading (5)
Group Work (2)
Inclusion (4)
Infographics (1)
Learning Objectives (3)
Multimodality (7)
Peer Review (1)
Podcasts (1)
Presentations (1)
Qualitative courses (1)
Quantitative courses (1)
Rubrics (2)
Scaffolding (1)
Social Media (2)
Summative Assessments (1)
Synchrony (8)
Third-Party Tools (2)
Universal Design for Learning (UDL) (1)
Video (4)
Visual Design (1)
Workload (1)
Written Assignments (1)
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.
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.
Increase Engagement Now
Whether you’re halfway through the term or just getting started, this post presents actionable, simple strategies you can implement immediately to increase engagement in your course.
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.
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.
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.
Six Strategies for Multimodal Content Delivery
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.