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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.
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.
Teaching Styles Series: Introduction
This is the first in a series of pieces examining online instructor teaching styles. In this introductory piece, we will characterize teaching styles, summarize Anthony Grasha’s typology of teaching styles, and discuss how identifying your teaching style (or styles) can inform online course design and instruction. In subsequent pieces, we will explore each of Grasha’s teaching styles in depth.
Developing AI Literacy Across the Curriculum: A Guide for Programs and Faculty
The rapid integration of AI into professional practice across disciplines makes AI literacy increasingly crucial, not just for technology-focused fields but for all areas of study. Even faculty who are skeptical of AI's value need to consider how it's transforming their disciplines. For example, scientific fields are seeing AI adoption in literature reviews, experimental design, and data analysis. In the humanities, AI tools are already being used for textual analysis, translation, and content creation. Creative disciplines must grapple with AI's impact on artistic production and copyright. Professional programs face increasing pressure from employers who expect graduates to understand AI applications in their field.
Fostering Deep Learning and Motivation in the AI Era
As generative artificial intelligence (genAI) reshapes the educational landscape, faculty must rethink traditional assessment strategies to maintain academic integrity and real-world relevance. This piece explores strategies for creating effective assessments in an AI-mediated world, focusing on two key areas: collaborative activities that develop essential human skills, and formative assessments that emphasize personal growth and deep learning. These approaches not only address concerns about AI misuse but also prepare students for future workplaces where human capabilities will complement AI tools.