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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.

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.

To foster academic integrity, pair anti-plagiarism tools with clear conduct expectations and authentic low-stakes assessments. When designing and teaching online courses, maintaining academic integrity is frequently top of mind. In many cases, faculty may opt to adopt third-party tools to monitor student work. Despite the prevalence of academic monitoring software in online courses, however, the most powerful tools for promoting academic integrity are introduced much earlier in the course build process.

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.

Universal Design for Learning (UDL), which has roots in Ronald Mace’s concept of Universal Design, is a pedagogical framework that supports diverse learning needs. According to CAST, the creator of the framework, UDL seeks “to improve and optimize teaching and learning for all people based on scientific insights into how humans learn” (2018). UDL is not a step-by-step curriculum plan, but rather an approach to pedagogy and curriculum development that aims to make the learning environment as accessible as possible for as many learners as possible (Derer, 2021; CAST, 2018).

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.

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.

From trivia games to final exams, quizzing tools have a variety of uses for learning as well as assessment. Exams and quizzes have a particularly plentiful range of possibilities in a multimodal or hybrid course, where they can be administered synchronously or asynchronously. Research suggests that the presentation of a tool influences student behavior in response to the tool. In comparing two student discussion boards, one an ungraded discussion and one a graded replacement for a final exam, Cheng et al. (2013) found that students displayed more knowledge on the graded board, but more evidence of learning on the ungraded board. The students who participated in the study were more likely to grapple with new ideas when the stakes were low, but more eager to showcase topics they were confident about when their responses would have a greater impact on their grades. When considering quizzing tools, then, we recommend allowing your course goals to guide your usage.

Whether designing a fully asynchronous course or a hybrid/blended learning experience, you’re likely thinking about recording a video to explain an idea, tell a story, or demonstrate a skill. And, in many situations, you should (see the Envision piece Video Planning: To Record or Not to Record? if you are wondering whether video is appropriate for your unique situation). Most research shows that online students enjoy learning from video and that it can be an effective way to deliver content. Students often appreciate the opportunity to review material at their own pace and to pause, rewind, and rewatch content as needed (Boateng et. al. 2016; Brame 2016).

For many people, “online learning” conjures images of successive videos, shot in a studio or perhaps on location, featuring high production value and expert, polished speakers, interspersed with short quizzes or activities. Indeed, strongholds such as MasterClass, LinkedIn Learning, and Coursera have mastered this formula and led many to believe that it is the recipe for success. While the economic success of these companies is undeniable, the effectiveness of an online course is measured by student success. When done well, video can have a positive impact on student learning (Clark & Mayer, 2011). Rather than designing your course according to the economic model, follow the evidence and research-based principles of visual communication, cognitive science, and online learning to decide when and how to create instructional videos. Through careful consideration of your learners, your objectives, your constraints, and the following best practices, you can spend your time and resources creating only the most essential videos. For a visual aid that accompanies this article, see the Video Planning Decision Tree.