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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.
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.
Inclusive Language
Use inclusive language across course content and communications to reach every learner. “Inclusive education must be cultivated deliberately if we want to advance in its implementation” (Márquez & Melero-Aguilar, 2022, p. 842). Inclusion entails creating an environment of open participation for all individuals. Inclusive course design works to ensure that all students feel heard, valued, and validated. The thoughtful use of language can establish an environment of inclusion in online learning.
Game-Based Learning Experiences
Game-based learning (GBL) is a learning experience, or set of learning experiences, delivered through gameplay or game-like activities with defined learning outcomes. GBL is often confused with gamification, which is the application of game elements to a non-gaming experience. GBL engages students cognitively, emotionally, behaviorally, and socioculturally (Plass et al., 2015). Many factors should be considered when designing GBL, including narrative, player positioning, and interactive design (Dickey, 2005).
Engagement Series: Student-Content Engagement
This is the second in a series of pieces exploring different types of course engagement. This piece focuses on how course developers and instructors can foster student-content engagement in online courses.
Best Practices for Screencast
Do you want to deliver presentations, share tutorials, or teach complex applications in your online course? If so, creating screencasts may be a great option for you. This piece defines what a screencast is, identifies important development considerations and common instructional use cases, and highlights best practices for creating screencasts for your online course.
Creating Video: 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.
Data-Centric Recommendations for Video Engagement
Incorporating prerecorded videos and animations into online learning experiences allows students the opportunity to access content at any time after the material is delivered. The inclusion of video and animation in online learning is now ubiquitous. To promote engagement, it is imperative that such content be delivered to learners clearly and effectively.
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.