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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).
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.
Branching Scenario Best Practices Guide
Designed to simulate real-world experiences, branching scenarios are powerful tools for increasing student engagement. Like a choose-your-own-adventure book, a branching scenario invites users to explore a virtual world, using knowledge and skills from their coursework and information shared within the scenario to make decisions. The decisions they make lead them down different pathways (some of which may include embedded documents and videos) towards different endings. Depending on the complexity of the branching scenarios and the choices students make, they can experience a variety of different possible outcomes within a single scenario.
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.
Using Hotspots
A unique way to share information, images with hotspots offer online learners the opportunity to interact with course content. Learners can click or hover on particular parts of an image and receive pop-ups giving them more information. Hotspots represent information in a particular context; thus, they fulfill the multimedia principle—use words and graphics rather than words alone—and the contiguity principle—align words to corresponding graphics (Clark & Mayer, 2016).
The Power of Retrieval Practice
Faculty aim to impart lasting knowledge and skills, but sometimes, learning doesn’t stick. One of the most powerful techniques for enhancing students’ long-term retention is retrieval practice, the process of actively recalling information to mind rather than passively reading or reviewing it. In this piece, we’ll dive into the evidence behind retrieval practice, provide strategies for how to incorporate it into online courses, suggest ways to frame its utility to students to ensure they fully reap the benefits of this learning strategy, and describe specific types of retrieval practice activities.
Types of Retrieval Practice Activities
By incorporating regular retrieval practice into your online course, you can ensure that key takeaways are actually being taken away by students to use in the future rather than being left behind due to lack of use. The following are some specific activities that can help move learners from a hazy recollection of something toward more clarity and permanence.