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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).
Incorporating Multimedia in Your Course
Multimedia, which helps create an engaging and interactive online learning environment, has been shown to contribute to improved student performance (Cheng et al., 2009, p. 1). Though many online courses incorporate videos, they neglect to feature other forms of multimedia. And, while videos are a staple of multimedia use, there are other exciting options to consider: podcast episodes, graphics, and animations can all enhance course content, enriching the student experience. To maximize the benefits multimedia can provide, consider including these underutilized forms of multimedia in your course.
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.
Engagement Series: Introduction
There are many components to consider when developing an online course; a key framework to inform course development is student engagement. The Glossary of Education Reform defines student engagement as “the degree of attention, curiosity, interest, optimism, and passion that students show when they are learning or being taught, which extends to the level of motivation they have to learn and progress in their education” (Great Schools Partnership, 2016, para. 1). Developing and evaluating course content through the lens of engagement can help instructors create an environment that is conducive to learning and mastery of course outcomes.
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.