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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.
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.
Formative Assessments
Formative assessments encompass a broad range of low-stakes activities aimed at improving student learning outcomes. In contrast to summative assessments, which are intended to measure products of student learning, formative assessments are oriented towards the learning process itself (Black & Wiliam, 1998). They can provide students with opportunities to evaluate their developing understanding of key concepts, practice new skills, and prepare for summative assessments (McLaughlin & Yan, 2017; Orange, Agak, Okelo, & Kiprotich, 2018). They can also provide instructors with valuable data on student progress (Bell & Cowie, 2001; McLaughlin & Yan, 2017). The results of formative assessments can indicate where individual students are struggling or excelling, allowing instructors to provide targeted feedback and tailor their instructional delivery accordingly.