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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 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.

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.

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.

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.

Transferring your course online opens a world of possibilities. In fact, you might be tempted to spend hours trying to locate and learn new educational technologies, or to rebuild your entire course in the learning management system (LMS). But while effective use of technology can certainly enhance learning experiences, it can also introduce obstacles for both faculty and students.

“How do I choose the right technology?” is a common question in education generally, and in online program management in particular, where it is usually asked in the context of developing an online course or other virtual learning experience. After all, the Subject Matter Expert and Instructional Designer are hoping to create an experience for students that is both meaningful and valuable. Knowing how to orchestrate content and pedagogy is already hard enough, but add in the fact that there are thousands of technology options, and the task can feel even more daunting.