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While student populations have become increasingly diverse, many groups, including first-generation, non-native English speakers, and individuals with disabilities, still face barriers and bias that can derail their success in college (Super et al., 2020). Traditional grading practices—including penalties for late work, writing in dialects other than standard English, and even plagiarism— are prone to bias and only perpetuate disparities, the research says (Feldman, 2019; Savini, 2021).

Today’s students are diverse and include marginalized groups that have historically been excluded from mainstream education (Ladson-Billings, 2013). In 2021, students of color comprised upwards of 40% of the 15.4 million undergraduates enrolled in U.S. colleges and universities (Nam, 2023; National Center for Education Statistics, 2023). Gloria Ladson-Billings, whose work centers on culturally relevant pedagogy, argues that diverse students require inclusive learning to succeed. “[These students] do not fit neatly into the rigid categories of race, class, gender, or national origin” upon which hierarchies of the past have been built (Ladson-Billings, 2013, p. 5), so authentic representation of diversity in higher education is critical. Adrienne Keene, an assistant professor of American Studies at Brown University, writes that instructors can do their part to support underrepresented students by being honest about their own bias and blind spots, critiquing their course materials, and integrating meaningful representations of diversity into the curriculum (Fuchs et al., 2020; Keene, 2015).

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.

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.

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.

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.