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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).

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.

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.

Good page design requires balance between white space, or negative space, and positive space. Positive space encompasses all aspects and types of content; on a course page, these objects might include an introductory paragraph, video thumbnail, infographic, callout box, opinion poll, or provocative quotation. Relative to these course components, white space might seem like a nice-to-have. Because it promotes clarity and reduces distortion, however, white space is just as important to instructional page design as content.

Course developers (those who build individual courses) play a crucial role in the success of an online degree program by providing expertise and bringing unique perspectives. Accordingly, it is valuable for faculty to customize their course spaces by infusing them with their own knowledge and personality. At the same time, it is also crucial to prioritize structural consistency within and across courses in an online program, as course consistency is a key aspect of accessibility and a key contributing factor to student success. In particular, students must be able to perceive, operate, and understand the course and course materials using program-standard devices and certain assistive technologies, and this should be true across all of the courses in a program. This is where program chairs and administrators can help support faculty in standardizing key elements of courses to facilitate a seamless student experience. In this piece, we discuss how maintaining structural consistency within and across courses can positively impact accessibility.

When you think of a scientist, who comes to mind? If it’s Albert Einstein or Charles Darwin, you’re not alone. Gender stereotypes and a lack of inclusive role models in science, technology, engineering, and math (STEM) have contributed to spaces that have not always been welcoming for African American, Indigenous, and Latino students or those from other historically underserved groups (American Association of University Women, n.d.). Kimberlé Crenshaw’s concept of intersectionality, a term she coined in 1989, provides a framework for understanding Black women’s lived and overlapping experiences of racism and sexism (Center for Excellence in Teaching and Learning, n.d.; TED, 2016). Crenshaw, a law professor and Black feminist scholar, explains that “intersectionality is a lens through which you can see where power comes and collides, where it interlocks and intersects” (Columbia Law School, 2017).

Employing a variety of modes of instruction and assessment, as recommended by Universal Design for Learning (UDL) principles, can enhance the learning experience for students in quantitative courses. Diverse elements such as visual aids, interactive features, and real-world applications can complement, extend, or replace traditional lectures and exams. Since classes consist of students with varying learning preferences and strategies, using multiple modes of representation in a course promotes deeper understanding, engagement, and skill development. This piece details design elements that can be particularly impactful in quantitative courses.

Universal Design for Learning (UDL), which has roots in Ronald Mace’s concept of Universal Design, is a pedagogical framework that supports diverse learning needs. According to CAST, the creator of the framework, UDL seeks “to improve and optimize teaching and learning for all people based on scientific insights into how humans learn” (2018). UDL is not a step-by-step curriculum plan, but rather an approach to pedagogy and curriculum development that aims to make the learning environment as accessible as possible for as many learners as possible (Derer, 2021; CAST, 2018).