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Enhancing Quantitative Courses With Varied Learning Approaches
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.
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.
Improving PowerPoints
Sharing information via PowerPoint presentations is a long-established strategy in higher education. Designing PowerPoint presentations for online courses can pose unique challenges; however, best practices can help overcome these hurdles. With time and attention, faculty and instructional designers can create engaging and purposeful presentations with lasting value.
Presentation Best Practices Guide
Many online courses focus on written communication skills, featuring discussion posts, papers, and case study reports among other assignments. However, oral communication and presentation skills are just as integral to students’ success, and, indeed, many employers list presenting as one of the most desirable skills for job candidates (Suhadi et al., 2021).
Zoom Into Online Learning
Faculty often express concern over how to maintain personal relationships with their students in an online course space; incorporating optional synchronous elements to an online course can help “put a face” to a name. Zoom, the video conferencing tool that allows you to create synchronous experiences for their students, has become ubiquitous in educational and businesses in the past two years.
Academic Integrity in Assessment
To foster academic integrity, pair anti-plagiarism tools with clear conduct expectations and authentic low-stakes assessments. When designing and teaching online courses, maintaining academic integrity is frequently top of mind. In many cases, faculty may opt to adopt third-party tools to monitor student work. Despite the prevalence of academic monitoring software in online courses, however, the most powerful tools for promoting academic integrity are introduced much earlier in the course build process.
Instructor Presence in Online Courses
Consistent and meaningful instructor presence is one of the most important drivers of student success and satisfaction in online courses (Roddy et al., 2017). However, establishing instructor presence online can be challenging. In fact, studies have shown that many online students feel their instructors are largely invisible (Tichavsky et al., 2015).