Search
There are 44 results.
Category
Tag
Tag
All (124)
Active Learning (4)
Activities (4)
Alt Text (2)
Analytics (4)
Animations (1)
Assessments (7)
Asynchrony (6)
Authentic Activities (2)
Backwards Design (2)
Belonging (3)
Canvas (10)
Case Studies (2)
Collaboration (5)
Color Contrast (2)
Communication (8)
Community (7)
Content Creation (12)
Copyright (2)
Course Maintenance (5)
Course Materials (7)
Course Preparation (6)
Discussions (5)
Diversity (5)
Equity (2)
Faculty Presence (3)
Faculty Support (2)
Feedback (8)
Formative Assessments (6)
Game-Based Learning (2)
Gamification (1)
Generative AI (2)
Grading (5)
Group Work (2)
Hyperlinks (1)
Images (3)
Inclusion (6)
Infographics (2)
Learning Objectives (3)
Multimodality (7)
Page Design (2)
Peer Review (1)
Podcasts (1)
PowerPoint (2)
Presentations (2)
Qualitative courses (1)
Quantitative courses (1)
Representation (1)
Revising (2)
Rubrics (4)
Scaffolding (1)
Screen Readers (1)
Social Media (2)
Summative Assessments (1)
Synchrony (8)
Third-Party Tools (2)
Universal Design for Learning (UDL) (2)
Video (12)
Visual Accessibility (2)
Visual Design (2)
Workload (1)
Written Assignments (1)
Best Practices for Screencast
Do you want to deliver presentations, share tutorials, or teach complex applications in your online course? If so, creating screencasts may be a great option for you. This piece defines what a screencast is, identifies important development considerations and common instructional use cases, and highlights best practices for creating screencasts for your online course.
Data-Centric Recommendations for Video Engagement
Incorporating prerecorded videos and animations into online learning experiences allows students the opportunity to access content at any time after the material is delivered. The inclusion of video and animation in online learning is now ubiquitous. To promote engagement, it is imperative that such content be delivered to learners clearly and effectively.
Rubrics as a Tool to Support Equity and Inclusion
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).
Inclusive Texts
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).
Universal Design for Learning
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).
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.
Creating Learning Objectives
Learning objectives help inform students about what they will learn and how they will be assessed. Objectives are meant to align with course expectations. Therefore, any assigned exercises should be guided by the course’s specific learning objectives. Everything in the course should work together to ensure students master the course objectives.
Problem-Based Learning
Problem Based Learning is a teaching method used to facilitate student knowledge acquisition. This teaching method is often confused with Project Based Learning, which centers on students applying knowledge. The focus of Problem Based Learning is students acquiring the knowledge. Since the two methods use the same acronym, they are easily confused, but have different objectives for students.