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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.

Case-based learning allows students to develop higher-order critical thinking, problem-solving, synthesis, analysis, and communication skills by engaging with a realistic scenario in service of practicing course skills and concepts. Case studies are valuable tools for any class that combines asynchronous and synchronous learning. Indeed, some research (e.g., Webb, Gill, & Poe, 2005) suggests that a multimodal delivery model may be ideal for case study-based work, with the combination of synchronous and asynchronous elements enabling students to participate more fully in cases. In the first half of this piece, we outline some key considerations for using case studies in a multimodal course. In the second half, we make targeted recommendations for effectively prepping, facilitating, and reflecting on your multimodal case studies.

Situations may present themselves in which links or rubrics from another course can be useful in a current course. Should this occur, rubrics from other courses can be uploaded into another course. To successfully insert a previously built rubric, please follow the following steps.

Over time, you may want to make changes to the syllabus of a course. The syllabus documents are saved in the “Files” area (1) of the course. To preserve the integrity of the document, the Word document is located in the “Instructor Only” folder (3) and the PDF is found in the “Documents” folder (2) so it is visible to students.

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.