A major concern with increasing student numbers is maintaining the quality of the student experience. Faculty employ both pedagogical approaches and educational technologies to reach ever-increasing numbers of students. While numerous approaches have been successfully deployed in the classrooms of large enrollment courses (for example, iClickers), office hours are often administered in the traditional method which does not account for, nor take advantage of, large student enrollments. As our large courses continue to grow larger, office and lab hours become crowded. Traditionally, students raise their hand or add their name to a whiteboard list to get assistance from course staff. In these settings, course staff may find themselves repeatedly answering the same or similar questions. Students may wait for long periods before getting help from an instructor. Shy students may be hesitant to ask for help or be overpowered by more aggressive personalities. While some office hours are crowded, others have very few students coming in, and rarely do we capture any analytics on utilization or usefulness of these one-to-one interactions with students.
To facilitate office hours in large courses, we have previously described the development of an online queuing software for educational use. While the tool was initially developed for office hours in large enrollment courses, the Queue has been adopted in several additional use cases including advising, peer learning, and active learning. In these early adoption cases, we have identified benefits of implementing the Queue in educational settings, including saving time for students and instructors and expanding learning environments beyond classrooms and faculty offices. Further, the Queue can collect rich data that can help instructors identify common questions or “muddiest points”. Instructors can use this data to assess course delivery, content, and performance of course staff. Overall, these benefits and features of the Queue provide educators with an easy-to-use tool for working with large student numbers. Here we present our findings from combining user surveys and interviews to present the use of the Queue in diverse educational settings.
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