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Wade Fagen-Ulmschneider

Wade Fagen-Ulmschneider

· Teaching ProfessorVerified

University of Illinois Urbana-Champaign · Computer Science

Active 2019–2024

h-index1
Citations7
Papers76 last 5y
Funding
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Research topics

  • Computer Science
  • Multimedia
  • Psychology
  • Mechanical engineering
  • Aerospace engineering
  • Data science
  • Computer network
  • Engineering
  • Medical education
  • Mathematics education
  • World Wide Web
  • Medicine
  • Operating system

Selected publications

  • Adoption of an Online Queue App for Higher Education: A Case Study

    2020 · 1 citations

    Senior authorCorresponding
    • Computer Science
    • Computer Science
    • Medical education

    Abstract 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.

  • Work in Progress: Analysis of the Impact of Office Hours on Graded Course Assessments

    2020 ASEE Virtual Annual Conference Content Access Proceedings · 2020 · 2 citations

    • Computer Science
    • Computer Science
    • Engineering

    degree in mathematics, with a minor in

  • Measuring Impact: Student and Instructor Experience Using an Online Queue

    2020 ASEE Virtual Annual Conference Content Access Proceedings · 2020 · 2 citations

    • Computer Science
    • Computer Science
    • Multimedia

    Abstract This paper presents the results of surveys of students, educators, and advisors who used a custom online queuing system in diverse educational settings. Prior work identified that using technology such as a mobile-friendly, web-based queue has benefits to scaling student/educator interactions. The current study was developed to collect student, instructor, and advisor feedback to understand best practices, challenges, and perceptions from using the online queuing system for office hours, active learning, and advising. There is an increasing need to facilitate quality instruction in large enrollment courses. Towards addressing this need, we have previously described the development and early use of an online queue system for education (BLINDED). The Queue is an open-source application that allows students to add their name and a question or topic to an online queue that is monitored by course staff or advisors. Students can access the Queue web page with a cell phone, tablet, laptop, or any other computing device. Both students and course staff can view which students are in the queue and what questions they have. While the Queue software was originally developed for use in office hours of large enrollment courses, the software has since been adopted for other educational purposes, including, drop-in advising, peer learning, and active learning (BLINDED). Since its implementation in Fall 2017, the Queue has been adopted by 20 courses, 3 advising offices, and has facilitated over 50,000 questions from over 6,000 different students. In the early use cases of the Queue, we have identified several benefits for students and instructors, including but not limited to saved time, improved accessibility, and improved use of space since office hours are not set to a fixed location that may or may not accommodate demand. Student surveys will validate those benefits and add new personal insights into how the Queue enhances their interactions and success in courses. Surveys will collect data on student preferences when using the Queue to inform development features (e.g., I would prefer to be anonymous on the Queue) as well as assessing students perceptions about learning material (e.g., The Queue helped me toward mastering material in the course). Further, student surveys will assess whether the Queue facilitates student-instructor interactions (e.g., I am more likely to approach course or office staff using a digital queue). Student feedback on additional software features will also be solicited. Queue adopter surveys (administered to faculty, advisors, and staff who use the system) will assess ease of implementation (e.g., The Queue was easy to implement in my course/office) as well as solicit general feedback on features and data collection.

Frequent coauthors

Education

  • PhD, Computer Science

    University of Illinois at Urbana-Champaign

    2013

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