Asee peer logo

Measuring Impact: Student and Instructor Experience Using an Online Queue

Download Paper |

Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

New Engineering Educators 4: Tips and Tools

Tagged Division

New Engineering Educators

Page Count

10

DOI

10.18260/1-2--34961

Permanent URL

https://peer.asee.org/34961

Download Count

168

Request a correction

Paper Authors

biography

David Mussulman University of Illinois at Urbana-Champaign

visit author page

Dave is an Instructional Technology Facilitator with the University of Illinois at Urbana-Champaign's Engineering IT Shared Services. He helps instructors select and integrate technologies into their courses to enhance student learning and improve course administration.

visit author page

biography

Karin Jensen University of Illinois at Urbana-Champaign Orcid 16x16 orcid.org/0000-0001-9456-5042

visit author page

Karin Jensen, Ph.D. is a Teaching Assistant Professor in bioengineering at the University of Illinois at Urbana-Champaign. Her research interests include student mental health and wellness, engineering student career pathways, and engagement of engineering faculty in engineering education research. She was awarded a CAREER award from the National Science Foundation for her research on undergraduate mental health in engineering programs. Before joining UIUC she completed a post-doctoral fellowship at Sanofi Oncology in Cambridge, MA. She earned a bachelor's degree in biological engineering from Cornell University and a Ph.D. in biomedical engineering from the University of Virginia.

visit author page

biography

Jennifer R. Amos University of Illinois at Urbana-Champaign

visit author page

Dr Amos joined the Bioengineering Department at the University of Illinois in 2009 and is currently a Teaching Associate Professor in Bioengineering and an Adjunct Associate Professor in Educational Psychology. She received her B.S. in Chemical Engineering at Texas Tech and Ph.D. in Chemical Engineering from University of South Carolina. She completed a Fulbright Program at Ecole Centrale de Lille in France to benchmark and help create a new hybrid masters program combining medicine and engineering and also has led multiple curricular initiative in Bioengineering and the College of Engineering on several NSF funded projects.

visit author page

biography

Lawrence Angrave University of Illinois at Urbana-Champaign Orcid 16x16 orcid.org/0000-0001-9762-7181

visit author page

Lawrence Angrave is an award winning Fellow and Teaching Professor at the department of computer science at the University of Illinois at Urbana-Champaign (UIUC). His interests include (but are not limited to) joyful teaching, empirically-sound educational research, campus and online courses, computer science, engaging underrepresented students, improving accessibility and creating novel methods that encourage new learning opportunities and foster vibrant learning communities.

visit author page

biography

Karle Flanagan University of Illinois at Urbana-Champaign

visit author page

Karle Flanagan is a Senior Instructor of Statistics at the University of Illinois at Urbana-Champaign. She has taught introductory statistics to thousands of students at UIUC since Spring of 2014. She also serves as the MS advisor for the statistics department. In 2018, she was awarded the Illinois Student Government’s Teaching Excellence Award and in February of 2019, she also won the highest level teaching award at UIUC, the Campus Award for Excellence in Undergraduate Teaching. She completed her undergraduate degree in mathematics, with a minor in secondary education. She previously has taught mathematics and worked as a statistician in the insurance industry. Along with teaching, she is currently working on course development for other advanced statistics courses and data science courses using Python. Her research interests include online education, optimizing efficiency in office hours for large classes, and active learning methods for undergraduate statistics instruction.

visit author page

biography

Wade Fagen-Ulmschneider University of Illinois at Urbana-Champaign Orcid 16x16 orcid.org/0000-0002-7313-7708

visit author page

Wade Fagen-Ulmschneider is a Teaching Associate Professor of Computer Science at the University of Illinois at Urbana-Champaign (UIUC). With a passion for data, he teaches thousands of students each year in his courses on Data Structures, Data Visualization, and Data Science. He was selected as one of the National Academy of Engineering’s Frontiers of Engineering Education scholars, awarded the Collins Award for Innovation Teaching, and has been consistently ranked as an excellent instructor by his students for the past ten years. His work on data visualizations has been used by governors of multiple states, featured by websites including Popular Mechanics and The Verge, and has been viewed by millions of readers.

visit author page

biography

Natalia Ozymko University of Illinois at Urbana-Champaign

visit author page

Natalia Ozymko is a rising senior majoring in Computer Science with a minor in Spanish at the University of Illinois at Urbana-Champaign (UIUC). She is interested in helping students master advanced topics in Computer Science and building new technologies to improve people’s lives. She was awarded the Scott Fisher Outstanding Course Assistant award, and has worked under the direction of multiple faculty members assisting in teaching both Data Structures and Systems Programming.

visit author page

biography

Rittika Adhikari University of Illinois at Urbana-Champaign

visit author page

I am a junior studying CS at the University of Illinois at Urbana-Champaign, and I have worked on implementing features to continue improving the Queue.

visit author page

biography

Jacqueline Osborn University of Illinois at Urbana-Champaign

visit author page

Jacqueline is an undergraduate at the University of Illinois at Urbana-Champaign studying Computer Science. She is a Lead Course Assistant for CS 225 (Data Structures), and was selected as one of the Fall 2019 Outstanding Course Assistants within her department.

visit author page

Download Paper |

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.

Mussulman, D., & Jensen, K., & Amos, J. R., & Angrave, L., & Flanagan, K., & Fagen-Ulmschneider, W., & Ozymko, N., & Adhikari, R., & Osborn, J. (2020, June), Measuring Impact: Student and Instructor Experience Using an Online Queue Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34961

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2020 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015