Role: Project Manager

Fall 2015 - Carnegie Mellon University

Project Summary

QUEUEPLUS was the name of the product developed out of the final group project for my User Centered Research and Evaluation course taken at Carnegie Mellon University during the Fall 2014 semester. Within this project, we were tasked to improve the process in which students recieve help from teaching assistants when visiting their office hours.

Our final solution
Contextual Inquiries

Each team member spent one hour with a student in a specific intro to programming course at Carnegie Mellon University when they attended the office hours of the course's teaching assistants. Our intial findings highlighted several issues, mainly that most students never actually receive help, and must wait in a noisy lab room constantly watching the queue for when it is their turn. Additionally, the TAs are working for 3 hours straight, and become overworked.

Affinity Diagram

Within 48 hours after our contextual inquries, our team met up and synthesized our notes to create individual note suitable for use in creating an affinity diagram.

Sequence Models

Utilizing our consolidated notes from our contextual inquiries, sequence models were created to show the processes followed for various tasks by the students we monitored. When we found the same task was completed by multiple students, we created consolidated sequence models to illustrate this.

Flow Models

We also used our consolidated notes to create flow models to represent the flow of information and represent breakdowns. Once again, we we found similarities between students, we created consolidated flow models.


Based off of our consolidated notes, our affinity diagram, consolidated flow models, and consolidated sequence models, we created six visions of possible solutions. We then narrowed those six visions down two three, which possible solutions to explore futher.

Final Solution

Our solution was to try and minimize the overall number of students in the queue, and minimize the time that students are waiting in the queue. To minimize the queue, we proposed splitting it into two options. One for students with more conceptual problems, where multiple students can be helped at once, and one for students who need 1 on 1 help with their specific coding questions. To do so, we’re suggested the creation of a web application which will help create these 2 different lab hours options, automatically manage the queue for TAs, and notify students when it is their turn to get help.

For the first option, students sign up 24 hours in advance on topics they have questions about. TAs can in turn prepare mini lectures based on topic popularity. The schedule of mini lectures would be available to all students, allowing for multiple student questions to be answered at once, and in turn shortening the overall queue times. Nearby students would get a notification when a mini lecture is about to start through the app.

For the students who have more specific questions, they could still attend office hours for individual one on one time. Since many of the students would now be attending the mini-lectures, the length of this queue is now shortened. With the web application, students could now leave the lab room, and are no longer forced to wait in a noisy lab room while waiting to get help. The application would notify the student when they are third in the queue, second, and then first, telling them to get back to the lab room. For the 1-on-1s, the TA would have their own individual room to minimize distractions.

Problems & Risks
  • Need more office hours space
  • More prep work for TA
  • Potential higher preference for 1-1 help
  • Disruption of walk-ins to mini-lectures
  • Need to develop the software
Benefits of our solution
  • Better conceptual understanding > more focused questions > more efficient help time > more students helped.
  • Less idle time for student
  • Better chance at talking to a TA
  • Student-TA interaction is away from noisy lab room
  • TAs only have to focus on helping students
  • Various avenues of help: Walk-ins Available
  • Provides class instructor with data about topics the students are having difficulty with
The Team

My team was made up of 5 Masters Students in the Human Computer Interaction program at Carnegie Mellon University. Along with myself, the team included Joyce Liu, Cindy Saroha, Leticia Patricio, and Danita Delce.