The RA/TA/LA Matching Web Application aims to automate the complex process of assigning graduate students to Research Assistant (RA), Teaching Assistant (TA), and Learning Assistant (LA) positions within the Department of Computer Science.
DescriptionEach semester, a small team of faculty members is tasked with the challenging job of matching graduate students with various positions, including Research Assistant (RA), Teaching Assistant (TA), and Learning Assistant (LA) roles. This matching process is critical to the functioning of the Department of Computer Science, as these positions play a significant role in supporting both research initiatives and instructional activities.
The complexity of this task is particularly pronounced at the beginning of the fall semester, when the volume of candidates and available positions reaches its peak. There may be as many as 50 to 60 graduate students seeking employment opportunities, alongside 20 to 30 research projects that require dedicated RAs to assist with their development and execution. Additionally, around 100 LA positions must be filled to ensure that undergraduate courses are adequately supported.
Each of these roles has its own unique requirements and expectations, leading to a multifaceted matching scenario. For instance, RAs often need specific skills or backgrounds to contribute effectively to particular research projects, while TAs and LAs may be selected based on their familiarity with the course material and prior experience. The matching process is further complicated by a variety of constraints and preferences—such as scheduling conflicts, funding guarantees for certain students, and instructors' specific needs for their courses.
Given the intricate nature of this matching process, relying on manual methods becomes inefficient and prone to errors. Faculty members often find themselves overwhelmed with administrative tasks, consuming valuable time and resources that could otherwise be directed toward teaching and research. As a result, there is a pressing need for an automated solution that can streamline the matching process, improve accuracy, and ultimately enhance the overall experience for both students and faculty.
Task Details:- Matching Graduate Students with RA Positions: Prioritize assigning graduate students to RA roles based on their qualifications and project requirements.
- Assigning TAs: For those who do not secure an RA position, the tool will flag them, and they will be handed off to the XL Labs tool to secure their position.
The application will feature a straightforward interface allowing users to specify constraints and preferences easily. At minimum, a text file or spreadsheet input will be sufficient. If time and resources allow, a more user-friendly data entry interface will be developed, potentially integrating with existing systems in the XL lab for user input.
PlatformThe tool will be a web-based application, enabling access from various devices. Ideally, it will support integration with Google Sheets for data input, facilitating real-time updates and easy collaboration among users.