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Based on the specific needs of its technical and administrative staff, the Institute of Mathematics and Computer Science (ICMC) at USP opted for an in-house solution, custom-developed by two of its own students, rather than using off-the-shelf market alternatives. Under the guidance of professor Maristela Oliveira dos Santos, Gabriel Vinicius Bacci (a graduate student in Computer Science and Computational Mathematics) and Gabriel Sanches da Silva (an undergraduate in Applied Mathematics and Scientific Computing) developed computational algorithms to support the selection of teaching assistants for departmental courses and the scheduling of classroom reservations.
For many years, these tasks were carried out manually, requiring time, attention, and the accumulated knowledge of the team. The need for improvements became especially evident in the case of room allocation, when public servant Juliana Merlotti, who had years of experience in the Undergraduate Studies Secretariat, was transferred to the Department Secretariat. “She knew all the rules. Without her, we realized it would take much longer to start everything from scratch, without automation,” recalls Isabela Araújo, administrative analyst at the Undergraduate Studies Service.
In the case of selecting teaching assistants, the starting point was a monitoring scholarship that gave Gabriel Bacci the opportunity to apply the knowledge he had gained in optimization courses throughout his studies. As part of this role, in addition to assisting students with coursework in the mathematical programming class, he also contributed to improving the assistant allocation process, working alongside public servant Giovano de Oliveira Cardozo.
According to professor Maristela, the systems are based on optimization concepts that students typically learn during their undergraduate studies. “Seeing this knowledge move beyond the classroom to solve a real-world problem within the university is extremely meaningful and rewarding for us,” she emphasizes.
Teaching Assistant Selection
The selection of teaching assistants takes place every semester and involves around 60 courses. The challenge lies in reconciling multiple criteria, such as students’ applications, often listing more than one preference, professors’ recommendations, and candidates’ academic transcripts. Manually handling this screening process made it both time-consuming and prone to errors.
With the system developed in Python, everything became simpler. The program automatically reads information from an Excel spreadsheet generated from the responses provided by students through an electronic form and processes the data to indicate the most suitable candidate for each subject, considering both academic performance and professors’ recommendations.
“Furthermore, if there are courses with no interested applicants, the system searches among those not initially selected for candidates who have previously taken similar subjects, and suggests them for the position,” Bacci explains.
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According to Giovano, before the new system was implemented, the task was carried out separately by four departments, each operating on its own timeline, ranging from a few hours to several days. This increased the risk of assigning the same student to multiple courses in different departments. When that happened, the selection process had to be restarted for one of the conflicting courses. With the new system, this risk is eliminated, and the initial selection phase is now faster and more standardized, although each department remains responsible for reviewing the results.
The Coordination of Department Secretariats (C-SEC) has already used the system in the selection process for the current semester, but this required some programming knowledge. The idea is to improve it, creating a more user-friendly interface so that it can be used by anyone, without the need for prior knowledge.
“Any university offers monitoring, and after talking to some colleagues, they were interested in the system, so the idea is to replicate it at other universities as well as at USP,” professor Maristela emphasizes.
By Gabriele Maciel, ICMC Communications Office
English version: Nexus Traduções, edited by Denis Pacheco
