How to identify variables that contribute to the organization of personnel in the area of ​​Classroom Services at Universidad de los Andes using the data analysis technique

Abstract

Los Andes University has always been characterized by being at the forefront and having state-of-the-art technology, something that is not very reflected in the Classroom Services department, a unit that provides audiovisual support before, during and after classes. and different events within the university.

In classroom services, the service increased after the return to school, once everything began to normalize after the Covid-2019 pandemic (the university before the covid offered 100 percent face-to-face classes, something that changed drastically, in these new times it is not It is unreasonable that the classes are semi-face-to-face and in turn are recorded for later student reviews.So, the department manages 2 Am and Pm work shifts, with a total of 20 people distributed 10 in AM shift and 10 in PM shift .

Each of these people must ensure that not only the audiovisual resources such as the Video Beam, the microphone or the camera work, but also that the different platforms and the comfort within the Classroom are optimal.

When starting the work, a cleaning of the data was carried out, where the modification of the box had to be carried out. Building where only the name of the building was left without nomenclature, in the box for the days of the week an x ​​had to be added in the empty boxes, the base originally had the month in numbers and it was fixed box by box with its name of the month and in the lower part it is observed as it says YES / NO. As a general objective, it seeks to identify the peak hours in each of the different buildings (Zones), events within the Universidad de los Andes, as specific objectives:

• Identify the different variables that can be generated in order to find the peaks in the classes.
• Obtain a better distribution of personnel in each of the University Buildings.
• Identify the days of the week with the highest and lowest volume of work in the different buildings.
• Identify job volumes in the months
• Search for work volumes in Am and Pm hours