Proposal of a remote education model with the integration of an ICT architecture to improve learning management

A computer architecture based on disruptive information technologies for drug management in hospitals

The drug management currently carried out in hospitals is inadequate due to several factors, such as processes carried out manually, the lack of visibility of the hospital supply chain, the lack of standardized identification of medicines, inefficient stock management, an inability to follow the traceability of medicines, and poor data exploitation. Disruptive information technologies could be used to develop and implement a drug management system in hospitals that is innovative in all its phases and allows these problems to be overcome. However, there are no examples in the literature that show how these technologies can be used and combined for efficient drug management in hospitals. To help solve this research gap in the literature, this article proposes a computer architecture for the whole drug management process in hospitals that uses and combines different disruptive computer technologies such as blockchain, radio frequency identification (RFID), quick response code (QR), Internet of Things (IoT), artificial intelligence and big data, for data capture, data storage and data exploitation throughout the whole drug management process, from the moment the drug enters the hospital until it is dispensed and eliminated.

Data Analysis Model for the Evaluation of the Factors That Influence the Teaching of University Students

Currently, the effects of the pandemic caused by the Coronavirus disease discovered in 2019 are the subject of numerous studies by experts in labor, psychological issues, educational issues, etc. The universities, for their continuity, have implemented various technological tools for the development of their activities, such as videoconference platforms, learning management systems, etc. This experience has led the educational sector to propose new educational models, such as hybrid education, that focus on the use of information technologies. To carry out its implementation, it is necessary to identify the adaptability of students to a technological environment and what the factors are that influence learning. To do this, this article proposes a data analysis framework that identifies the factors and variables of a hybrid teaching environment. The results obtained allow us to determine the level of influence of educational factors that affect learning by applying data analysis algorithms to profile students through a classification based on their characteristics and improve learning methodologies in these educational models. The updating of educational systems requires a flexible process that is aligned with the needs of the students. With this analysis framework, it is possible to create an educational environment focused on students and allows for efficient change with the granular analysis of the state of the learning.

Assistance System for the Teaching of Natural Numbers to Preschool Children with the Use of Artificial Intelligence Algorithms

This research was aimed at designing an image recognition system that can help increase children’s interest in learning natural numbers between 0 and 9. The research method used was qualitative descriptive, observing early childhood learning in a face-to-face education model, especially in the learning of numbers, with additional data from literature studies. For the development of the system, the cascade method was used, consisting of three stages: identification of the population, design of the artificial intelligence architecture, and implementation of the recognition system. The method of the system sought to replicate a mechanic that simulates a game, whereby the child trains the artificial intelligence algorithm such that it recognizes the numbers that the child draws on a blackboard. The system is expected to help increase the ability of children in their interest to learn numbers and identify the meaning of quantities to help improve teaching success with a fun and engaging teaching method for children. The implementation of learning in this system is expected to make it easier for children to learn to write, read, and conceive the quantities of numbers, in addition to exploring their potential, creativity, and interest in learning, with the use of technologies.

Proposal for the Analysis of the State of Learning in University Students with the Inclusion of ICT in the Classroom

The inclusion of information and communication technologies in education has become a priority for all universities. To meet this need, there are several research works that have dealt with the subject for several decades. However, for its inclusion, the analysis of each institution is necessary since the needs of the university population and the resources for its application change according to each situation. This work seeks to create a method that allows establishing the needs and doubts of students about the use of educational technologies in the classroom without affecting their performance. For this, a process has been designed that identifies learning needs, through the validation of data obtained from surveys and the monitoring of the academic efficiency and learning of a cohort of students. The follow-up includes a period of four years from 2019 to 2022. This follow-up allowed establishing three different realities, in 2019 the academic data was analyzed in a face-to-face education model, from 2020 to 2021 the follow-up was included in a remote model with the use of technologies as a communication channel and in 2022 these were included as a learning component, which marked an in-depth analysis of student performance and how technology affected their learning.

Identification of the Consequences of COVID-19 through the Analysis of Data Obtained in Surveys of a Specific Population

The pandemic caused by the 2019 coronavirus disease has marked a total change in the development of society. Since then, its effects have been visible in people, both in work, education and psychological areas. There are many jobs and organizations that have set out to identify the reality of people after the pandemic and how the pandemic has affected their daily lives. To do this, countries have organized data and statistics collection campaigns that allow investigating the new needs of people. With this, instruments such as surveys have become more relevant and valid to know what these needs are. However, the analysis processes must guarantee answers that are able to determine the direct impact that each question has on people’s feelings. This work proposes a framework to determine the incidence values of surveys based on their categories and questions and how they capture the reality of people in areas such as education, the impact of work, family and the stress generated by the pandemic. With the results obtained, each element and category that the population considers a consequence of COVID-19 that affects the normal development of life has been identified.