Hernán Díaz

Relationship between the Ergonomic State of the Classroom Measured in Energy Units and the Well-being of Students Observed by Non-invasive Instrumentation

Abstract This work aims to measure the ergonomic level of a classroom by means of the quantification of two readily measurable variables. The central hypothesis is that the greater the ergonomic level of the classroom, the higher the well-being of the students and, consequently, the less of total environmental adjustments that must be done to achieve a comfortable situation. Previous research put forward that when human beings are faced with non-pleasing environments, immediately emerges a state of restlessness, which is behaviorally manifested by postural changes and surrounding observation assessing both the sources of discomfort and the potential resources to avoid them. This fact is mainly attested by the movements of the head, the part of the body that concentrates all the sensory system, and the rest of the body. Regarding that the well-being experienced by a student in a specific learning environment is reflected in the body of the individual, we choose to measure these movements as a proxy variable of the ergonomic level of the classroom. A second variable can be measured during the first few minutes of the class by recording the distance displacement of objects and the modification of other aspects of the classroom made by the students to get a better condition to be in it. We choose the net amount of energy required to do these changes as another proxy variable to estimate the ergonomics of the classroom. This second variable is measured once the students are free to make adjustments in the classroom quantifying the energy used for this purpose. These observations are plotted on a Cartesian plane revealing a clear correlation between energy and movements, confirming that both variables are quantitative indicators of the ergonomic state of the classroom, the main artificial ecosystem of learning.

Study of the achievement of university students and their relationship with the selection process.

Abstract This paper explores the performance of students from four university careers of scientific orientation, per the qualifications and the effective progress achieved in their corresponding curricula, as well as their relationship with the variables of the admission process and the subsequent performance. Under the assumption that grades are less representative than the progress achieved by the student, the returns are measured mainly in terms of the progress achieved by the student in his / her respective curriculum. The analysis was approached by means of the application of the test of equality of average and the coefficient of correlation of Pearson, in subgroups of students formed per their condition of novices or previous experience in the university, its career and its type of school of origin. The results show little connection between the variables of the selection process and the academic performance, as well as a poor relationship between the indicators related to the secondary education grades and the performance of the students in their respective careers. Finally, a particular conceptual approach for the solution based on neuro-management considerations as a model to conceptually aboard complex dynamic routines that need to be redirected.

Model for the organization, storage and processing of large data banks of physiological variables

The proliferation and popularization of new instruments for measuring different types of electrophysiological variables, has generated the need to store huge volumes of information, corresponding to the records obtained by applying this instruments on experimental subjects. Together with this must be added the data derived from the analysis and purification processes. Moreover, several stages involved in the processing of data, is associated with one or more specific methods related to the area of research and to the treatment at which the base information (RAW) is subjected. As a result of this and with the passage of time, various problems occur, which are the most obvious consequence of that data and metadata derived from the treatment processes and analysis, and can end up accumulating and requiring more storage space than the base data. In addition, the enormous amount of information, as it increases over time, can lead to the loss of the link between the processed data, the methods of treatment used, and the analysis performed, so that eventually all becomes simply a huge repository of biometric data, devoid of meaning and sense. Current approaches around the concept of big data, while take over the storage and other aspects such as information search mechanisms, are far from incorporating metadata about the neurophysiological and emotional records. This type of information requires the construction of chronologies of events, including the methods of processing and analysis. In addition, it is required to maintain an adequate link between those responsible for the data (those who recorded and analyzed) and subjects that are under investigation, without breaking confidentiality to which they are entitled. This paper presents an approach founded in a data model that can adequately handle different types of chronologies of physiological and emotional information, ensuring confidentiality of information according to the experimental protocols and relevant ethical requirements, linking the information with the methods of treatment used and the technical and scientific documents derived from the analysis. Because the information coming from the original data will be associated with the methods of treatment to which they were subjected and with the results stored permanently, it is not necessary to repeat analysis with equivalent requirements, ensuring a better use of CPU and memory computer resources. Consequently, the need to generate specific data model is justified by the fact that the tools currently associated with the storage of large volumes of information are not able to take care of the semantic elements that make up the metadata and information relating to the analysis of base records of physiological information.