This present describes the results of the evaluation regarding the self-perception of personal and social attitudes acquired by university students from an engineer-ing faculty at a state university in Peru, in the context of virtual teaching and learning, declared by the health emergency by COVID-19; For which the follow-ing objectives were proposed, to determine the variation or impact that the self-perception of personal and social attitudes experienced, having as reference sce-narios, the academic semester with face-to-face teaching (academic semester 2019B) and then the academic semester developed totally virtual (2020A). An exploratory-descriptive research level was used, with a longitudinal non-experimental design, whose population and sample is made up of 674 and 761 students, in the 2019B and 2020A semesters respectively. The data collection in-struments were validated through Cronbach's Alpha, whose average results per academic semester were 0.960 and 0.958. After the investigation, it was found that there is no negative impact, due to virtual teaching; On the contrary, on aver-age, there was an increase in all levels of satisfaction, increasing the level very satisfied by 52.8% and the level satisfied by 3.25%.

In this competitive scenario of the educational system, higher education institutions use intelligent learning tools and techniques to predict the factors of student academic performance. Given this, the article aims to determine the supervised learning model for the predictive system of personal and social attitudes of university students of professional engineering careers. For this, the Machine Learning Classification Learner technique is used by means of the Matlab R2021a software. The results reflect a predictive system capable of classifying the four satisfaction classes (1: dissatisfied, 2: not very satisfied, 3: satisfied and 4: very satisfied) with an accuracy of 91.96%, a precision of 79.09%, a Sensitivity of 75.66% and a Specificity of 92.09%, regarding the students' perception of their personal and social attitudes. As a result, the higher institution will be able to take measures to monitor and correct the strengths and weaknesses of each variable related to satisfaction with the quality of the educational service.

<span>Today, when industry 4.0 is already being talked about, and its advantages at the organizational level, there are still industrial processes that show a lack of automatic regulation mechanisms, which means that an optimal operating process is not guaranteed, nor that monitoring and supervision capacity. In this sense, the purpose of the article is to demonstrate the feasibility of the integration between the programmable logic controller and the Arduino nanocontrollers, this as an alternative to automate a concentric tube heat exchanger, for monitoring and data acquisition through a supervision, control and data acquisition system. The integration is shown through the design and implementation of a temperature transducer made up of a MAX6675 converter module and an Arduino Nano controller, which is amplified through its pulse width modulation (PWM) interface and the integrated TL081CP and coupled to the analog inputs of the automaton. As a result of the experimental tests, it was possible to determine that the flow rate of the automated system is directly proportional to the drop or difference in temperature in the hot fluid and inversely proportional to the increase in temperature in the cold fluid, verifying the effectiveness of the automated heat exchanger.</span>

Research training promotes the development of students' research skills and competences. For this reason, the study focuses on analyzing the self-perception of the acquisition of research competences of mechanical and electrical engineering students at the National Technological University of Lima Sur, located in Peru. The purpose of determining these results is to generate a research culture in the university context, by means of policies, strategies and knowledge management mechanisms supported by the use of information and communication technologies (ICT). The research will be carried out in the year 2022, and from the methodological point of view it is descriptive and non-experimental design of transversal type. A questionnaire was designed for data collection, consisting of 12 indicators; the reliability of the data collected was assessed using Cronbach's alpha, whose value was 0.817. As there is no research training from the initial level of the curriculum plan that is aimed at enhancing the scientific and technological capabilities of the student, the results reveal that 72% failed to complete the development of scientific articles. With regard to the difficulties and/or weaknesses identified, they are centred on the low level of knowledge of quantitative or qualitative research, the concepts of techniques and instruments for data collection and discussion of results.