Technological tools for virtual teaching and their effect on the satisfaction of online learning

The objective of the research is to analyze the satisfaction of the online learning of the applied electricity subject, when implementing technological tools for virtual teaching. The development of the research determines a high level of student satisfaction, finding the perception of reliability with 93.05%, that of security with 93.2%, that of answer’s capacity with 90.73% and empathy with 82.87%. Satisfaction with the technological tools of virtual teaching is related to the adequate and accessible use of simulation software during online learning, which allowed compliance with the syllable. In addition to the security and confidence when the teacher is willing to help him in the use of the simulation software, responding to it appropriately and quickly. Satisfaction of online learning of the applied electricity subject using virtual teaching tools is related to the teacher's sample of concern towards students regarding their academic needs and their expressed interests

Failure rate in university students: analysis of its variation in the transition from face-to-face education to virtual education

The article presents an exploratory and descriptive study of the failure rate of students of the professional school of mechanical and electrical engineering of a public university in Peru. The purpose is to identify if the level of failure has experienced any positive or negative variation when moving from the context of face-to-face education to virtual education, due to the state of health emergency. This study makes it possible to demonstrate an initial reference state, relevant for decision-making at the level of university academic management, through strategies that will increase the approval rate of this professional school. The results obtained indicate that the level of failure of the students has experienced a positive variation when moving from the face-to-face context to the virtual one, due to the increase in the average rate of failure from 25% to 34%. The results are equivalent to 242 students failed during the context of face-to-face education, and 438 students failed during the context of virtual education. In addition, it is visualized that the specialty subjects, where there are the largest number of failed students, are linked to the area of electrical engineering. Being the subject of Electrical Machines I, the one with the highest failure rate, with a total average of 43% during the context of face-to-face education and 48% during virtual education.Campus Lima Nort

Academic performance before and during the state of emergency due to COVID-19: analysis from the perspective of distance education

Faced with Covid-19, and the need to adapt to environments that guarantee continuity of educational service in the context of social distancing, many universities did not initially plan the mechanisms for adapting to the virtual modality adequately. Therefore, this period of transition to e-learning was characterised by a decrease in academic performance . This article reports on a study that focused on determining whether the transition from a classroom to a virtual teaching–learning model had an effect or influence on the academic performance of university students in mechanical and electrical engineering at a public university in Peru during the period 2018 to 2021. The purpose of the study was to ensure the quality of the education system in the face of the implementation of a hybrid mode of teaching. Methodologically, a descriptive type of investigation and longitudinal non-experimental design were undertaken. The research methodology followed a hypothetical-deductive approach. The number of participants was 157 and a registration form was used to collect data on the indicators that made up the academic performance variable. The results reveal that the switch to a virtual teaching–learning modality significantly influenced the academic performance of the students. Student’s t-test found a significance equal to 0.000. Passing grades were achieved by 98.57% of students under the virtual teaching–learning modality, compared to 68.4% under classroom learning.Campus Lima Nort

Digital competence in scientific research in higher education

Background: Due to the current contingency due to covid 19, students and teachers have had to face new digital challenges in such a way that they seek to become aware of how important digital skills are for the learning process. However, it is evident that, in Peru, there is a digital divide due to inequality; therefore, there is no good university service due to the lack of Internet access in rural areas. The digital skills of university students allow the production of new knowledge and technological innovation from the development of digital skills. Objective: The general objective of the research was to identify the country with the most scientific production through a bibliometric and bibliographic review, to search for the production of research works on the construct of digital competence in scientific research in higher education during the period 2016- 2021. Methodology: The research was developed under a qualitative approach based on a documentary review of the studies carried out in the period 2016-2021 in Latin American countries of the digital competence variable, 44 articles registered in the Scopus database were identified

Supervised Learning through Classification Learner Techniques for the Predictive System of Personal and Social Attitudes of Engineering Students

—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