No abstract

The relevance of digital technology to fight isolation, distribute preventive measures and assist economic systems began to build as early as the installation of the first health measures for covid 19. This study's goal is to analyze Latin America's ability to fulfill this challenge. The following are the conclusions: Latin America's digital ecosystem is at an intermediate degree of development, allowing it to somewhat alleviate the consequences of the epidemic. Also, the rural/urban contrast shows a significant amount of digital marginalization. The digital divide prevents key segments of the population from receiving health information, downloading instructional resources to improve school performance, or purchasing things online. The digital gap is compounded by the fact that most Latin American homes only use the internet for communication and social networking. A home digital resilience index (calculated on the use of the Internet to download health apps, educational apps, perform e-commerce operations and use fintech). It also suggests a lack of technology adoption, but rather a lack of technological integration in manufacturing processes, notably supply networks. The share of the workforce that can telework adds to the labor market disruption in COVID-19.

In the digital technology environment, business enterprises are focusing in enhancing the precision on marketing efforts so as to remain more competitive and enhance profit margins. The application of Machine Learning, Deep Learning, Data analytics in supply chain management (SCM) is getting more popular due to the growing consumer demand and organisation are identifying various ways in order to lower the cost of transportation of goods from one location to another. Through the enhancement in theology across SCM process, the data is highly critical for analysing the location and movement of the networks so as to reduce the overall cost involvement in the goods and services. The supply chain process is highly interconnected through physical flow of goods from raw materials to finished goods, hence there are more volume of data and financial flow across the supply chain. Therefore, it is highly important in analysing the increasing complexity in supply chain and also to understand the implementation of ML in enhancing the SCM process for sustainable development and growth among the various companies. The study is an empirical investigation on the key factors influencing the design and implementation of ML in the SCM process by major companies located in India for achieving sustainable development. A total of 132 respondents were chosen and closed ended questionnaire were distributed to them, based on the data collected the researchers performed detailed statistical analysis like Correlation analysis, Multiple regression analysis using SPSS package.

Over the last few decades, there has been a gradual deterioration in higher education in all three areas: the academic setting (both staff and students), as well as research and development output (including graduates). All colleges and universities are essentially focused on improving management decision-making and educating pupils. High-quality higher education can be obtained through a variety of methods. One method is to accurately forecast pupils’ achievement in their chosen educational context. There are numerous prediction models from which to pick. While it is unclear whether there are any markers that can predict whether a kid will be an academic genius, a dropout, or an average performer, the researcher reports student achievement. This article presents a metaheuristics and machine learning-based method for the classification and prediction of student performance. Firstly, features are selected using a relief algorithm. Machine learning classifiers such as BPNN, RF, and NB are used to classify student academic performance data. BPNN is having better accuracy for classification and prediction of student academic performance.

Son numerosos los trabajos que señalan al aula invertida (flipped classroom) como una metodología de clase que aporta beneficios en el proceso de enseñanza-aprendizaje, sobre todo relacionados con la motivación y satisfacción del alumno. Este artículo presenta la planificación y la aplicación del modelo pedagógico “Flipped Classroom” para la enseñanza-aprendizaje en el curso de métodos numéricos. Durante la investigación se realizaron videos tutoriales sobre los contenidos del curso, los cuales fueron elaborados previamente para luego ser presentados a los estudiantes de la Escuela Profesional de Ingeniería Civil de la Universidad Nacional Santiago Antúnez de Mayolo que cursaban la asignatura de Métodos Numéricos. Se analizó la valoración del alumnado y el posible impacto de esta metodología en la calificación de los estudiantes. Los resultados obtenidos, expresan que los alumnos consideran la Clase Invertida como una metodología más divertida y motivadora que la clase tradicional; además, se observa una diferencia en las calificaciones obtenidas por los estudiantes que aprendieron con la metodología de aula invertida y con aquellos que lo hicieron mediante una metodología tradicional.