Influencia del software GeoGebra en el aprendizaje de la geometría en estudiantes de cuarto grado de secundaria en el distrito de Tambopata de la región de Madre de Dios

The objective of this research has been to determine the influence of GeoGebra software on the learning of geometry in fourth grade students of secondary education at the Señor de los Milagros educational institution. The research problem was the presence of the low level of student learning in mathematics courses, especially in geometry. The study is quasi-experimental and the sample was 67 students divided into two groups. Both groups were evaluated with a geometry learning assessment test that was applied after the intervention. The results were finally discussed. The use of GeoGebra software significantly improved the learning of geometry in fourth grade high school students. Where the students of the experimental and control group obtained an average score of 13.3611 and 8.9354 points respectively, giving the difference of 4.4257 points in favor of the experimental group.El objetivo de la investigación que se reporta en esta comunicación ha sido determinar la influencia del software GeoGebra en el aprendizaje de la geometría en estudiantes de cuarto grado de educación secundaria de la institución educativa Señor de los Milagros. El problema que motivó la investigación y una intervención didáctica fue el bajo nivel de aprendizaje de los estudiantes en los cursos de matemática, en especial en geometría. El estudio es cuasi experimental con una muestra de 67 estudiantes, distribuidos en dos grupos, que fueron evaluados con una prueba de evaluación del aprendizaje en geometría aplicada después de la intervención. Los resultados muestran que la intervención didáctica basada en el empleo del software GeoGebra, mejoró significativamente

Public Services in the Household and Their Effect on Poverty, Analysis for the Peruvian Case, 2021

The objective of the research was to determine the effect of public services in the household on poverty in Peru, in the period 2021, for which a quantitative, non-experimental research approach was considered with a descriptive and correlational design. The information from the National Household Survey of the National Institute of Statistics and Informatics (INEI) database was used, considering the modules “Dwelling and Household Characteristics”, “Household Members’ Characteristics”, “Education”, “Employment and Income”, “Household Equipment”, “Summaries (Calculated Variables)” and “Citizen Participation”. It was possible to determine that the following variables had negative effects on household poverty in Peru: access to potable water, sanitation, electric power, cell phone services; achieving higher, secondary, and primary education levels; having a washing machine, motorcycle, tricycle, motorcycle taxi, computer, kitchen, refrigerator in the household; having a property title; being part of an association or organization; living in a rural residence area; and having remittances. However, the number of household members had a positive effect on poverty. Therefore, it was concluded that access to public services in the household contributed to reducing the probability of being poor in Peru

Social Factors Associated with Poverty in Households in Peru

The objective of the research was to identify the determinants of poverty at the household level in Peru in 2020. The research design was descriptive and correlational, with a type of non-experimental research and quantitative approach, and considered the logit econometric model; the sources of information used correspond to the National Household Survey of the National Institute of Statistics and Informatics, from which the variables that are considered determinants of poverty were extracted and managed. It was determined that the size of the household positively influences by 1.3%; the economic income of the head of household negatively influences by 0.000828%; the years of education of the head of household influences by 0.1%; homeownership influences by 0.9%; access to social programs of food and non-food aid influence by 0.9% and 0.6%, respectively; access to drinking water service, hygienic service and electric power service have a negative influence of 1.8%, 0.6% and 1.7%; all these factors are associated with the poverty of households in Peru. Therefore, the social determinants of poverty were household size, economic income, years of education, access to homeownership, access to a social food aid program, access to a social non-food aid program, access to drinking water services, access to hygienic services and access to electric power services

Determinants of financial inclusion in households in Peru

The issue of financial inclusion considers access to and use of quality financial services by household members and different types of companies around the world, allowing us to reach the opportunities that the globalized world offers us. The objective of this research was to identify the socioeconomic factors that determined the inclusion of households in the financial system in Peru in the period of 2021. A quantitative approach was considered, which was non-experimental with a descriptive and correlational design and in which 81,441 pieces of data were obtained from the National Household Survey (ENAHO) of the National Institute of Statistics and Informatics, applying a logit binomial regression. It was determined that 47.02% of households were included in the financial system; 61.93% of those surveyed had their residence in the urban area; on average, respondents had incomplete secondary education; the age of the respondents on average was from 25 to 44 years; the average economic income of the household was less than $251 per month; 72.18% were represented by men as heads of the household and the rest by women; most of the respondents had a cohabiting marital status; the social conditions showed that 23.82% were in the group of being poor; and the majority of households did not have a property title. The determinants of financial inclusion in Peruvian households for 2021 were the area of residence, educational level, age of the respondent, economic income, gender of the respondent, marital status, social status, and property title