“…e permite a utilização de cinco classes (Jenks, 1967;Costa et al, 2020;Ward et al, 2021). (Dias & Ramos, 2022). As bruscas alterações no processo de ensino e de aprendizagem, provocaram uma quebra em um ciclo ascendente do índice em estudo.…”
Section: Resultsunclassified
“…O número de municípios sem dados do IDEB só é inferior ao ano de 2011 com 16 valores perdidos. O valor máximo do IDEB em 2021, requer investigação, já que a pandemia gerou dificuldades para o ensino, sendo utilizado no periodo recursos digitais que prejudicou o ensino(Dias & Ramos, 2022). 1 -Análises descritivas dos dados de IDEB para os anos de 2005 a 2021.…”
The work presents a study on the Basic Education Development Index (IDEB), which is an educational indicator that relates learning through performance assessments and school flow. The IDEB is calculated with school approval data, obtained from the School Census and also using performance averages that are applied by the National Basic Education Assessment System (SAEB) and Prova Brasil. For carrying out a discussion about the IDEB values in the municipalities of the state of Paraná, a dataset were collected referring to the initial years of municipal elementary education in Paraná, using the average, from the first to the fifth year. For the years 2005 to 2021 the results showed which there are municipalities with higher values. In this period, an effort to improve the values of the IDEB in the schools of the municipalities was identified because a tendency of increment in the analyzed spatial time series. The results indicated that the IDEB appears in the context of school evaluation as a managerial instrument to verify results and used to classify schools and direct resources based on meritocracy.
“…e permite a utilização de cinco classes (Jenks, 1967;Costa et al, 2020;Ward et al, 2021). (Dias & Ramos, 2022). As bruscas alterações no processo de ensino e de aprendizagem, provocaram uma quebra em um ciclo ascendente do índice em estudo.…”
Section: Resultsunclassified
“…O número de municípios sem dados do IDEB só é inferior ao ano de 2011 com 16 valores perdidos. O valor máximo do IDEB em 2021, requer investigação, já que a pandemia gerou dificuldades para o ensino, sendo utilizado no periodo recursos digitais que prejudicou o ensino(Dias & Ramos, 2022). 1 -Análises descritivas dos dados de IDEB para os anos de 2005 a 2021.…”
The work presents a study on the Basic Education Development Index (IDEB), which is an educational indicator that relates learning through performance assessments and school flow. The IDEB is calculated with school approval data, obtained from the School Census and also using performance averages that are applied by the National Basic Education Assessment System (SAEB) and Prova Brasil. For carrying out a discussion about the IDEB values in the municipalities of the state of Paraná, a dataset were collected referring to the initial years of municipal elementary education in Paraná, using the average, from the first to the fifth year. For the years 2005 to 2021 the results showed which there are municipalities with higher values. In this period, an effort to improve the values of the IDEB in the schools of the municipalities was identified because a tendency of increment in the analyzed spatial time series. The results indicated that the IDEB appears in the context of school evaluation as a managerial instrument to verify results and used to classify schools and direct resources based on meritocracy.
“…Com relação aos impactos da COVID-19 nas PMEs no contexto brasileiro, alguns estudos exploraram a questão em empresas operando em diferentes setores (Bretas & Alon, 2020;Dweck, 2020;Pereira & Patel, 2022;Rediske et al, 2022;Reis et al, 2021) como comércio e serviços (Marques et al, 2021) e instituições de ensino (A. D. S. M. Costa et al, 2020;B. G. S. Costa et al, 2022;Dias & Ramos, 2022). Ainda, estudos como Wecker et al (2020) discutiram as estratégias utilizadas pelas empresas para lidar com a pandemia e seus efeitos.…”
Resumo Partindo dos resultados inconclusivos da escassa literatura sobre o impacto do COVID-19 nas pequenas e médias empresas (PMEs), este artigo propõe um novo modelo de avaliação para abordar esse problema por meio de percepções gerenciais. Para atingir esse objetivo, mais de 6.000 PMEs responderam doze rodadas de pesquisas de 2020 a 2021, durante a pandemia, permitindo assim acompanhar a evolução do impacto percebido da pandemia nas pequenas e médias empresas. Uma nova abordagem de função de utilidade ponderada pela entropia é proposta aqui, seguida por regressão de rede neural para mapear quais variáveis relacionadas aos negócios das PMEs impulsionam mais a utilidade percebida de cada critério de negócios durante a pandemia. Primeiro, os pesos dos critérios relacionados aos negócios foram calculados usando a análise de proporção de avaliação de peso passo a passo (SWARA), classificando sua importância relativa - ou percepções - com base nas classificações de entropia de informações derivadas de dados coletados. As medições de entropia de transferência também ajudaram a revelar as relações de causa e efeito entre os critérios. Em segundo lugar, as funções de utilidade comercial para cada critério foram calculadas usando a Avaliação Proporcional Complexa com base nos pesos SWARA. Terceiro, regressões de redes neurais foram usadas para explicar as percepções gerenciais sobre cada critério de negócios durante a pandemia à luz de cada variável de negócios. Nossos resultados, esperados e inesperados, sugerem que as PMEs mais resilientes no Brasil são aquelas com 5 a 10 anos de idade operando nos setores de serviços e construção. Além disso, o sucesso do empréstimo é o segundo critério de maior impacto, impactando profundamente a continuidade dos níveis de atividade econômica; e não é afetado por nenhum outro critério de negócio. Implicações para formuladores de políticas e ações governamentais são destacadas.
“…Some studies evaluating the impacts of COVID-19 for SMEs were carried out for the Brazilian context (Bretas & Alon, 2020;Dweck, 2020;Pereira & Patel, 2022;Rediske et al, 2022;Reis et al, 2021), that operate in different sectors; with a focus on commerce and services (Marques et al, 2021), on educational institutions (A. D. S. M. Costa et al, 2020;B. G. S. Costa et al, 2022;Dias & Ramos, 2022), on the strategies used (Wecker et al, 2020). Thus far, however, it has not been made clear how SME business-related variables impact on the perceived utility of business-criteria, particularly during the COVID-19 pandemic.…”
Departing from the inconclusive results of the scant literature on the COVID-19 impact on Small and Medium Enterprises (SMEs), this paper proposes a novel evaluation model for addressing this issue through managerial perceptions. Over 6000 SMEs responded to twelve rounds of surveys from 2020 to 2021 during the pandemic, allowing to track the evolution over time of the perceived impact of the pandemic on small businesses. A novel entropy-weighted utility function approach is proposed here, followed by artificial neural network regression to map the variables related to the SME’s businesses that most foster the perceived utility of each business criterion during the pandemic. First, weights of business-related criteria were computed using Stepwise Weight Assessment Ratio Analysis (SWARA), sorting their relative importance - or perceptions - based on information entropy ranks derived from questionnaires collected. Transfer entropy measurements also helped in unveiling the hidden cause-effect relationships among criteria. Second, business utility functions for each criterion were computed using Complex Proportional Assessment based on SWARA weights. Third, neural network regressions were used to explain the managerial perceptions on each business criterion during the pandemic, considering each business variable. Our expected and unexpected results suggest that more resilient SMEs in Brazil are 5-10 years old and operating in the services and construction sectors. Moreover, loan success is the second most impactful criterion, deeply impacting the continuity of economic activity levels, and it is not impacted by any other business criteria. Implications for policymakers and governmental actions are highlighted.
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