segunda-feira, 22 de junho de 2020

Técnicas de Abordagem & Coleta de Dados

Student, Typing, Keyboard, Text, Startup
Indução & Dedução (Abordagem)

CERVO; BERVIAN; DA SILVA (2007, p. 44 e 47)

"Na indução, a conclusão está para as premissas como o todo está para as partes. De verdades particulares concluímos verdades gerais" (grifei)

"A dedução é a argumentação que torna explícitas verdades particulares contidas em verdades universais. O ponto de partida é antecedente, que afirma uma verdade universal, e o ponto de chegada é o consequente, que afirma uma verdade particular ou menos geral contida implicitamente no primeiro".

"Pode-se tomar a inferência como equivalente ao raciocínio. Pela inferência, somos levados a tirar conclusões a partir de premissas conhecidas. Inferir é tirar uma conclusão a partir de uma ou várias proposições nas quais ela está implicitamente contida. A inferência é imediata quando chegamos à proposição nova sem intermediários e mediata quando há intermediários". (2007, p. 49, grifei)

Entrevista, Questionário & Formulário

(coleta de dados)

A coleta de dados é uma importante fase de pesquisa. Para coletar dados, devem-se utilizar como ferramentas: a) entrevista; b) questionário; e c) formulário.

Antes de examinarmos cada uma delas, veremos alguns passos a serem observados na criação das perguntas:

- identificar dados / variáveis;
- selecionar tipo de pergunta (vantagens / desvantagens);
- uma ou mais perguntas para cada dado;
- questões elaboradas (clareza / classificação / necessidade);
- codificar questões (tabulação / análise);
- instruções claras e precisas;
- submissão a outro técnico (para revisão);
- revisão do instrumento;
- instrumento para pré-teste.

(CERVO; BERVIAN; DA SILVA, 2007, p. 51)

Entrevista

Objetivo: "recolher, por meio do interrogatório do informante, dados para a pesquisa". (2007, p. 51)

Neste caso, a entrevista se torna necessária quando se precisa obter dados que não constam em registros e fontes documentais e que podem ser adquiridos por pessoas. (2007, p. 51)

Critérios e preparos para a Entrevista

- planejar a entrevista (objetivos);
- conhecimento prévio do entrevistado;
- local / horário com antecedência;
- criar condições (naturalidade);
- escolher o entrevistado (familiaridade / autoridade);
- lista das questões (mais importantes);
- número suficiente de entrevistados.

(2007, p. 52)

Questionário

"O questionário é a forma mais usada para coletar dados, pois possibilita medir com mais exatidão o que se deseja". (2007, p. 53)

Deve-se enviá-lo por correio / e-mail, mantendo a imparcialidade de elaborador, com clareza na redação das questões, bem como o anonimato dos questionados, para se sentirem mais à vontade.

Neste sentido, perguntas fechadas são melhores do que questões abertas.

Formulário

"O formulário é uma lista informal, catálogo ou inventário, destinado à coleta de dados resultantes quer de observações quer de interrogações, e seu preenchimento é feito pelo próprio investigador". (2007, p. 53)


Referência


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

CERVO; BERVIAN; DA SILVA. Metodologia Científica. 6a. edição. São Paulo: Pearson, 2007)



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