Análise de agrupamento (Clusters Analysis) em duas etapas no ensino à distância: Uma forma de reduzir as lacunas na literatura científica no ensino à distância

Guillaume Desjardins; Cathia Papi; Serge Gérin-Lajoie; Louise Sauvé

doi:10.31211/rpics.2021.7.2.230

Autores

Guillaume Desjardins Université du Québec en Outaouais, Gatineau, Canada https://orcid.org/0000-0002-5669-6671
Cathia Papi Université TÉLUQ, Québec, Canada https://orcid.org/0000-0002-5193-3906
Serge Gérin-Lajoie Université TÉLUQ, Québec, Canada https://orcid.org/0000-0001-7030-1640
Louise Sauvé Université TÉLUQ, Québec, Canada https://orcid.org/0000-0001-5362-7104

DOI:

https://doi.org/10.31211/rpics.2021.7.2.230

Palavras-chave:

Curso online, Ensino à distância, Ensino superior, Perseverança, Análise cluster

Resumo

Contexto: Embora as taxas de abandono escolar sejam frequentemente muito elevadas no ensino à distância, tem sido realizada muita investigação para identificar os fatores que influenciam o abandono escolar ou a persistência neste modo de aprendizagem. As conclusões destes estudos nem sempre convergem e salientam que é difícil isolar um único fator explicativo. Embora a maioria dos fatores sejam pessoais e ambientais, há menos investigação sobre a relação entre a conceção e a retenção ou desistência do curso. Método: Este estudo apresenta uma metodologia que envolve uma análise em duas fases de 623 variáveis de 19 cursos universitários de uma instituição de ensino à distância (EAD). Este estudo agrupou os cursos em cinco tipos de cursos com base em 22 variáveis. Resultados: Os resultados indicaram que certas variáveis sociodemográficas se tornam um fator de risco de desistência dos cursos, dependendo da sua distribuição nos cursos padrão. Conclusão: Esta metodologia sublinha a importância da conceção instrucional na equação de retenção e desistência da EAD e ajuda a explicar, em parte, porque é que estudos anteriores não chegaram a um consenso sobre quais as variáveis que devem ser utilizadas para explicar a desistência.

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