Publicação
Identifying at-risk students in higher education
| Resumo: | The successful implementation of quality management systems in higher education relies on the ability to address topics meaningful to stakeholders. A topic that is moving to the top of many higher education institutions agendas and is meaningful to students, faculty and management is student dropout. Alongside its social and personal consequences, dropout impairs cost efficiency and the institution's image. This paper shows that in spite of the complex web of factors influencing student dropout, simple models for the identification of at-risk of dropout students can be derived and used to support decision making. The paper starts with an introduction to dropout models, next, the difficulty in implementing quality management systems in higher education is addressed; details about a process for the identification of at-risk students are presented. A case study is used to show that it is possible to identify at-risk students using only academic data and administrative records. Finally, the advantage of including an at-risk student identification process within the framework of a higher education quality management system is discussed. |
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| Autores principais: | Duarte, Rogério |
| Outros Autores: | Pires, A.M.R.; Gonçalves, Helena |
| Assunto: | Higher education Student dropout Quality management system Academic analytics |
| Ano: | 2014 |
| País: | Portugal |
| Tipo de documento: | artigo |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Setúbal |
| Idioma: | inglês |
| Origem: | Instituto Politécnico de Setúbal |
| Resumo: | The successful implementation of quality management systems in higher education relies on the ability to address topics meaningful to stakeholders. A topic that is moving to the top of many higher education institutions agendas and is meaningful to students, faculty and management is student dropout. Alongside its social and personal consequences, dropout impairs cost efficiency and the institution's image. This paper shows that in spite of the complex web of factors influencing student dropout, simple models for the identification of at-risk of dropout students can be derived and used to support decision making. The paper starts with an introduction to dropout models, next, the difficulty in implementing quality management systems in higher education is addressed; details about a process for the identification of at-risk students are presented. A case study is used to show that it is possible to identify at-risk students using only academic data and administrative records. Finally, the advantage of including an at-risk student identification process within the framework of a higher education quality management system is discussed. |
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