Publication: Una aproximación práctica a los diseños de investigación cuantitativa
Authors
Sánchez Martín, Micaela ; Ponce Gea, Ana Isabel ; Rubio Aparicio, María ; Navarro-Mateu, Fernando ; Olmedo Moreno, Eva María
item.page.secondaryauthor
item.page.director
Publisher
Editorial Universidad de Almería
publication.page.editor
publication.page.department
DOI
https://doi.org/10.25115/ecp.v17i35.9725
item.page.type
info:eu-repo/semantics/article
Description
© 2024, Universidad de Almería. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/. This document is the Submitted Published version of a Published Work that appeared in final form in Espiral.Cuadernos del Profesorado. To access the final edited and published work see https://doi.org/10.25115/ecp.v17i35.9725
Abstract
La elección del diseño de investigación tras plantear nuestra pregunta de investigación es una de las claves para aumentar la probabilidad de éxito. Se han propuesto numerosas clasificaciones para los diferentes diseños de investigación. Aunque, a grandes rasgos, los diseños se pueden clasificar en aquellos que siguen un diseño
cuantitativo, cualitativo o mixto, en esta píldora de investigación nos centraremos en una clasificación sencilla y
práctica de los diseños de investigación cuantitativos. Esta clasificación los agrupa en descriptivos (cuando el
objetivo del estudio es describir las características de una población y no hay una elaboración previa de hipótesis de investigación) y analíticos (cuando el objetivo del estudio es intentar explicar la relación, generalmente causal, entre los diferentes factores analizados). Los estudios analíticos se pueden agrupar según el grado de control que el investigador tiene sobre la asignación de la exposición entre los participantes, en estudios de intervención (estudios experimentales y cuasiexperimentales) y observacionales (estudios de cohortes, casos y controles, y transversales). Además de su amplia utilización en ámbitos diferentes del conocimiento, esta clasificación facilita la identificación y utilización de las listas de comprobación que se han elaborado para mejorar la calidad y transparencia en las publicaciones científicas.
After stablishing our research question, the selection of our research design is one of the keys to increase the probability of success. A number of classifications have been proposed for different research designs. Although, broadly speaking, designs can be classified into quantitative, qualitative, or mixed designs, in this research pill we will focus on a simple and practical classification of quantitative research designs. This classify them into descriptive (when the aim of the study is to describe the characteristics of a population and there is no prior elaboration of research hypotheses) and analytic (when the aim of the study is to try to explain the relationship, generally causal, between the different factors analyzed). Analytic studies can be grouped, based on the degree of control the researcher has over the allocation of exposure among participants, into intervention studies (experimental and quasi-experimental studies) and observational studies (cohort, case-control studies, and crosssectional). In addition to its wide use in different areas of knowledge, this classification facilitates the identification and use of checklists specifically developed to improve the quality and transparency in scientific publications.
After stablishing our research question, the selection of our research design is one of the keys to increase the probability of success. A number of classifications have been proposed for different research designs. Although, broadly speaking, designs can be classified into quantitative, qualitative, or mixed designs, in this research pill we will focus on a simple and practical classification of quantitative research designs. This classify them into descriptive (when the aim of the study is to describe the characteristics of a population and there is no prior elaboration of research hypotheses) and analytic (when the aim of the study is to try to explain the relationship, generally causal, between the different factors analyzed). Analytic studies can be grouped, based on the degree of control the researcher has over the allocation of exposure among participants, into intervention studies (experimental and quasi-experimental studies) and observational studies (cohort, case-control studies, and crosssectional). In addition to its wide use in different areas of knowledge, this classification facilitates the identification and use of checklists specifically developed to improve the quality and transparency in scientific publications.
Citation
Espiral. Cuadernos del Profesorado, 17(35) 2024
item.page.embargo
Collections
Ir a Estadísticas
Este ítem está sujeto a una licencia Creative Commons. http://creativecommons.org/licenses/by-nc-nd/4.0/