Use of text mining for understanding Peruvian students and faculties’ perceptions on bibliometrics training
Descripción del Articulo
Background: Studies on bibliometrics and informetrics training have focused on teachers and curricular experts’ opinion, only a few studies have examined undergraduate students and practitioners’ perceptions. Objective: To understand how librarianship students and professionals perceive the bibliome...
Autores: | , |
---|---|
Formato: | objeto de conferencia |
Fecha de Publicación: | 2016 |
Institución: | Universidad San Ignacio de Loyola |
Repositorio: | USIL-Institucional |
Lenguaje: | inglés |
OAI Identifier: | oai:repositorio.usil.edu.pe:20.500.14005/1934 |
Enlace del recurso: | https://hdl.handle.net/20.500.14005/1934 http://ceur-ws.org/Vol-1743/paper20.pdf |
Nivel de acceso: | acceso embargado |
Materia: | Minería de texto Bibliometría Estudiantes universitarios Cuestionarios Percepción Profesionales |
Sumario: | Background: Studies on bibliometrics and informetrics training have focused on teachers and curricular experts’ opinion, only a few studies have examined undergraduate students and practitioners’ perceptions. Objective: To understand how librarianship students and professionals perceive the bibliometrics and informetrics training delivered to them. Methods: For data collection, we used a survey with opened-ended questions, to know the genuine responses of the participants. After working with the automatic term extraction technique, for codifying the answers we employed a data dictionary for quantifying the frequency of occurrences. The software programs used at this stage were ter-MEXt and LWIC. Data analysis was carried out with statistics of mean difference and the correlation coefficient. Results: The output of statistical analysis lets us understood how students and practitioners perceive the bibliometrics and informetrics training delivered to them. Conclusion: Text mining techniques facilitates the processing of responses to opened-ended questions, and contributes with a quantitative approach to analyzing people’s opinions. |
---|
Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).