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Export Reference (APA) 
Luísa Veloso & Craveiro, D. (2017). Evaluation and participation: identifying different school organization profiles in Portuguese public schools. Portuguese Journal of Social Science. 16 (2), 209-231
Export Reference (IEEE) 
M. L. Veloso and D. M. Craveiro,  "Evaluation and participation: identifying different school organization profiles in Portuguese public schools", in Portuguese Journal of Social Science, vol. 16, no. 2, pp. 209-231, 2017
Export BibTeX 
@article{veloso2017_1785924891926,
	author = "Luísa Veloso and Craveiro, D.",
	title = "Evaluation and participation: identifying different school organization profiles in Portuguese public schools",
	journal = "Portuguese Journal of Social Science",
	year = "2017",
	volume = "16",
	number = "2",
	doi = "10.1386/pjss.16.2.209_1",
	pages = "209-231",
	url = "http://www.ingentaconnect.com/contentone/intellect/pjss/2017/00000016/00000002/art00006"
}
Export RIS 
TY  - JOUR
TI  - Evaluation and participation: identifying different school organization profiles in Portuguese public schools
T2  - Portuguese Journal of Social Science
VL  - 16
IS  - 2
AU  - Luísa Veloso
AU  - Craveiro, D.
PY  - 2017
SP  - 209-231
SN  - 1476-413X
DO  - 10.1386/pjss.16.2.209_1
UR  - http://www.ingentaconnect.com/contentone/intellect/pjss/2017/00000016/00000002/art00006
AB  -  The article discusses some of the major changes in Portuguese schools, due to both the external evaluation process set up in 2008 and the new school management model. The results discussed here demonstrate how the external evaluation process in Portugal highlights the importance of schools as organizations and the focus on community involvement in school management. A multivariate analysis based on a set of variables enabled us to define three school organization profiles (innovative, traditional and diffuse) using two points of reference: the type of curriculum offered and the relationship with the school community. The article consolidates an analysis based on mixed-method research, enhancing the analysis of qualitative information, how qualitative information can be turned into quantified variables, and how data reducing provides support for quantitative and qualitative data analysis. 
ER  -