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Computerized Adaptive Assessment of Organizational Climate

Fernando Menéndez et al · Servicio de Publicaciones de la Universidad de Murcia · 2017

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Computerized Adaptive Tests (CAT) constitutes a major advance in the field of the assessment of social sciences and health. It is interesting to incorporate this methodological development to organizational field. The objective of this research is to develop a CAT for evaluating the organizational climate. In order to do this, a bank of 160 items was constructed, which was administered to a sample of 3,163 workers (M age= 51.90 years; SD= 6.28 years). The results show that the CAT works efficiently for the three item banks used (150, 130 and 50 items). The information function shows that the latent trait in the whole range of values is measured with similar accuracy. The correlation between the scores obtained with the CAT, the three item banks and the CLIOR scale of organizational climate was higher than .90 in all cases (SE<0.32). With a SE< 0.32, the 150 item CAT uses a mean of 22.5 items (SD = 13.5 items). The CAT developed allows an accuracy and useful assessment of the organizational climate on organizational settings and research.

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APA 7

al, F. M. E. (2017). Computerized Adaptive Assessment of Organizational Climate. https://doi.org/10.6018/analesps.33.1.225921

MLA

al, Fernando Menéndez et. "Computerized Adaptive Assessment of Organizational Climate." 2017. https://doi.org/10.6018/analesps.33.1.225921.

Chicago

al, Fernando Menéndez et. 2017. "Computerized Adaptive Assessment of Organizational Climate.". https://doi.org/10.6018/analesps.33.1.225921.

Harvard

al, F. M. E. 2017, Computerized Adaptive Assessment of Organizational Climate, Servicio de Publicaciones de la Universidad de Murcia, available at: https://doi.org/10.6018/analesps.33.1.225921 [Accessed 8 Aug. 2026].

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Title
Computerized Adaptive Assessment of Organizational Climate
Author / contributors
Fernando Menéndez et al
Publisher
Servicio de Publicaciones de la Universidad de Murcia
Publication year
2017
ISSN
0212-9728
ISSN
0212-9728
Language
English

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