Abstract
The qualitative evaluation methods presented in this chapter play a complementary role to the quantitative methods referred to in the previous chapter of this book. The author shows wider aspects regarding qualitative research, in addition to detailed remarks concerning fieldwork observation. In the latter part the chapter deals with logic models supporting two key evaluator challenges: measuring expected and achieved project outcomes and attributing these outcomes to specific project activities, based on the application of theory-based approaches. It is essential in the case of development, public and European projects, nevertheless, that the author should encourage these models to be introduced within the wider scope of different projects, including business-related situations. The end of the chapter focuses on the applications of new qualitative intelligent systems. Such systems should not only support the analysis of available qualitative data, but should also be characterized by machine intelligence, as a result of discovering knowledge from data that can be observed subjectively, suggesting specific decision rules, adapting to a particular project situation and the specific needs of researchers and evaluators.
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Grzeszczyk, T.A. (2018). Qualitative Evaluation Methods. In: Mixed Intelligent Systems. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-319-91158-8_4
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DOI: https://doi.org/10.1007/978-3-319-91158-8_4
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