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The Grounded Theory approach uses data to drive the construction of theory as opposed to other methodological approaches, which fit data to existing theoretical frameworks.
In this paper we describe methodological approaches which we have applied and refined for the past 10 years for the evaluation of health information systems.
Based on an analysis of 80 case studies, Annex 57 showed various inconsistencies in current methodological approaches, which inhibit comparisons of results and difficult development of robust reduction strategies.
As a consequence, Learning Analytics in mobile learning requires original methodological approaches which enrich techniques already tested in different learning contexts (e.g., in Virtual Learning Environments) with specific strategies to deal with the complexity of mobile learning and manage the corresponding datasets.
Successful outcomes depend on robust methodological approaches which are complementary and which engage multidisciplinary researchers.
However, it has been emphasized by Paul et al. [12] the need for more studies with sufficient methodological approaches, which will investigate the cholinergic hypothesis in MG.
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Data observed may be the consequence of the methodological approach, which was retrospective.
This was addressed by Murray (2002) who proposed a new methodological approach which uses a patent-paper pair rather than using patents and publication as separate indicators.
We delineate our key assumptions and comprehensively describe our methodological approach, which employs analytical derivation and general linear least squares curve fitting.
In order to follow a methodological approach which is consistent with the sampling theorem it is necessary to treat the dynamics in the context of multivariate Fourier analysis.
Thus, planning energy conservation measures is a difficult task, demanding a precise methodological approach, which will embody most of these aspects to a great extent.
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