Methodological Triangulation

Methodological triangulation has been a core criterion for choosing methods to capture uniqueness in learning. The collection of data can be experienced overwhelming when it is happening simultaneously with all the daily iterations of implementation loops and we learned that more focused data collection could be needed to avoid the amount of data. 

Both observational and archival studies are needed in order to understand the fiiU complexity of a natural environment, also when the possibilities for controlled experiments are limited (Bisantz and Drury 2005). The study employed methodological triangulation of accident statistics, video observations and scenario workshops, covering all three time perspectives of the topic past (accident archival), present (observations) and future (scenarios), as presented in Fig. 2. 

Similar to the concurrent triangulation approach, the concurrent nested strategy uses one data collection analysis phase. However, as indicated in Figure 5, one approach has priority over the other and the more dominant methodology guides the study. The less dominant method may address a different research question or collect data at different levels— teaching assistants rather than faculty or students, or administrators rather than faculty members. 

In this study, we used qualitative approaches by triangulating the data collection procedure. Our philosophical position was to approach issues without a priori notion to the extent that we could identify emerging issues. Therefore, we used grounded theory methodology that allows the researcher to study a phenomenon without a set framework but instead lets us see that specific issues emerge (Kezar... 

Some of the most used technologies for indoor location include the use of infra-red [15], ultrasonic waves [16], pressure sensors [8], RFID (Radio Frequency Identification) [13] and wireless communications networks [1, 9, 10]. In what concerns to the methodologies used to obtain the location, they can be divided into three main areas [3] Triangulation, Proximity and Scene Analysis. 

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