Figure 1.A generic MMOL platform Architecture. The next table summarizes the 4DF in our MMOL experience Table 1. Using the 4DF to implement MMOL experience. Figure 3. MadriPolis evaluation meeting point Figure 2. MadriPolis in realX tend Figure 4. MadriPolis collaborative space I Figure 6. Co-browsing view er Figure 8. In-world Google document to determine average values conducted with 4DF (Table 2). 4.4.2 The educational scenario Figure 9. Course over LCMS Figure 10. Evaluated Learning O bject (http://www.ite.educacion.es/w3/novedades/dossiers/libro/) (Fig. 10). Figure 11. Researchers participating in the MMOL platform Table 3. Density values of case studies. The last column shows the density increase trend when MMOL is used. students became removed from many of the day-to-day workings in Table 8 (Ford, Moore and Harmon, 2005). Table 8. Bloom’s Taxonomy: Description and Possible Products. (A dantad from Fard at al ONNS) diversity content into the curriculum (see Table 9). educational situations in the fields of diversity. A translated version of Figure 20. Summary of Aldrich’s approach steps." Source: INE! (Spanish N ational Institute of Statistic) showed in the next table (Table 11). On that basis, a summarized description of activity centers is Evaluation Level ( planning of all activities. The same instructional unit was carried out in both real s; RCGR and VWGR. The next table (Table 13) shows the confidence intervals for each simulation. Table 16 presents Total Score means, standard errors, and 95% totalizes results obtained in both groups. Figure 28. Mean Differences between groups’ simulations As reviewed in earlier chapters, MMOL platforms or educational al., 2012). The generic representation of this architecture is shown in Table 19. Teacher's Activity Plan Activity Plan Figure 31. Avatar to chatbot interaction Lattemann, 2008). The main survey items are showed in Table 21: significant antecedent to explain BIU. As we explain above, PEOU concerns PU in the following table (Table 22). Therefore, we define a new hypothesis associated with variables and the hypotheses are depicted in Figure 32. Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. carry out in this thesis. Figure 35 . Data Analysis and collection method. analysis and oollection process used in this thesis: A.4 TAM method related: As a summary, the next figure (Figure 35) shows the data
