# Learn-CIAM: A Model-Driven Approach for the Development of Collaborative Learning Tools
## 5 Validation
### Results of the First Experiment  
The results were generally satisfactory. We compared technical (CS) with non-technical (ED) profiles. Table 10 in the Appendix A summarizes the results of this experiment, as well as the descriptive statistics (mean, median and mode) of both profiles. Next, we proceed to highlight the results of the items of the questionnaire which are summarized in Figure 14.  
In the first question (MET1), the participants were asked about the suitability and usefulness of proposing a new methodological framework to model, validate and generate collaborative tools. In response, approximately half of both ED and CS experts, 50% and 55% of the respondents, respectively, rated it as five, considering it very useful to propose a method such as Learn-CIAM (**RQ1**). This denotes a possible predisposition to its utility for the part of both profiles. On the other hand, addressing the second aspect of the methodological framework (MET2), the respondents were asked whether following a Model-Driven Development paradigm, as opposed to a traditional ad-hoc development paradigm, was easier for them to use. In this sense, 100% of the respondents with an ED profile fully agreed, while 91% of the respondents with a CS profile agreed, from which 36% fully agreed. These results are positive from both profiles, and it should be noted that the respondents with a less technical (ED) profile were in full agreement (**RQ2**). Regarding the third question (MET3), in which the participants were asked about the adequacy of the election of the Eclipse platform as support for the method, all the respondents with an ED profile agreed, whereas 64% of the respondents with a CS profile agreed, from which 36% fully agreed (**RQ3**). These results denote that both profiles consider as adequate the election of the Eclipse MDD approach as a support for the methodology, the technical experts being more critical about this choice. Furthermore, regarding the questions about the subjective perception of the proposed method, its division in different phases and stages, and the use of high-level languages, the answers were positive and none of the respondents from both profiles disagreed (**RQ4**). Lastly, in relation with the last question about the methodological framework (MET6), which asked whether they considered that a user with less advanced computer skills would be able to apply and generate collaborative tools, 50% of the ED respondents agreed, while the other 50% disagreed, scoring a two. On this same item, among the respondents with a CS profile, there was a bigger variation  
Figure 14: Distribution of results of the most relevant items from the first experiment. in the results, with only 27% agreeing, 18% disagreeing and 9% completely disagreeing. These results indicate a greater disparity of opinion; however, they do not denote very negative results as half of the ED experts agreed. In addition, among the CS experts, a greater part agreed than the sum of those who did not agree with this statement (**RQ5**). In relation to the conceptual framework, we asked about the Learn-CIAN notation (CON2), the conceptual core of the Learn-CIAM methodology, it being worth noting how 100% of the experts of both profiles considered it to be adequate for modeling flows of learning activities, with 50% of the respondents with an ED profile considering it to be very appropriate as well as 45% of the respondents with a CS profile. Additionally, in relation to the visual strain of the notation that this could cause (CON3), again the respondents gave good scores, since more than half of the experts in both groups fully agreed, with 50% (ED) and 55% (CS) respectively, pointing out that the Learn-CIAN notation has a sufficient and manageable number of visual elements (**RQ6**).