## 4 Results
### Data Considered in the Analysis  
The first analysis that is run establishes the grades obtained by the students of the two modalities. This comparison, shown in Figure 7, identifies that face-to-face students have better grades. For this, variables such as the time that students interact with the platform and available resources, surveys on the availability and use of office tools were analyzed. Data are the academic systems such as grades and attendance at tutorials and classes. The horizontal-axis represents the interaction time that students have with IT tools and the vertical-axis represents the general grades in the subject evaluated. The horizontal-axis scale considers the use of IT from at least 2 to 6 h of dedication to the use of IT in the aforementioned subject. The red marks represent the students of the online education modality and the green marks represent the students of the face-to-face modality. The IT refers to the LMSs--the attendance and academic record systems. To provide greater granularity, the data from the surveys passed to the 50 students were added. When processed, it was found that face-to-face students perform better with office tools, as well as a variety of different utilities. In the online mode, satisfaction is low and several students do not use tools such as Excel or have other utilities as shown in Figure 8. In this figure, several changes are observed. One of them is that now the measurement is carried out between the grades obtained by the 50 students in the second week of the 2020-2 period, where a survey was run regarding the availability and use of office tools (Excel, Access, web page designs with templates, etc.). The horizontal-axis in the graph represents the values with which the survey questions were scored, with 1 as the lowest level and 5 as the highest level. The reason for analyzing this week specifically is that practical evaluations were carried out with the use of office tools; in addition, the resources contain guides on the use of these tools. Once again, after the analysis of the framework, more marked results are obtained in relation to the use of IT tools. Students with high grades mostly belong to the online education model where the teacher is the one who teaches the use of each tool step by step, something that does not happen in online education. These results are not significant for the purpose of generating an adaptive learning model. Therefore, it is necessary to include a greater number of variables; among these, the data on attendance at classes for face-to-face sessions and tutorials for online education is included in the analysis. After the analysis, it was found that attendance at tutorials and classes do not display a difference that allows the determination of a possible problem. Therefore, a variable is integrated that provides data related to the age of each group. This variable determines that in the online modality the average age is 32 years in relation to the average of the face-to-face modality, which is 20 years. In addition, 93% of the online group worked full hours, as opposed to the face-to-face group that only worked at 1%; none of the latter worked full hours. The results obtained with the inclusion of several variables allow the identification of certain patterns in the groups and can be related in a general way. Thus, the following scenario is presented. The 26 students of the online modality present a high percentage of low marks, considering 6/10 as an  
Figure 7: Analysis of the use of information and communication technology in the administration career in relation to grades per student. acceptable average mark. This group of students work normal hours and most of them are parents. These results can be a determining factor for the analysis, since, by having a limited time for the development of activities, the understanding of the topics is relative to their qualifications. The application of the model to a very small scenario serves as a test bed to make the corresponding adjustments.