## 2 Background
Several studies on thermal comfort were carried out in educational institutions of different levels. The study performed by [PERSON] et al. [21], compiling 93 research papers on the subject, found that students were dissatisfied with the thermal environment and preferred a colder temperature in all education levels. This study shows that it is necessary to establish a different set of guidelines or standards for students of different ages in different educational levels in order to satisfy their thermal comfort needs or preferences. Another study conducted by [PERSON] et al. on a post-occupancy thermal comfort assessment in a primary school focused on the building's energy adaptation and improvement. A post-occupancy evaluation (POE), in which the sample size was the classroom [22], was performed. Standard PMV and PPD values for both students and teachers were calculated, and then, a survey about their comfort level was conducted. Results show that the children's thermal comfort status is different from that of adults and highlight the concept's subjectivity. Once again, age incidence is stressed and further shows the need to find other tools to get closer to reality. [PERSON], [PERSON] and [PERSON] [23] performed studies in office buildings with air conditioners and mixed mode ventilation, and they used analytical and adaptive models for thermal comfort. For the authors, the analytical model overestimated users' sensation of cold and did not adequately predict the percentage of thermal dissatisfaction. As such, they recommended adapting a broader range of indoor thermal conditions than those recommended by ASHRAE 55-2013 during the functioning of air-conditioning, while the application of the adaptive model would prove inadequate for buildings with air-conditioning, although this finding was not conclusive due to a lack of sufficient data. In the same research line, [PERSON], [PERSON] et al. [24] noted that: \"...there is no consensus among previous studies on how to assess thermal comfort on occupants in mixed mode (MM) buildings. This study aims at comparing the PMV-PPD and the adaptive model applicability in MM buildings and assessing if the occupants' thermal perception varies with different functioning modes...\". The results showed that the analytical model was not fitted for MM buildings and that the adaptive model proved better applicability in cooling mode with air conditioners than with natural ventilation. Studies by [PERSON], [PERSON] et al. showed that the PMV model predicts to some extent the thermal sensation of occupants but fails to estimate the temperature at which occupants feel comfortable [25]. According to [PERSON], [PERSON] et al. [26], \"it was noted that the panelists showed better thermal comfort sensation at lower temperatures than would result from the traditional Fanger distribution, so the authors proposed the experimental function of percentage of dissatisfied (PPD) = f(PMV)\". It is another case that highlights the need to review the methodology for assessing thermal comfort in the face of new challenges. Based on this background, the research study on thermal comfort has been mainly conducted on two models--the mathematical and the adaptive--from a conceptual and methodological standpoint. In the mathematical model, also known as the quantitative method, the person-environment heat exchange is studied by measuring the physiological variations experienced by test subjects in controlled chambers. Thermal balance equations linked to physiological values obtained through experience are solved to predict comfort sensation. As it has been stated, the model reference is [PERSON] [10]. This model is fitted for evaluating thermal comfort in constantly conditioned buildings. Adaptive models are based on qualitative methods using observation, surveys, and/or interviews in actual operability settings, mostly offices and houses, for data mining. They record all possible details about clothing type, people's characteristics, activity, and temperature.