A Proposed Model for enhancing the Orientation towards Comparative Learnology based on incorporating some Artificial Intelligence Applications at Pre-university Institutions

The research aimed to propose a model to enhance the orientation towards comparative learnology based on incorporating some Artificial Intelligence Applications into Pre-university Institutions. To this end, the research adopted the descriptive approach to identify both the foundations of comparative learnology through comparative education literature, and the most convenient artificial intelligence applications that support this orientation. To investigate the effectiveness of incorporating these artificial intelligence applications into learning environments for both observing their lived reality and supporting the orientation towards comparative learnology, the research administered a questionnaire to a group of educational technology experts (32 experts) at some Egyptian universities. Based on the findings of the field study, the proposed model was formulated including four stages; the first for collecting data regarding the lived reality of learning environments through incorporating Internet of Things into them, the second stage for analyzing learning data through incorporating artificial intelligence applications, the third stage for managing learning data locally through fog computing, finally the stage of publishing learning data globally through cloud computing. Based on the findings, learning environments can be compared according to real data and based on interpretations of local culture (Emic Approach).