# Intelligent Educational Environments: Recent Trends, Modeling, and Applications
## 5 Results
### Conceptual Model of an Intelligent Educational Environment
_TeachingLearning_ interacts with _ResourceLibrary_, which indexes and stores diverse content such as video, audio, interactive exercises, text, etc., and thus enables teachers to use various types of learning resources. Most of the functionalities of ITS are implemented by classes _TeachingLearning_, _EducationalTechnology_, _Assessment_, _Analytics_, and _DigitalRepository_. Also, the classes _Authoring_ and _Automation_, together with _EducationalTechnology_ help teachers offer several personalization and adaptation modes. These modes are based on user profiles in combination with applied _Analytics_ (e.g., learning analytics, machine learning, etc.). Further, feedback from _Assessment_ also helps to refine personalization and adaptation approaches considering the results achieved. The _TeachingLearning_ and _Assessment_ classes and users' _Profiles_ can store highly structured information, including ontological knowledge models. This information can form the basis of personalization strategies implemented by built-in multiagent systems. The _EducationalTechnology_ class contains the attributes IntelligentTutors, Personalization, and KnowledgeBasedTech (e.g., ontologies, LLM, and machine learning) that can support the learning process of all students, including those with specific educational needs. In this way, they propose real-time personalization of the learning/tutoring process. Intelligent tutors usually work in multiagent environments, proposing built-in communication and collaboration mechanisms. They can use knowledge-based reasoning mechanisms to recommend the best learning resources to every student. Hybrid reasoning that combines rule-based, model-based, and case-based reasoning can be most useful in supporting intelligent tutoring. The class _SmartEducationalDevice_ includes smart devices, such as interactive screens, web cameras, and various computer-based devices that are used in implementing the teaching-learning process. Appliances that ensure classroom comfort, such as heating, ventilation, and air conditioning systems, are usually responsible for almost half the energy consumption in contemporary smart schools and universities. Thus, in integrated intelligent educational environments, one of the goals is to reduce operating costs. Modern appliances may be viewed as _IoTDevice_ class instances in their own right, and these capabilities can be applied to control and optimize the microclimate in smart classrooms to achieve energy efficiency. Advanced smart technologies permit the continuous monitoring of appliances and can help achieve appropriate microclimate conditions in educational environments, as well as reliable control, fault detection, and hence--energy efficiency. The conceptual model illustrated in Figure 7 incorporates the concept of gathering data from IoT devices organized in predominantly wireless sensor networks and controlling the learning environment via different kinds of actuator IoT devices. An IoT device (modeled by the class _IoTDevice_) may act as both a \"Sensor\" and an \"Actuator\", which is why these device roles are represented as interfaces in the model. On a higher level, the data that are gathered by devices implementing the interface \"Sensor\" are divided into two broad categories--data related to the environment (temperature, humidity, air quality, luminosity, etc.) and data related to interaction with the participants of the learning process (e.g., presence of students, frequency of movements, gestural patterns, sound patterns, etc.). The data belonging to each category is managed by a separate class--_Environment_ or _Interaction_, respectively. The devices implementing the interface \"Actuator\" also follow this categorization. Environmental control includes air conditioning systems, motorized windows, window shade control, smart lighting, etc. The actuators that are designed to enhance interaction include laser projection systems, multimedia systems with sound and video capabilities, smart physical models, laboratory equipment, etc.