## 4 Overview of Included Studies
(2017) created a system employing AI and XR which aims to address unethical behaviors in traditional education in Bangladesh and enhance self-learning. The system integrates AR and VR capabilities through a mobile app and web portal, with AR enabling interaction with 3D models from textbooks and VR offering immersive learning while AI personalizes study guidance based on quiz performance. The concept is built upon simple tools such as, the Google cardboard, simple AI algorithms such as decision trees, and smartphones, the app claims compatibility with low-spec devices. The system was tested by comparing the performance of students using traditional resources and the other using the proposed system and showcased that students with access to the system performed significantly better. Students reported finding the AR, VR, and AI study guide features beneficial. Even though the outcome sounds promising, the study poses several critical limitations. First of all, it attempts to eliminate the teachers' role and does not consider ways to complement traditional educational methods and provide diverse learning styles. The AI capabilities are underwhelming with very limited features. Use of DL and NNs would enhance predictive accuracy and adaptability as well as incorporate features such as interactive learning through conversation, retrieving recent information on subjects, specific searches, tailored quizzes, etc. Additionally, no cost-effectiveness analysis is provided and ensuring accessibility to affordable technology for all students is not thoroughly explored while creating an app for low-spec devices is not deemed sufficient. The testing user base is also extremely limited to only 20 students while no feedback mechanism was implemented in the app. Finally, the content creation seems to be limited to the developers and not expandable by users. Implementing AI or a collaborative framework that allows contributions from educators could enhance this aspect. The solution does not seem easily scalable, and the authors do not discuss further around that topic. The 2023 research by [PERSON] et al. addressed several of the aforementioned limitations while combining AI, IoT and VR in a single framework to modernize physical education (PE) in higher education [72]. The system immerses students in a VR environment for simulated physical activities, with motion data captured via Kinect devices and analyzed using Support Vector Machines (SVM) optimized by Particle Swarm Optimization (PSO) for accurate, real-time feedback. An action information module provides detailed motion data and animations, enabling students to compare their performance with template actions. The system features a 5-layered architecture, including hardware (Kinect sensors, VR-ready computers), data storage, application services, business logic (SVM and PSO algorithms), and a presentation layer offering action evaluation, learning libraries, and intuitive interfaces. Experimental results highlight the system's effectiveness in enhancing PE instruction. Simulations conducted by the authors show significant improvements in performance metrics post-optimization. The system also handled increasing amounts of data effectively, making it better suited for real-world use than traditional methods. The results confirmed that combining VR, SVM, and PSO enhanced PE evaluation by providing individualized feedback while maintaining computational efficiency. The authors also provide a detailed description of the tools, methods, setup, and findings, with all the data available in the paper. This novel method of teaching, not only increases student engagement and performance in PE, but it also makes learning more pleasant while taking into account traditional techniques and the already existing frameworks. It serves as an interesting example of how AI, VR and IoT harmonically cooperate. The synergistic combination of VR, AI and IoT extends to the arts and cultural domain, as demonstrated by [PERSON] et al.