## 4 Result Analysis
### Proposal and Showcase Studies
The provision of customization, the interactive experiences, the accessibility from different devices, and the collection of data emerged as the most impactful features. Finally, they highlighted the use of data analytics and commented upon the use of artificial intelligence-based module to undertake this task. Using xAPI, [PERSON] et al. [83] explored the use of learning analytics to track learners' behaviors in augmented reality applications. Their proposed application will follow the positive behavior intervention and support methodology and will be able to support behavioral lessons while also capitalizing on the benefits that augmented reality applications bring. To support the educational process, [PERSON] et al. [80] proposed a framework for developing augmented reality mobile applications. Using the suggested framework, they developed an augmented reality application and integrated analytics to determine learners' engagement and performance. [PERSON] and [PERSON] [97] explored the integration of learning analytics into virtual reality environments to assess students' experiences and performance. They highlighted the significance of learning analytics to assist in developing, managing, and operating teaching and learning within virtual environments. Their proposed system follows the theory of constraints and uses different assessment methods. [PERSON] et al. [84] focused on presenting design guidelines for training industrial stakeholders within virtual reality settings. Although the study explored different design considerations, learning analytics emerged as one of the most impactful approaches to enhance the effectiveness of training and learning in virtual reality. [PERSON] et al. [88] investigated the use of data analytics within virtual reality environments to support language learning. Their application enabled learners to interact with virtual agents and for meaningful information to be collected. [PERSON] et al. [85,86] explored the use of learning analytics within web-based 3D and 360-degree virtual reality environments. Specifically, they presented a framework for creating e-learning material and quizzes that used linked data. Additionally, they presented a prototype system that uses visual analyzing tools and collects and analyzes data from learners' activities. [PERSON] et al. [81] and [PERSON] et al. [87] demonstrated two virtual reality applications for medical training, which also integrated aspects of real-time data analytic through the use of supervised machine learning. Their work highlighted the potential of these technologies to offer training opportunities even in unprecedented events, such as the COVID-19 pandemic. In their study, [PERSON] et al. [95] presented their evaluation platform for assessing user interactions in virtual learning environments. Specifically, they focused on integrating learning analytics to personalize the overall experience through the integration of xAPI. [PERSON] et al. [79] focused on examining the use of immersive learning analytics to support different training scenarios. Their approach demonstrates how collaborative immersive community analytics could be achieved when using wearable devices to support learning. [PERSON] et al. [94] looked into the usefulness of learning logs in the context of virtual reality classrooms. They highlighted the significance of learning analytics to identify and track issues encountered by most students and to provide meaningful visualized information to assist teachers. [PERSON] et al. [82] explored the use of learning analytics in the context of a virtual reality-based computer science course. The study goes over the applicability of learning analytics within virtual reality environments and emphasizes their use in supporting learners' self-regulated learning and self-efficacy, as well as learners'affective and cognitive behaviors. The potential of supporting all learners despite their learning performance was highly commented.