# Transforming Interactive Educational Content into Immersive Virtual Reality Learning Objects
## 1 Introduction  
Every individual has a preferred way of thinking, processing, and understanding information, and this diversity of learning styles has attracted considerable attention in educational research. The four primary learning styles commonly identified are aural, visual, read/write, and kinesthetic (tactile) learning styles [1]. However, most of the learning material and information presented in e-learning are tailored primarily for visual and auditory learners, often a disadvantage for kinesthetic learners [2]. Kinesthetic learners are better suited for active learning environments, where physical activities and hands-on experiences play a crucial role in their understanding and retention of knowledge [2]. Thankfully, immersive virtual reality (IVR) technology underwent increasing technological developments in recent years [3]. The reduction of its cost throughout the years made it an attractive alternative solution to traditional laboratories and equipment [4]. Initially popularized for entertainment, gaming, and training purposes, IVR has extended into the realm of education, where IVR is being recognized as a tool that can transform approaches to learning [5], allowing users not only to experience virtual environments but engage multiple senses simultaneously, including visual, auditory, kinesthetic interactions. This level of immersion introduces new opportunities for presenting learning material and facilitating learning for kinesthetic learners [6]. Subsequently for kinesthetics, IVR integration in educational environments is beneficial, as it befeft their preferred learning style encompassing hands-on experiences and physical activities [4]. In IVR environments, students can actively interact with virtual objects, manipulate scenarios, and conduct practical simulations, thus promoting active learning experiences. Such IVR applications can increase the motivation [7], interest [8], and retention of students' knowledge [9, 10], ultimately improving their learning outcomes [11]. Numerous systematic reviews found in scientific literature have analyzed various research works that apply IVR technology for different educational [5; 12; 13; 14; 15; 16; 17] or industrial training purposes [18]. These papers range from proposals to full studies of developed solutions, or their effectiveness evaluations. However, not all works are specifically focused on the implementation of kinesthetic learning using IVR technology. Additionally, while IVR does bring promising potential into education [12; 14; 18], there are pressing challenges that need to be addressed. One challenge that requires consideration includes the development and integration of desktop or IVR applications into an existing learning management system (LMS) [19]. Another challenge is that it is expensive to develop tailored IVR educational applications [6; 12; 17]. Depending on the complexity of the application, it may require a wider set of design features or detailed 3D environments, which in turn can increase the cost of development. This can be highly probable with IVR applications adapted for kinesthetic learners as it requires a higher level of interactivity, as one way to reduce or share the cost of development and management of any educational content was through the concept of learning objects [20; 21]. Learning objects (LOs) are reusable and sharable packages containing educational content and its metadata description [21]. There is no clear definition on what type or scope of educational content should be included in a learning object, meaning that it can contain any volume of text, image, audio or video resources, interactive content [22; 23], etc. However, LOs' metadata must be properly annotated as they help categorize LOs and allow users to find suitable content for a specific context more efficiently, which is key to an LO's reusable and sharable nature [20; 24]. A correct structure of LOs and their metadata are defined by standards such as Learning Object Metadata (LOM) or the Sharable Content Object Reference Model (SCORM) [20].