Revolutionizing Education with the Metaverse: A Study of the AIIS Program

By Dr. Sampath LonkaReviewed by Susha Cheriyedath, M.Sc.Oct 18 2023

In a recent publication in the journal Electronics, researchers constructed the artificial intelligence, innovation, and society (AIIS) collaborative learning interface, a metaverse-based educational platform for undergraduates.

Background

In recent decades, experts across diverse fields, particularly those specializing in human-computer interaction and information systems, have harnessed cutting-edge technologies to enhance educational experiences for students and educators.

Virtual reality (VR), a simulated digital environment enabling user interaction, has captured the interest of researchers, educators, and students, significantly enhancing instructional and learning experiences, particularly in fields such as medicine. Additionally, emerging immersive technologies such as mixed reality (MR) and augmented reality (AR) have gained attention, offering novel ways to interact with both physical and virtual elements.

The metaverse, a virtual interconnected framework, has attracted researchers and developers from various disciplines, igniting interest in its applications across education, entertainment, and enterprise. This metaverse offers dynamic virtual spaces that enable real-time user interaction with digital content.

AIIS curriculum and learning environment

The core objective of the AIIS project is to provide a comprehensive medical technology program tailored for engineering students. This program encompasses AI, innovation, and soft skills to integrate them into European university curricula and potentially into Asian universities. The project leverages a metaverse framework to facilitate collaboration between students from engineering and medical backgrounds, creating real-life problem-solving scenarios.

Both the academic and practical components are mandated for the AIIS learning program. A third of the work consists of the practical portion, which is a machine-learning task using medical data under mentor supervision. The remaining two-thirds are dedicated to the theoretical portion, which may be accessed through the metaverse's AIIS learning interface.

The pedagogy is problem-centered, concentrating on the interests, study habits, and past knowledge of each student. It uses a tri-axial teaching method that combines inquiry-based pedagogy, reflection, and cooperation. The main goal is to assess if it is feasible to teach theoretical material in a shared metaverse setting, successfully integrating theory with real-world application.

The AIIS curriculum consists of 59 theory tasks addressing AI and soft skills. The AI module covers topics such as AI introduction, expert systems in healthcare, image recognition, machine learning, and machine vision basics in healthcare. These topics aim to provide students with a better understanding of AI in healthcare.

The soft skills module focuses on adaptability, self-awareness, communication, work organization, teamwork, and engineering ethics. The AIIS environment offers a range of user interfaces, with students navigating a virtual learning environment. Students can choose the sequence in which they complete tasks, with each task accompanied by a theory video lecture and an activity. To complete the theory component, students must earn 105 micro-credentials from the tasks. Additionally, students are expected to accumulate at least ten collaborator points through active participation in tasks initiated by their peers.

The environment also includes reflection zones, an interactive feature for exploring the physiological layers of the human head, and an ornamental control panel for observation. The AIIS program's first iteration was piloted with medical and engineering students, resulting in an approximate completion rate of 81 percent. User feedback indicated a positive overall experience with the collaborative virtual learning environment.

Assessing AIIS system usability: insights and recommendations

The study's primary goal was to assess the usability of the AIIS system, aiming to gain insights into student interactions within the learning environment. This investigation employed a mixed-methods approach, combining quantitative and qualitative research techniques to provide a comprehensive evaluation. The study primarily involved undergraduate students with a balanced gender distribution, ensuring a comprehensive evaluation of the AIIS system.

Despite their technological proficiency, limited exposure to VR, AR, or XR technologies and the metaverse revealed potential adoption barriers, including accessibility, cost constraints, awareness, and specialized equipment requirements. The study also highlighted the importance of equipping educators with the skills to effectively integrate immersive technologies into teaching practices. Addressing this aspect is crucial for successfully adopting AR and immersive technologies in educational settings.

Nielsen's heuristics played a significant role in the design of the AIIS system, enhancing usability, user satisfaction, and learning efficacy. Further application of these heuristics, such as aligning the system with real-world conditions, privileging recognition over recall, and improving flexibility and error prevention, can further strengthen the AIIS system.

The study employed various evaluation methods, including in-game and post-game Game Experience Questionnaires (GEQ) questionnaires, heuristic evaluation, and semi-structured interviews. Evaluating users' in-game experiences revealed promising aspects, including competence, sensory immersion, and challenge. However, there is room for improvement in terms of enhancing user agency, minimizing distractions, and maintaining the balance between challenge and frustration. The study emphasized the need for thoughtful discussions about integrating the metaverse into existing educational structures, considering ethical and societal ramifications, privacy, data protection, and the digital divide.

Considering the findings from their observational study during the usability test, the researchers present a set of design guidelines and recommendations aimed at enhancing the AIIS metaverse-based learning system and similar metaverse or mixed-reality systems in the future.

Conclusion

In summary, researchers introduced the AIIS metaverse-based learning program, focusing on its usability and user experiences for undergraduate students in computer engineering, medical, and nursing fields in Asia. The results of various evaluation methods indicated that AIIS excels in user-friendliness, captivates learners, and fosters an electrifying learning environment.

The study also offered valuable design recommendations for metaverse systems in academia, with short-term goals including enhancing interface usability, diversifying learning modules, and personalizing the learning experience.