AI-Powered VR for Enhanced Learning Compared to Traditional Methods

This paper evaluates a VR (Virtual Reality) application aimed at enhancing the learning of Python collection data types and structures for electrical and electronic engineering students. By incorporating gamification and personalisation features, the application provides an immersive environment where students can interact with virtual representations of complex programming concepts. To further enhance interactivity and engagement, the application integrates a virtual assistant and example generator, developed using Meta Voice SDK (Software Development Kit) and wit.ai. These AI (Artificial Intelligence)-NLP (Natural Language Processing) tools create personalised learning paths and generate dynamic examples based on individual learning progress. A user study was conducted with a total of 48 participants. During the user study, participants were divided into two equal groups of 24, both wearing EEG (Electroencephalography) headsets: one group engaged with the VR application, while the other read the traditional booklet, allowing for the recording and analysis of attention and engagement levels. These measures of engagement and attention were then compared to those extracted from a benchmark cohort of students whose learning experience was through more traditional booklets. The results indicated a statistically significant improvement in understanding Python collections among VR users compared to their baseline scores, highlighting the benefits of interactive and tailored learning environments. Additionally, EEG data analysis showed that VR users exhibited higher average levels of attention and engagement compared to those using the paper-based method, demonstrating the effectiveness of immersive technologies in sustaining learner interest and focus, particularly in enhancing learning for software development.