WhatsApp Messenger Forensics: Extracting Insights for Enhanced Learning Analytics in Smart Education

The rapid adoption of smartphones has changed how internet users engage in conducting many online activities, offering flexibility, high speed, user-friendliness, and seamless accessing to all mobile applications. This trend is also extended to the metaverse, where virtual environments introduce new opportunities and challenges for both digital misconduct and educational interactions. WhatsApp Messenger is one of the most widely used communication tools, it poses significant challenges for analyzing user data in the context of smart education. These challenges, including data acquisition, data integrity, and preservation, are further compounded in the immersive and dynamic environments of the metaverse. Mobile forensic tools, such as MOBILedit Forensic Express, are vital for educational experts to navigate all these obstacles with certain precision. The primary objective of this research is to foster smart learning in the application of mobile digital forensic tools for extracting and analyzing smartphone data. To achieve this, the study presents a case-based analysis of WhatsApp Messenger forensics across various Apple devices running different iOS versions, utilizing MOBILedit Forensic Express to assess the tool’s effectiveness in data extraction and analysis. The findings show that the tool successfully retrieves all relevant WhatsApp data, simulating manual searches on iPhones. However, some limitations were raised with devices newer than iPhone 8, due to some hardware-specific factors. These insights offer a foundation for refining learning analytics and contributing to the evolution of digital forensics education within smart education and learning platforms.