Examining Users' Concerns while Using Mobile Learning Apps

Abstract

Mobile learning applications (apps) are increasingly and widely adopted for learning purposes and educational content delivery globally, especially with the massive means of accessing the internet done majorly on mobile handheld devices. Users often give feedback on use, experience, and general satisfaction via the reviews and ratings provided on the various distribution platforms. The massive information offered through the reviews presents an opportunity to derive valuable insights. These insights can be utilized for multiple purposes by different stakeholders of these learning apps. This large volume of reviews creates significant information overload and reading through could be time-consuming. We analyze these user reviews by combining text mining techniques of topic modeling using Latent Dirichlet Algorithm (LDA). These techniques identify inherent topics in the reviews and variables of user satisfaction while engaging the apps. The content analysis reveals the importance of videos (multimedia) and downloads as integral parts of learning apps. The thematic analysis identifies features under these headings - financial, technical and design. Going by the values derived from these integral components and features of learning apps, it is worthwhile for app developers to improve on these to create a rewarding learning experience.