Examining Users’ Concerns while Using Mobile Learning Apps

Author:

Okuboyejo Senanu,Koyejo Ooreofe

Abstract

<p class="0abstract">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 submit their feedback on use, experience and general satisfaction via the reviews and ratings given in the digital distribution platforms. With this massive information given through the reviews, it presents an opportunity to derives valuable insights which can be utilized for various reasons and by different stakeholders of these mobile learning apps. This large volume of online reviews creates significant information overload which presents a time-consuming task to read through all reviews. By combining text mining techniques of topic modeling using Latent Dirichlet Algorithm (LDA) and sentiment analysis using Linguistic Inquiry Word Count (LIWC), we analyze these user reviews. These techniques identify inherent topics in the reviews and identifies variables of user satisfaction of mobile learning apps. The thematic analysis done reveals different keywords which guide classification into the topics identified. Conclusively, the topics derived are important to app stakeholders for further modifications and evolution tasks.</p>

Publisher

International Association of Online Engineering (IAOE)

Subject

Computer Networks and Communications,Computer Science Applications

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Learning processes, memory development, and knowledge sharing via mobile applications using MOOCs;Frontiers in Education;2023-04-27

2. MDFA: A New Multiple Dynamic Flip Algorithm for Mobile-based Apps Development;2022 IEEE 18th International Colloquium on Signal Processing & Applications (CSPA);2022-05-12

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