A COMPREHENSIVE FRAMEWORK FOR DESIGN AND EVALUATION OF M-LEARNING APPLICATIONS

Abstract

Human-computer interaction (HCI) communities and Mobile Learning Communities (MLCs) are well aware of the challenges that mobile devices impose when it comes to conducting proper usability and user experience evaluations for M-learning applications. So far there has been limited research on finding appropriate design and evaluation frameworks/methods that can be applied to the usability and user experience of M-learning applications. This thesis proposes a robust framework for mobile learning design and evaluation based on a mobile learning project that developed M-learning apps to train employees in the workplace. Cognitive tests (pre-test/post-test) questionnaires, usage data, and follow-up interviews were used to collect qualitative and quantitative data on learning effectiveness and learner experience with the application. The experimental results and analysis of the collected data demonstrate that the newly proposed framework is a robust framework that can help in designing an efficient, effective and user-friendly M-learning applications that are geared towards creating a better user learning experience.