Memory Load and Performance-based Adaptive Smartphone E-learning Framework for E-commerce Applications in Online Learning

Abstract

The term e-commerce is not confined to the purchase and sale of goods only. There are several occasions where students are not able to comprehend any idea on their own. With the availability of online learning platforms such as Massive Open Online Courses (MOOCs) and Virtual Learning Environments (VLEs), students may visit online Internet sites, where various articles are made available with a single click. With mobile devices in their hands, they can also listen to the presentations of different academics from anywhere and at any time. In an online learning environment, it is challenging to provide tailored learning content to students that fulfill their needs and requirement. Therefore, we in this research paper propose an adaptive smartphone learning framework. The framework first considers students’ academic performance, preferred learning content, and memory load i.e., cognitive characteristics. Based on students’ academic performance, preferred learning content, and memory load, appropriate adaptive and motivational triggers are sent on students’ smartphones to guide and motivate them in their learning process. We have introduced ten types of adaptive triggers that in different scenarios will be presented to students to help them in remembering important learning points. Furthermore, performance-based motivational triggers in connection with adaptive triggers are also introduced. These motivational triggers are sent on students’ smartphones for giving them a suggestion, hope, appreciation, and warnings during their studies. In this study, we also show how different students’ learning scenarios are created and how our framework deals with those scenarios in students’ learning process.