Adaptive multimedia learning framework with facial recognition system

Recent breakthrough in mobile technology, wireless communication and sensing ability of smart devices promote the ease to detect real-world learning status of students as well as the context aware for learning. Targeted information can be provided to individual students in the right place and at the right time. This work is one of the three main components of our Smart Learning Framework, others include Multimedia Module Contents (MMC) and Learning Style Index (LSI). However, this module of our work aimed to perfect efforts to correctly make decision during an educational learning process. This was based on the fact that adaptive decisions can only be made to protect learner enthusiasm, promote learning grid and enhances general understanding of an adaptive learning environment if users immediate behavior and concern is well considered. This approach implements facial expression recognition on a smart phone (android) using effectiva SDK. This enables correct detection of facial expression for further understanding of the meaning in a learning environment. The output of this module is used for Learners Behavior Analysis which then provide result of general evaluation of individual learner.