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Adaptive multimedia learning framework with facial recognition system

机译:具有面部识别系统的自适应多媒体学习框架

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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.
机译:智能技术在移动技术,无线通信和感应能力方面的最新突破,使人们更容易检测学生的现实世界学习状况以及感知学习的环境。可以在正确的位置和正确的时间向有针对性的学生提供有针对性的信息。这项工作是我们智能学习框架的三个主要组成部分之一,其他包括多媒体模块内容(MMC)和学习风格索引(LSI)。但是,我们的工作模块旨在完善在教育学习过程中正确做出决定的努力。这是基于以下事实:如果充分考虑了用户的直接行为和关注,则只能做出适应性决策来保护学习者的热情,促进学习网格并增强对适应性学习环境的一般理解。这种方法使用effectiva SDK在智能手机(android)上实现面部表情识别。这使得能够正确检测面部表情,以进一步理解学习环境中的含义。该模块的输出用于学习者行为分析,然后提供对单个学习者的总体评估结果。

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