Adaptive Multimedia Learning Framework with Facial Recognition System
– Adaptive Multimedia Learning Framework with Facial Recognition System –
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ABSTRACT
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 major modules 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 academic learning process.
This was based on the fact that adaptive decisions can be made to protect learner enthusiasm, promote learning grid and enhances general understanding of an adaptive learning environment if user’s immediate behavior and concern is well considered.
This approach implements facial expression recognition on a smart phone (Android) using effective 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.
INTRODUCTION
An adaptive learning system refers to an academic environment for teaching, learning, managing courses, and storing user data; which helps in a better understanding of the user’s learning behaviour and preferences.
More importantly, it applies the user’s data to adapt and personalise the various visible aspects of the system, according to the user. Adaptive learning systems tailor the learner’s experience to suit individual needs.
The adaptive learning frameworks provide an environment where adaptation and customization are achieved, in order to improve the learning process.
Generally, the adaptive learning framework extends and includes the benefits derived from the traditional Learning Management Systems (LMS); and learner personalized support in a distance learning setting.
Cognitive Computing and Computer Vision
Cognitive computing (CC) describes technology platforms that, broadly speaking, are based on the scientific disciplines of Artificial Intelligence (AI), and image and signal processing.
These platforms encompass machine learning, reasoning, natural language processing, speech and vision recognition (Object Recognition), and human-computer interaction.
Computer vision (CV) is an interdisciplinary field that deals with how computers can be formulated to gain high-level understanding from digital images or videos.
Tasks include methods for acquiring, processing, analysing and understanding digital images, and extraction of high-dimensional data from the real-world in order to produce numerical or symbolic information.
REFERENCES
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Choi, H.-C. and Oh, S.-Y. (2006b). Real-time Recognition of Facial Expression using Active Appearance Model with Second Order Minimization and Neural Network. 2006 IEEE International Conference on Systems, Man and Cybernetics, pages 1559–1564.
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Davenport, J. L., Yaron, D., Klahr, D., and Koedinger, K. (2008). When do dia-grams enhance learning? A framework for designing relevant representations. Proceedings of the 8th International Conference on the Learning Sciences, pages 191–198.
CSN Team.
