Abstract
In online learning is more difficult for teachers identify to see how individual students behave. Student’s emotions like self-esteem, motivation, commitment, and others that are believed to be determinant in student’s performance can not be ignored, as they are known (affective states and also learning styles) to greatly influence student’s learning. The ability of the computer to evaluate the emotional state of the user is getting bigger attention. By evaluating the emotional state, there is an attempt to overcome the barrier between man and non-emotional machine. Recognition of a real time emotion in e-learning by using webcams is research area in the last decade. Improving learning through webcams and microphones offers relevant feedback based upon learner’s facial expressions and verbalizations. The majority of current software does not work in real time – scans face and progressively evaluates its features. The designed software works by the use neural networks in real time which enable to apply the software into various fields of our lives and thus actively influence its quality. Validation of face emotion recognition software was annotated by using various experts. These expert findings were contrasted with the software results. An overall accuracy of our software based on the requested emotions and the recognized emotions is 78%. Online evaluation of emotions is an appropriate technology for enhancing the quality and efficacy of e-learning by including the learner´s emotional states.
Highlights
Today, ICT are fundamental for our society
Development of adaptive techniques for the sphere of e-learning systems, which allow for personalization of the student, has been known for long [18]
Previous software primarily dealt with offline emotion recognition that cause post-processing of the learner’s data [1]
Summary
ICT are fundamental for our society. Their task is to make information accessible from every place in the world, quickly and without effort [47]. Wide spectrum of opportunities and open space for experimenting allows us applying our creativity on the topmost level [12], [31] Such system of learning by means of ICT, for example in cooperation with the Existing methods for gathering affective user data, like psychological sensors and questionnaires, are either obtrusive or discontinuous. They can hamper learning as well as issues in its suitability for elearning [16], [41]. Previous software primarily dealt with offline emotion recognition that cause post-processing of the learner’s data [1] They have a couple of limitations that mainly restrict their application context and might impede their accuracy. Emotions are a critical component of effective learning and problem solving, especially when it comes to interacting with computer-based learning environments
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