Viktors Zagorskis and Atis Kapenieks
Distance Education Study Centre, Riga Technical University, Kronvalda 1, Riga, Latvia
Cognitive Energy, E-leaning Quality, Computer Agent, Virtual Student.
Data analysis in Virtual Learning Environment deepens the understanding of cognition processes in real student’s brain. The challenge is the evaluation of the quality of e-learning courses before the large-scale implementation. With this aim, we formulate the concept for a computer model for Virtual Student’s evolution. We combine knowledge elements explored from learners behavior data and cognitive theories. We assume that some of the brains energy flow expenses in learning and memorization are due to energy extraction for applying existing skills, analysis of accumulated knowledge, and adaptation of newly available information. We argue that the proposed Virtual Student model can perform cognitive energy flow modeling by extracting energy from the environmental learning objects and losing the power in a tedious learning process. The re- search shows that Cognitive Energy Flow model can be computerized to produce synthetic data to improve e-learning courses and predict real student’s behavior.