Model-based optimisation for enhanced training of individuals based on abilities, learning styles and preferences

[摘要] Computer based training of individuals is becoming more common. Computer basedsystems increasingly are filled with devices and appliances that enhance the user’s interactionwith the computer. These new devices and appliances present new modalitiesof interaction with the user. This opens new possibilities for computer based training.However, not much is known about mapping these modalities to the user for enhancedlearning. This thesis presents an artificial learning model for on-line training of individuals.The model supplied is a multi-modal system in that it links multiple input andoutput modalities to a user profile. The model contains a non-linear mapping betweenthe user profile and the modalities. The non-linear mapping has been achieved throughthe use of an Artificial Neural Network. The learning model has been extended to includetime dependencies of the suggested modalities via a feedback mechanism within the ArtificialNeural Network. The presented results indicate the complexity in choosing the mostappropriate mapping for an individual. Results are presented showing the robustness ofthe learning model. By taking cognisance of the user profile and context (e.g. the user isbored or tired) appropriate modalities are suggested which facilitate learning.

[发布机构] University of the Witwatersrand