A computer-based training system for automatically selecting a learning strategy, the training system comprising a computer and data acquisition means, the data acquisition means being connected to the computer, wherein the memory stores information specific to the user-entity, the computer comprising: - a display; - a processor; and - a memory coupled to the processor, the memory storing instructions (604, 606, 608, 610) adapted to be executed by the processor to: o present a first training section associated with at least one first stored learning strategy, o gather quantitative data about the first training section with respect to a user-entity, the gathering of the quantitative data comprising: acquiring a sequence of images using the data acquisition means from a predefined body part of the user-entity and acquiring brainwave data from the user-entity using the data acquisition means during the first training section, the predefined body part being an eye of the user-entity, extracting the eye movement using the acquired images, analyzing the extracted eye movement in order to determine the eye movement frequency during the first training section, and filtering eye movement frequency data to provide the quantitative data that is descriptive of the eye movement, the eye movement being indicative of learning effectiveness of the user-entity, o combining by a weighted linear combination the quantitative data provided on the basis of the image acquisition with further quantitative data comprising the brainwave data to provide resultant quantitative data, o evaluate the resultant quantitative data to determine a learning effectiveness of the at least one first learning strategy for the user-entity, o select at least one stored second learning strategy as part of the information specific to the user-entity based on the determined learning effectiveness of the at least one first learning strategy for the user-entity, and o present on the display a second training section associated with the at least one second learning strategy to the user-entity. - a display; - a processor; - a memory coupled to the processor, the memory storing instructions (604, 606, 608, 610) adapted to be executed by the processor to: o present a first training section associated with at least one first stored learning strategy, o gather quantitative data about the first training section with respect to a user-entity, the gathering of the quantitative data comprising: acquiring a sequence of images using the data acquisition means from a predefined body part of the user-entity and acquiring brainwave data from the user-entity using the data acquisition means during the first training section, the predefined body part being an eye of the user-entity, extracting the eye movement using the acquired images, analyzing the extracted eye movement in order to determine the eye movement frequency during the first training section, and filtering eye movement frequency data to provide the quantitative data that is descriptive of the eye movement, the eye movement being indicative of learning effectiveness of the user-entity, o combining by a weighted linear combination the quantitative data provided on the basis of the image acquisition with further quantitative data comprising the brainwave data to provide resultant quantitative data, o evaluate the resultant quantitative data to determine a learning effectiveness of the at least one first learning strategy for the user-entity, o select at least one stored second learning strategy as part of the information specific to the user-entity based on the determined learning effectiveness of the at least one first learning strategy for the user-entity, and o present on the display a second training section associated with the at least one second learning strategy to the user-entity. o present a first training section associated with at least one first stored learning strategy, o gather quantitative data about the first training section with respect to a user-entity, the gathering of the quantitative data comprising: acquiring a sequence of images using the data acquisition means from a predefined body part of the user-entity and acquiring brainwave data from the user-entity using the data acquisition means during the first training section, the predefined body part being an eye of the user-entity, extracting the eye movement using the acquired images, analyzing the extracted eye movement in order to determine the eye movement frequency during the first training section, and filtering eye movement frequency data to provide the quantitative data that is descriptive of the eye movement, the eye movement being indicative of learning effectiveness of the user-entity, o combining by a weighted linear combination the quantitative data provided on the basis of the image acquisition with further quantitative data comprising the brainwave data to provide resultant quantitative data, o evaluate the resultant quantitative data to determine a learning effectiveness of the at least one first learning strategy for the user-entity, o select at least one stored second learning strategy as part of the information specific to the user-entity based on the determined learning effectiveness of the at least one first learning strategy for the user-entity, and o present on the display a second training section associated with the at least one second learning strategy to the user-entity.