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Prediction of Learning Abilities Based on a Cross-Modal Evaluation of Non-verbal Mental Attributes Using Video-Game-Like Interfaces

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Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5641))

Abstract

The authors propose the thesis that today’s children immersed in cyberspace need to rely on different skills and mental attributes in order to interact successfully with knowledge. It is argued that learning pedagogies as well as corresponding assessment tools must comply with the multi-modality principle. The paper describes a multimodal evaluation of the learning potential and reading/learning abilities of young children’s brains. The method is based on the assessment of non-verbal abilities using video-game-like interfaces. The results show that the ability to orientate and navigate, to sequence or categorize objects or events, as well as to discriminate visual and auditory stimuli and the short-term visual and auditory memory can predict reading and learning abilities. Moreover, the combined assessment of several independent modalities significantly increases the predictive power.

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Laouris, Y., Aristodemou, E., Makris, P. (2009). Prediction of Learning Abilities Based on a Cross-Modal Evaluation of Non-verbal Mental Attributes Using Video-Game-Like Interfaces. In: Esposito, A., Vích, R. (eds) Cross-Modal Analysis of Speech, Gestures, Gaze and Facial Expressions. Lecture Notes in Computer Science(), vol 5641. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03320-9_24

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  • DOI: https://doi.org/10.1007/978-3-642-03320-9_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-03319-3

  • Online ISBN: 978-3-642-03320-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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