This chapter describes the research problems inherent the design of effective intelligent tutoring systems (ITS) based on cognitive neuroscience research (brain-based approach) and evidence-based education. Effective student-ITS interaction requires a thorough understanding of the brain processes that underpin learning. The knowledge of these principles allows you to select optimal pedagogical strategies to monitor and guide the process. AI-based tutors have great potential in constantly adapting teaching content and tactics to the changing cognitive needs of the individual student in order to foster deep understanding, increase motivation and develop a sense of self-efficacy in the learner. The brain-based approach can give ITSs a significant increase in effectiveness in promoting learning.
Design Intelligent Tutoring Systems with AI: Brain-based principles for learning effectiveness
Roberto Trinchero
2021-01-01
Abstract
This chapter describes the research problems inherent the design of effective intelligent tutoring systems (ITS) based on cognitive neuroscience research (brain-based approach) and evidence-based education. Effective student-ITS interaction requires a thorough understanding of the brain processes that underpin learning. The knowledge of these principles allows you to select optimal pedagogical strategies to monitor and guide the process. AI-based tutors have great potential in constantly adapting teaching content and tactics to the changing cognitive needs of the individual student in order to foster deep understanding, increase motivation and develop a sense of self-efficacy in the learner. The brain-based approach can give ITSs a significant increase in effectiveness in promoting learning.File | Dimensione | Formato | |
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