Human-robot scaffolding, an architecture to support the learning process

Recognizing and diagnosing the learner’s cognitive and emotional state to intervene assertively during the learning process is a condition of the social robots in educational contexts. A cognitive architecture to manage the robot social behavior with handling capacity is presented. The architecture has three modules: recognition, diagnosis, and intervention. The first recognizes emotional, cognitive, and mechanical assembly task. The second makes sense of the user’s cognitive and emotional state according to learning’s task state. The third configures the actions of the robot according to the flow theory, which establishes a relation during the learning between challenge and development of skills. The proposed architecture contributes to the field of human-robot interaction by suggest an architecture that seeks the robot’s proactive behavior according to the learner’s needs.