Abstract
Few robotic adaptive architectures can be programmed by the teachers and used in school environments as a regular tool for teaching, compared to other information systems. This paper describes an experiment in a school environment. The experiment aimed to analyze the benefits of a cognitive adaptive system, which controls a social robot for educational activities, for teaching. The system performance was evaluated based on three criteria: (i) teachers perceptions in using the system, (ii) students perception with regard to the robot and (iii) the system accuracy. Teachers and students perceptions were obtained by means of questionnaires and the system's accuracy was evaluated by manual validation. Overall, the outcomes suggest that the teachers and students identified the benefits of the system for teaching. Furthermore, the system's classifications of verbal answers showed itself efficient when the answers were rightly understood by the speech recognizer.
Recommended Citation
Tozadore, Daniel; Hannauer Valentini, João Pedro; Rodrigues, Victor Henrique; Pazzini, Julia; and ROMERO, Roseli, "When Social Adaptive Robots meet School Environments" (2019). AMCIS 2019 Proceedings. 4.
https://aisel.aisnet.org/amcis2019/cognitive_in_is/cognitive_in_is/4
When Social Adaptive Robots meet School Environments
Few robotic adaptive architectures can be programmed by the teachers and used in school environments as a regular tool for teaching, compared to other information systems. This paper describes an experiment in a school environment. The experiment aimed to analyze the benefits of a cognitive adaptive system, which controls a social robot for educational activities, for teaching. The system performance was evaluated based on three criteria: (i) teachers perceptions in using the system, (ii) students perception with regard to the robot and (iii) the system accuracy. Teachers and students perceptions were obtained by means of questionnaires and the system's accuracy was evaluated by manual validation. Overall, the outcomes suggest that the teachers and students identified the benefits of the system for teaching. Furthermore, the system's classifications of verbal answers showed itself efficient when the answers were rightly understood by the speech recognizer.