Abstract
In this paper, we propose the use of a robot platform for helping teachers and students in classrooms and at homes without degrading the academic achievement. We hypothesized that the robot can teach the same contents without degrading the academic achievement. In addition, it can improve the quality of teaching, mixing teaching with fun to attract students’ attention, repeat the contents without fatigue or anger and also providing pupils with special needs with the right contents in the right time. In this paper a 24 degrees of freedom (DOF) NAO robot is used for teaching an introduction to robotics to elementary school pupils. A GUI tool is designed to help teachers to easily upload slides of the subject’s contents. The robot presents the slides by reading it while generating random movements that resemble the body language of human presenters and teachers. The robot uses its camera to count the number of faces heading to it and use it as a measure of attention. When the number goes below a threshold number, the robot refreshes the classroom by automatically switching from teaching mode into entertainment mode where it dances, sings, tells a story, tells jokes, etc. in a manner that to attracts the attention of the pupils. In an experiment, pupils from stages 5 and 6 are divided into two groups; one group attended the same class content with the IT teacher and the second group attended with the robot. A questionnaire is designed to evaluate pupils’ knowledge before and after attending the class. Results showed that the robot could attract students and provide them with more deeply understanding of technical terms. As a future work, different subjects will be used and more experiments will be conducted.
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Hameed, I.A., Strazdins, G., Hatlemark, H.A.M., Jakobsen, I.S., Damdam, J.O. (2018). Robots That Can Mix Serious with Fun. In: Hassanien, A., Tolba, M., Elhoseny, M., Mostafa, M. (eds) The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018). AMLTA 2018. Advances in Intelligent Systems and Computing, vol 723. Springer, Cham. https://doi.org/10.1007/978-3-319-74690-6_58
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