An Algorithm for Providing Adaptive Behavior to Humanoid Robot in Oral Assessment

Abstract

Assistance humanoid robots (AHR) are the category of robotics used to offer social interaction to humans. In higher education, the teaching staff supports the acceptance of AHRs as a social assistance tool during the learning activities, with the whole responsibility of the correct operation of the device and providing a more comprehensive view of the objectives and significance of AHR use. On the other hand, students deal with AHRs either as a friend or control figures as a teacher. This paper presents an algorithm for AHRs in oral assessments. The proposed algorithm focuses on four characteristics: adaptive occurrence, friendly existence, persuasion, and external appearance. This paper integrates AHRs in higher education to improve the value of psychological and social communication during oral assessment where can assist students in dealing with challenges, such as shyness, dissatisfaction, hesitation, and confidence, better than a human teacher can. Thus, AHRs have increased students’ self-confidence and enriches active learning