Because of the heath measures taken during the outbreak of Covid-19, the lack of educational methods has become the primary concern among educational professionals who have been using technology as a motivational tool. Gamification is very important because it helps students to represent their study contents and enrich their experiences of higher education when learning in-person is unavailable during the Covid-19 period. This study seeks to present an Android-based gamification app to evaluate the effect of using gamification and e-quizzes on college students' learning. We used the visual blocks language from the MIT App Inventor platform to develop an application, available at (https://play.google.com/store/apps/details?id=appinventor.ai_mekomerofofo. projectGamification). The participants were students from level 2 who used digital lessons for learning MATLAB. The study included gamified learning and non-gamified learning, both integrated into lesson plans, to investigate the differences in learners' performance. Two types of quizzes were used for instruction: gamified e-quizzes and paper-based quizzes. The outcomes plainly showed that using the new gamified e-quiz was more effective than using paper-based quizzes. They are better for assessing the learning performance of the students in question, specifically in terms of formative assessment. It is very important for instructors to apply games as a modern and innovation-oriented tool through which students can be engaged in an attractive, competitive experience.
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' selfconfidence and enriches active learning.
The development of emotional intelligence robotics in the learning environment plays valuable support for social interaction among students. Emotional intelligence robots should be scalable to recognize emotions, appear empathetic in learning situations, and enrich the confidence with students for active interaction. This paper presents some related issues about integrating emotional intelligence robotics in E-learning such as its role and outcomes to motivate interaction during education and discover the main aspects of the emotional intelligence between humans and robots. This paper aims to determine the design requirements of emotional robots. Besides, this paper proposed a framework of educational Robotics with Emotional Intelligence in Learning (EREIL). EREIL consists of three main units; student emotions discovery, student emotions representation, and EREIL-Student Communication (RSC). In addition, it introduces a perception of EREIL working. In the future, this paper tries to merge more sensor devices and machine learning algorithms to integrate face analysis with speech recognition. Besides, it can add a persuasion unit in the EREIL robot to convince students with better learning choices to their abilities.
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