Search

AbstractAlthough the existing research on educational robots has exhibited the assistance for EFL learners’ English skills, the evidence which shows robot-assisted systems’ effect on adult learners’ English read-aloud is still rare. Nevertheless, read-aloud is still treated as a useful approach in English classes for speech pronunciations in particular in Asia. This study aims at the design of a system that uses a robot as a tutor equips automatic speech recognition to diagnose learners’ errors while they are reading aloud the English passages. The learner is able to practice and improve pronunciations via the diagnosis. An experiment designed with a pretest, a posttest, and a delayed posttest was conducted to evaluate the proposed robot-tutoring system. 19 university students in Taiwan enrolled in the experiment, and learned with the system for 90 minutes per round, with a total of 2 rounds of self-learning. The results showed the participants’ accuracy of read-aloud in the delayed posttest was significantly better than those of the pretest and immediate posttest. In addition, when looking into the investigation of the participants’ perceptions of the system, most were impressed by the system, and also agreed the system was a useful and helpful tool to help reading English passages aloud. Therefore, this study provides evidence of the effects of robot-tutoring approach on adults’ English read-aloud in Taiwan.

This study aims to determine the impact of educational robot on increasing English vocabulary as a foreign language. Pre-experimental research design was conducted with 35 first grade junior high school students as sample. The pre-post English vocabulary test was given to the sample and the research were done in eight meetings. In the control class there was no action treatment and did not use robots in learning but in the treatment class, researchers used educational robots, namely the Evoce robot in learning. From the comparison between the two classes both the control class and the treatment class from the pre and post English vocabulary tests, the result finding showed in the t-test score based on the value of df = 35-1 = 34 at a significant level of 5%, a ttable of 1.0691 is obtained and at a significant level of 1%, a ttable of 2.441 is obtained. With a tcount of 9.899, which means that it is greater than ttable at a significance level of 5% and 1%, (1.0691 < 9.899 > 2.441) then Ho is rejected and Ha is accepted. In summary, the Evoce robot has given contribution in young learners’ English vocabulary. It recommended that the educational robot may become one of alternative media to be used for recent days for English vocabulary class.

Bu araştırmada kodlama eğitiminde eğitsel robot kullanımının, özel yetenekli öğrencilerin bilgi işlemsel düşünme becerisine etkisini incelemek amaçlanmıştır. Araştırmada deneysel yöntemler içerisinde yer alan kontrol gruplu ön test son test yarı deneysel desen kullanılmıştır. Araştırmanın çalışma grubu 2021-2022 eğitim öğretim yılında Konya ili Selçuklu ilçesinde bulunan bir Bilim ve Sanat Merkezine devam eden özel yetenekli 5. Sınıf öğrencileri oluşturmuştur. Araştırmaya kontrol grubunda 55 ve deney grubunda 55 olmak üzere toplam 110 öğrenci katılmıştır. Araştırmada öğrencilerin bilgi işlemsel düşünme düzeylerini belirlemek amacıyla, deney ve kontrol gruplarında ön test ve son test olarak, Korkmaz, Çakır ve Özden (2015) tarafından geliştirilen Bilgisayarca Düşünme Beceri Düzeyleri Ölçeği kullanılmıştır. Uygulama sürecinde deney grubu öğrencileri ile kodlama eğitimi blok tabanlı kodlama aracı mBlock ve eğitsel robot seti mBot kullanılarak gerçekleştirilmiştir. Kontrol grubunda ise, kodlama eğitimi blok tabanlı kodlama aracı mBlock kullanılarak gerçekleştirilmiştir. Deney ve kontrol grubunda aynı blok tabanlı kodlama yazılımı olan mBlock blok tabanlı kodlama yazılımı tercih edilmiştir. Araştırmadan elde edilen bulgular şu şekildedir: 1.Kodlama eğitiminde eğitsel robot kullanılan deney grubu öğrencilerin bilgi işlemsel düşünme becerilerinde uygulama sonunda artış olduğu görülmüştür. 2. Kodlama eğitimlerinde eğitsel robot kullanılmayan kontrol grubu öğrencilerinin de bilgi işlemsel düşünme becerileri son test puanlarında uygulama sonunda artış olduğu görülmüştür. 3.Deney ve kontrol grubu öğrencilerinin bilgi işlemsel düşünme erişleri karşılaştırıldığında meydana gelen farkın kodlama eğitiminde eğitsel robot kullanılan deney grubu öğrencilerinin lehine olduğu görülmüştür.

In recent years, the national policy has strongly promoted the integration of artificial intelligence technology and the field of education. In response to the national policy’s call, this paper proposes a robot-assisted teaching model. Taking the coordinate transformation model, velocity motion model, odometry motion model, and visual and auditory recognition model as design principles of the educational robot, the design of the educational robot is materialized by borrowing relevant hardware and programming software. The robot-assisted preschool education teaching model was created to explain the role of educational robots in preschool education. The research subjects were selected, and the teaching effect of robot-assisted preschool education was analyzed by combining theoretical knowledge of statistics. After the experimental intervention, in terms of learning quality, language expression ability, and cooperative literacy, there was a significant difference between the early childhood students in Group B and Group C, with P

Existing methods for scoring student presentations predominantly rely on computer-based implementations and do not incorporate a robotic multi-classification model. This limitation can result in potential misclassification issues as these approaches lack active feature learning capabilities due to fixed camera positions. Moreover, these scoring methods often solely focus on facial expressions and neglect other crucial factors, such as eye contact, hand gestures and body movements, thereby leading to potential biases or inaccuracies in scoring. To address these limitations, this study introduces Robotics-based Presentation Skill Scoring (RPSS), which employs a multi-model analysis. RPSS captures and analyses four key presentation parameters in real time, namely facial expressions, eye contact, hand gestures and body movements, and applies the fuzzy Delphi method for criteria selection and the analytic hierarchy process for weighting, thereby enabling decision makers or managers to assign varying weights to each criterion based on its relative importance. RPSS identifies five academic facial expressions and evaluates eye contact to achieve a comprehensive assessment and enhance its scoring accuracy. Specific sub-models are employed for each presentation parameter, namely EfficientNet for facial emotions, DeepEC for eye contact and an integrated Kalman and heuristic approach for hand and body movements. The scores are determined based on predefined rules. RPSS is implemented on a robot, and the results highlight its practical applicability. Each sub-model is rigorously evaluated offline and compared against benchmarks for selection. Real-world evaluations are also conducted by incorporating a novel active learning approach to improve performance by leveraging the robot’s mobility. In a comparative evaluation with human tutors, RPSS achieves a remarkable average agreement of 99%, showcasing its effectiveness in assessing students’ presentation skills.

Obesity is a chronic multifactorial pathology determined by many factors, including incorrect eating habits and a low level of physical activity. There is an urgent need to promote a persistent change in lifestyle in obese subjects, but very few individuals maintain long-term results achieved after diet therapies. Therapeutic Education (TE) has taken over an important role as a multidisciplinary intervention aimed at improving lifestyle and at acquiring new skills for the management of the disease. However, only a small portion of patients can maintain participation in such programs and fully benefit from them. Assistive technologies, and in particular assistive social robots, are powerful tools to boost independence and improve participation in educational activities. The aim of the research work described in this article is to evaluate the effect of employing a social robot as a therapeutic educational robot helping the expert therapist in the education activity. This article describes the implementation, deployment, and evaluation of a social educational robot used as a TE assistant. Although we cannot provide statistically significant results due to the limited number of people involved in the experimental protocol, all experimental results show a positive trend, indicating that the robot can enhance the social interactions between the patients and the therapist and among the patients, thus bringing to better overall results of the TE sessions, measured with standard tests for obesity management.

Aimed at the poor recognition effect of current educational robots on objects with complex shapes and colors and the single design of related experiments, this paper proposes a robot teaching instrument. The robot adopts a servo motor with an encoder, a drive, and a variety of sensors to realize a motor current loop, speed loop, position loop, and closed-loop control functions. Three experimental schemes were designed: a PID adjustment experiment, a robot obstacle avoidance and object-grasping program writing experiment, and a complex object recognition experiment based on cascade classifiers. The robot is conducive to improving students’ self-initiative ability, deepening their understanding of PID closed-loop control, multi-sensor fusion, and deep learning knowledge. It can improve students’ programming ability, enabling them to effectively combine theory and practice, as well as to comprehensively apply professional knowledge.

Research in psychology, pedagogy, and physiology has shown that learning a second language will be a great benefit to preschool children. Compared with adults, children have more advantages in learning, such as better pronunciation and intonation. However, because of children’s inattention, the effects of the second language education in many preschools are not ideal in China. To make children learn the second language effectively, it should be integrated into their daily lives and in line with their interests. In this paper, an educational robot system with object recognition technology is introduced, which aims to provide innovative second language learning services for preschool children in China. The proposed system combines object recognition and projection with English teaching and makes objects in daily life more interesting with projected animation to attract children’s attention. On the projection screen, children can interact with a robot by touch or movement and can easily trigger more interactive effects. To evaluate the effectiveness of the proposed system, we conducted an experiment, and the results showed that the system can improve the language learning efficiency for the Chinese preschool children by interacting with objects under proper guidance.

Due to the pandemic caused by the COVID-19, we are forced to maintain a social distance, relying on technology such as the use of robots for both commercial and educational activities. This document is a systematic review of scientific literature using Prism methodology and aims to determine the best characteristics for the development of educational robots in children on infectious disease care. We obtained 50 articles associated to the research topic collected from databases such as IEEE Xplore, Scielo, Scopus and WoS. The results were synthesized in different tables and graphs separated in approaches of: robotics in education, robotics in relation to humans, education in diseases, robotics in health and digital applications in education, where the first one is the most treated in the articles found.

This article presents a methodology to recycle and upgrade a 4-DOF educational robot manipulator with a gripper. The robot is upgraded by providing it an artificial vision that allows obtaining the position and shape of objects collected by it. A low-cost and open-source hardware solution is also proposed to achieve motion control of the robot through a decentralized control scheme. The robot joints are actuated through five direct current motors coupled to optical encoders. Each encoder signal is fed to a proportional integral derivative controller with anti-windup that employs the motor velocity provided by a state observer. The motion controller works with only two open-architecture Arduino Mega boards, which carry out data acquisition of the optical encoder signals. MATLAB-Simulink is used to implement the controller as well as a friendly graphical interface, which allows the user to interact with the manipulator. The communication between the Arduino boards and MATLAB-Simulink is performed in real-time utilizing the Arduino IO Toolbox. Through the proposed controller, the robot follows a trajectory to collect a desired object, avoiding its collision with other objects. This fact is verified through a set of experiments presented in the paper.