Educational Robotics Research Articles

Research Hotspots and Trends of Social Robot Interaction Design: A Bibliometric Analysis

(1) Background: Social robot interaction design is crucial for determining user acceptance and experience. However, few studies have systematically discussed the current focus and future research directions of social robot interaction design from a bibliometric perspective. Therefore, we conducted this study in order to identify the latest research progress and evolution trajectory of research hotspots in social robot interaction design over the last decade. (2) Methods: We conducted a comprehensive review based on 2416 papers related to social robot interaction design obtained from the Web of Science (WOS) database. Our review utilized bibliometric techniques and integrated VOSviewer and CiteSpace to construct a knowledge map. (3) Conclusions: The current research hotspots of social robot interaction design mainly focus on #1 the study of human–robot relationships in social robots, #2 research on the emotional design of social robots, #3 research on social robots for children’s psychotherapy, #4 research on companion robots for elderly rehabilitation, and #5 research on educational social robots. The reference co-citation analysis identifies the classic literature that forms the basis of the current research, which provides theoretical guidance and methods for the current research. Finally, we discuss several future research directions and challenges in this field.

The Impact of Early Robotics Education on Students' Understanding of Coding, Robotics Design, and Interest in Computing Careers.

Early robotics education has been sparsely researched, especially for children in elementary education. This research pertains to an early education study that introduced robotics design and programming to children in early education with the purpose of increasing their robotics design knowledge, improving their coding skills, and inspiring their aspirations for future careers. It represents a seven-year study of students ages seven through ten years in a large urban school district. The study engaged a pre-post program comparison of the robotics and coding intervention that focused on children's improved understanding of robotics in addition to their career aspirations. The study resulted in increases in the participating students' understanding of robotics design as well as improved coding skills in robotics contexts. Furthermore, the study also led to increases in the students' career aspirations toward computing fields.

The cognitive effects of computational thinking: A systematic review and meta-analytic study

In this paper, we review and meta-analyze the findings of experimental studies published between 2006 and 2022 that examined the effects of coding and programming interventions on children's core and higher order executive functions (response inhibition, working memory, cognitive flexibility, planning and problem solving). The systematic review and meta-analysis aimed to address three research questions: 1) Which executive functions are most impacted by the teaching of CT? 2) Which instructional modality (educational robotics/virtual coding/unplugged coding) is most effective in enhancing executive function skills in learners aged 4–16 years? and 3) Does the cognitive effectiveness of coding vary with children's age? A total of 19 studies with 1523 participants met the selection criteria for the systematic review. The meta-analysis included 11 of those studies. The results reveal beneficial effects of structured virtual and tangible coding (educational robotics) activities for preschoolers and first graders, and significant effects of more unstructured virtual coding activities (e.g., Scratch-based) for older students. A multivariate fixed-effects model meta-analysis shows that the teaching of coding significantly improves problem-solving with the highest effect (dppc2 = 0.89), but also planning (dppc2 = 0.36), and inhibition and working memory with lower effects (dppc2 = 0.17, dppc2 = 0.20).

Information Communication Technology (ICT) and Education

COVID-19 has accelerated the shift to blended or fully online learning environments, enforcing educational institutions to embrace technology and offer their students an online or at least blended learning experience [...]

Unibotics: open ROS-based online framework for practical learning of robotics in higher education

Unibotics: open ROS-based online framework for practical learning of robotics in higher education

Assessing Computational Thinking, Motivation, and Grit of Undergraduate Students Using Educational Robots

Educational technologists and practitioners have made substantial strides in developing affordable digital and tangible resources to support both formal and informal computer science instruction. However, there is a lack of research on practice-based assignments, such as Internet of Things (IoT) projects, that allow undergraduate students to design and demonstrate educational robots using digital or physical assistance, especially when it comes to computational thinking (CT) and programming skills development in association with their psycho-emotional experience. This study compares the impact of Scratch and LEGO® WeDo robotic kits on students' CT and programming skills development. A quasi-experimental approach was conducted, involving two hundred forty-six participants ( n = 246), who were equally divided between Scratch and LEGO® WeDo groups. Results indicate that the LEGO® WeDo group showed greater improvement in CT and programming skills development, while designing and presenting IoT projects. Nevertheless, no significant association between motivation, grit, and CT skills was observed. The findings highlight the potential of tangible robotics in facilitating students’ hands-on learning and enhancing motivation to foster CT and programming skills. This study provides a wide range of implications for instructional designers on how to use tangible robotics to support hands-on IoT projects in computer science courses.

Engaging Young Students in Effective Robotics Education: An Embodied Learning-Based Computer Programming Approach

Robotics education has received widespread attention in K-12 education. Studies have pointed out that in robotics courses, learners face challenges in learning abstract content, such as constructing a robot with a good structure and writing programs to drive a robot to complete specific learning tasks. The present study proposed the embodied learning-based computer programming approach and applied it to the LEGO Mindstorms EV3 robotics course. To evaluate its effectiveness, a quasi-experiment was conducted in one public primary school to explore its effects on students’ learning achievement, learning motivation, learning attitudes, learning engagement, and cognitive load. The experimental group (40 students) adopted the embodied learning-based computer programming approach, while the control group (40 students) adopted the conventional computer programming approach. The results showed that the experimental group had significantly better learning achievement in robotics than the control group, and that there was no significant difference in the cognitive load of the two groups. In terms of learning motivation, although both groups showed improvement, the experimental group had higher intrinsic learning motivation. In addition, the experimental group outperformed the control group with regard to learning attitudes and learning engagement (including cognitive, behavioral, and emotional engagement). Accordingly, this study could contribute to future research for developing more effective robotics teaching approaches and computer programming activity design.

The ReFiBot makers guide: Fostering academic open science and circularity with a robotic educational kit

The advent of robotics in schools and universities curricula are preparing students to encompass new didactic fields. This article presents ReFiBot which is an education robot that has been used to increase the technical literacy on robotics and bring more awareness to open science at Wageningen University. The ReFiBot combines open-source hardware and software, integrated with a chassis made from recycled plastic from fishnets. The ReFiBot was carefully designed to be easily assembled with off-the-shelf electronic parts and programmed using the Arduino IDE. Moreover, a software library is facilitated to ease its adoption in educational activities from any curricula level. The ReFiBot has been mainly used for education but can also be used for research on swarm robotics. The CAD files, components list, software files, and tutorial within this contribution will guide the reader through the assemblage and best practices of this circular robotics kit.

Nonverbal social behavior generation for social robots using end-to-end learning

Social robots facilitate improved human–robot interactions through nonverbal behaviors such as handshakes or hugs. However, the traditional methods, which rely on precoded motions, are predictable and can detract from the perception of robots as interactive agents. To address this issue, we have introduced a Seq2Seq-based neural network model that learns social behaviors from human–human interactions in an end-to-end manner. To mitigate the risk of invalid pose sequences during long-term behavior generation, we incorporated a generative adversarial network (GAN). This proposed method was tested using the humanoid robot, Pepper, in a simulated environment. Given the challenges in assessing the success of social behavior generation, we devised novel metrics to quantify the discrepancy between the generated and ground-truth behaviors. Our analysis reveals the impact of different networks on behavior generation performance and compares the efficacy of learning multiple behaviors versus a single behavior. We anticipate that our method will find application in various sectors, including home service, guide, delivery, educational, and virtual robots, thereby enhancing user interaction and enjoyment.

Design of teaching aids in STEAM education and fuzzy hierarchical analysis of their educational effect

Focusing on problem-based learning (PBL) and the multi-disciplinary teaching of science, technology, engineering, arts, and mathematics (STEAM), we developed the evaluation tool of teaching aids in STEAM education to help students practice creative thinking and solution-finding. The fuzzy theory and the analytical hierarchy process were integrated for the evaluation of the acceptance of using robots in STEAM education. The fuzzy analytical hierarchy process (FAHP) was developed with the help of experts in education and industry who defined the goal, criteria, and alternatives (factors) of using teaching aids in STEAM education. FAHP was applied to the evaluation of three robots designed for STEAM education in this study. The result of the evaluation showed that the use of the designed robots in STEAM education was important in five criteria (structure, function, economy, aesthetic, and creativity). Among the alternatives, logic, creativity, simpleness, Avant-garde, and innovation were important for robots to be used for STEAM education. This indicated that artistic elements were important in the integration of them in STEAM education. The developed FAHP and questionnaire were useful in evaluating the acceptance of teaching aids in STEAM education. For the evaluation of the use of other teaching aids, the result of this study provides a basis and a reference for how teaching aids can be used for STEAM education.

The development of robotics courses for young children under vector space model.

Robotics education is important in training children's thinking, practical, and innovation abilities. It is significant to stimulate children's interest in learning and improve their learning quality. The existing research has not paid attention to the application of robotics education in children. It is necessary to stimulate children's interest in learning. This paper will take senior kindergarten students as the research object. It analyzes the application of the Vector Space Model (VSM) in robotics course development. The research and development of children's robotics courses incorporating Artificial Intelligence technology are based on the survey results of robotics courses offered by 38 kindergartens in Baoji City. An automatic document classification system based on VSM is designed to assist in compiling robotics teaching textbooks. Finally, the system performance is tested. The results show that about 24% of kindergartens offer robotics courses, and 76% do not. Besides, 70.14% of teachers support the establishment of children's robotics courses. The classification effect of the VSM system is better than that of Chinese documents. This system performs better than the automatic document classification system based on Term Frequency-Inverse Document Frequency. Its classification accuracy, recall, and F1 value are all above 85%. The development of the robotics course provides a better teaching environment for teaching young children about AI and robots. The robotics education discussed in this paper is a hot spot in the current curriculum reform and is of great significance to the development and innovation in early childhood education.

Personalised Presentation of Mathematics for Visually Impaired or Dyslexic Students: Challenges and Benefits

Artificial Intelligence in Education (AIEd) has the potential to transform learning by providing personalised and adaptive environments and enabling more effective assessment and feedback (Luckin et al., 2016). Implementing AIEd has different challenges involving accommodating different learning styles, understanding how learners interact with tools, creating accessible technology for students with learning or sensory disabilities, and managing cognitive load and stress. The potential benefits of using AIEd for the personalised presentation supports inclusive learning environments, including improved understanding, accessibility to learning (Costas-Jauregui et al., 2021), reduced stress (Hsu et al., 2021), and cognitive load (Turan & Goktas, 2016), to improve mathematical understanding and student confidence. Neto et al. (2021) argue that the opportunity to utilise robots to enhance inclusive classroom experiences lies in their ability to utilise their physical attributes, multimodal feedback systems, customised social behaviours, and sensory functions. The potential benefits promote the development of inclusive and intelligent educational frameworks. In this paper, the authors examine the potential of using AIEd combined with robotics to provide a personalised learning framework for students with learning disabilities (e.g., dyslexia) and sensory disabilities (e.g., vision impairment/blindness). The paper will assess the challenges and benefits of the AIEd framework combined with robotics for inclusive mathematics education.

Convolutional neural network model by deep learning and teaching robot in keyboard musical instrument teaching.

Keyboard instruments play a significant role in the music teaching process, providing students with an enjoyable musical experience while enhancing their music literacy. This study aims to investigate the current state of keyboard instrument teaching in preschool education, identify existing challenges, and propose potential solutions using the literature review method. In response to identified shortcomings, this paper proposes integrating intelligent technology and subject teaching through the application of teaching robots in keyboard instrument education. Specifically, a Convolutional Neural Network model of Deep Learning is employed for system debugging, enabling the teaching robot to analyze students' images and movements during musical instrument play and deliver targeted teaching. Feedback from students who participated in keyboard instrument teaching with the robot indicates high satisfaction levels. This paper aims to diversify keyboard instruments' teaching mode, introduce the practical application of robots in classroom teaching, and facilitate personalized teaching catering to individual students' aptitudes.

The Effect of Educational Robotics Applications on Students' Academic Achievement and Problem-Solving Skills in Science Education

The study explored the effects of robotic-assisted applications on the variables of academic achievement and problem-solving skills in the “Propagation of Light” unit of the 5th grade science course. The study employed the pretest-posttest control group design, one of the quasi-experimental methods. The study sample consist of 36 5th grade students attending a public school in Turkey located in a district center in the Western Black Sea region. The study was carried out in a six-week period in the 2019-2020 academic year, and 19 of the students were selected as the control and 16 as the experimental group. Robotic supported activities were applied to the students in the experimental group, and the activities prescribed by the Science Curriculum were applied to the students in the control group. Open-ended and closed-ended “Academic Achievement Test” and “Problem-Solving Skills Test” were used as pretest and posttest in both groups. The data were analyzed using the independent samples t-test. The study results revealed that the academic achievement and problem-solving skills of the students in the experimental group, in which robotic-assisted activities were used, were significantly higher in both tests compared to the students in the control group.

PENINGKATAN KEMAMPUAN TENAGA PENGAJAR ROBOTIK LPK UNIK ROBOT MENGGUNAKAN TEKNOLOGI TEPAT GUNA DAN PEMASARAN

This research includes community service which aims to improve the skills of robotics teachers in Purwokerto, Banyumas Regency. UNIK ROBOT, a robotics education institution, has partnered with schools in the area to provide robotics education through extracurricular activities. Interest in robotics from schools and students is very high, because technology and robotics increasingly dominate everyday life. Project-based education methods and action learning are the main focus, with the aim of developing 21st century skills, such as creativity, critical thinking, communication and collaboration. Evaluation of success was carried out through observation methods, oral tests, and questionnaires, which showed a significant increase in robotics and online marketing skills by 90%. It is hoped that this activity can become the basis for further development of robotics education in Purwokerto and its surroundings. The results of the research stated that educational activities for robotics teachers in Purwokerto succeeded in increasing robotics and online marketing skills by 90%. Hopefully in the future there will be robotic material that can be taught again so that learning activities can further develop.

Robots2school: telepresence-mediated learning in the hybrid classroom – experiences in education support for children during cancer treatment: a qualitative study

Children with cancer experience recurring hospitalizations and isolation during treatment, which affect their school attendance. This study explores experiences of children with cancer, their classmates, and teachers with using the telepresence robot as a learning mediator in the hybrid classroom during treatment periods. 31 children with cancer (aged 7–17 years), 30 teachers, and 118 classmates participated in interviews and 19 h of participant observations were undertaken in nine classrooms. The Agential Realism Theory and Situational Analysis framed the data analysis. There was a single overarching theme, “Telepresence robot didactic,“ and five sub-themes (Telepresence mediated learning, school-home collaboration, hybrid robot teaching, intra-actions in class, and inclusive spatiality). This study advocates the complexity of telepresence robot didactics, emphasizing that numerous human and other factors must intra-act and work simultaneously to achieve optimal learning conditions for children during cancer treatment. This includes considerations such as modality availability for the remote child; the teacher’s understanding of telepresence robot didactic and hybrid learning; the classmate’s ability to involve the remote child in groupwork; the child’s own treatment protocol, the robot’s functionalities, and spatiality in the class. Strategies for use and the systematic surveillance of telepresence robots are needed to ensure that children during cancer treatment do not lag in academic achievement. This study proposes that children with cancer can continue participating in class while hospitalized or isolated and consequently reduce social and academic setbacks.

Using STEM to Educate Engineers about Sustainability: A Case Study in Mechatronics Teaching and Building a Mobile Robot Using Upcycled and Recycled Materials

Background: Sustainable design means to base design on any systems and methods that can fulfill any of the sustainability goals: reducing waste, recycling plastics, upcycle materials, etc., and having less of an impact on the environment. Therefore, a challenge arises: how to design products based on sustainable design. This research presents a case study, about how students in a university’s design department, used sustainability practices in their projects, to adopt sustainability as a major aspect during the design process of a product. Methods: The researchers used STEM methodologies to educate and guide the students to adopt recycling and upcycling practices to design and develop an educational mobile robot for Educational Robotics and Mechatronics applications. Results: Students were encouraged to develop their problem-solving approaches when developing their designed robots, for a mechatronics project given to them. In this way, the researchers fostered the active and motivated participation of students; an increased interest was found related to several factors, including challenge, competition, group participation, and more. Conclusions: This research aimed to evidence the use of upcycled and recycled materials in product development to fulfill some of the sustainability goals. The research’s results were very promising and has sparked an ongoing research.

Employing an underwater vehicle in education as a learning tool for Python programming

AbstractGetting students motivated and interested in their education can be challenging in any classroom setting, even more so in an online learning environment. In this spectrum, educational robotics (ER) has demonstrated numerous advantages in the educational environment, not only by facilitating teaching, but also enabling the cultivation of manyfold skills, including creativity, problem‐solving, and teamwork. Meanwhile, many methods have been developed with the aid of technology to improve the teaching process and boost students' ability to learn. Blended learning is one approach that integrates conventional classroom methods with digital resources in an effort to foster students' creativity. But how can blended learning be combined with robotics? The objective of this paper is to evaluate the impact of employing an underwater vehicle, called educational underwater vehicle (EDUV), in conjunction with a dedicated programming learning platform within the context of a programming course that is offered at the high school level. In this work, this platform is utilized by students in secondary education, and a survey was conducted prior and after using the underwater vehicle's platform based on two questionnaires. The survey included 112 Greek participants, 64 males and 48 females in the age range of 14–18 years old. The experimental results show an increase in their motivation and creativity. In other words, they are more engaged in the classroom and the lesson becomes more enjoyable. More specifically, the survey revealed that most participants are familiar with computers but have limited knowledge of robotics and programming. After training on the EDUV platform, participants showed a significant increase in correct responses for Python and Blockly environments, with an average of 50.7% in four programming‐related questions. The platform also reduced “do not know” replies, which means that the student's self‐esteem increased. The paired sample T‐test showed that the EDUV platform positively influenced participants' perceptions of robotics and motivated them to further their education. In this paper, the related work is discussed, and the architecture of the vehicle is analyzed, along with the integration with the online platform. In addition, the methodology performed is explained and divided into steps. Finally, the experimental results are discussed. Instructions, 3D models, and code can be found in the github repository https://github.com/MariosVasileiou/EDUV.

Robot-Assisted Language Education and Speech Therapy for Children with Cleft Lip and Palate

Cleft lip and palate (CLP) is a congenital anomaly that can have detrimental effects on an individual's ability to produce certain sounds, including bilabial sounds such as /m/ and alveolar sounds such as /n/, as well as sounds that require closure between the nasal and oral cavities, such as sounds ending in /-ɪŋ/. While surgical intervention can assist in correcting anatomical irregularities, consistent speech and language therapy sessions are often necessary to overcome obstacles associated with speech production. The research problem addressed in this study is the interruption of regular therapy, as evidenced by the discontinuation of services during the COVID-19 pandemic, which can lead to setbacks in progress and an increase in the risk of developmental delays in children. To explore the potential of educational robots to address this problem, this paper (i) investigates the user requirements, usability considerations, and attitudes to speech therapy robots, from the perspective of parents and carers of children with CLP, (ii) presents an experimental prototype for CLP language education and speech therapy using a humanoid robot, named Robot Lily, based on input from prospective users; and (iii) evaluates the prototype Robot Lily on a subject with CLP. The robot has been programmed to interact with the child in a naturalistic manner, using the same language and gestures employed by human speech and language therapists. The robot can respond to inquiries, practice articulation and pronunciation, aid the child with speech fluency, provide feedback, and encourage continued speech exercises. The primary interactions between a child with CLP and Robot Lily were observed and evaluated, with the robot shown to provide a unique opportunity to acquire speech and language abilities in a captivating and interactive manner. Compared to web-based applications, speech education assistant robots like Robot Lily may offer children a more appealing, engaging, and practical solution; and be remotely controlled by humans for specialized interventions at home, thereby circumventing the challenges encountered during COVID-19. These findings and methods have been used to develop an integrated model for ethical robotic speech therapy utilizing machine learning, which is expected to help meet the growing demand for speech therapy services.

Twenty-first century parents’ attitudes and beliefs on early childhood robotics education

Twenty-first century parents’ attitudes and beliefs on early childhood robotics education