Educational Robotics Research Articles

Il «Robotics Interest Questionnaire» (RIQ): uno strumento per rilevare i fattori sottesi all’insegnamento della robotica

THE «ROBOTICS INTEREST QUESTIONNAIRE» (RIQ): A TOOL TO DETECT FACTORS UNDERLYING ROBOTICS TEACHING Abstract The growing interest of the scientific and educational community in Educational Robotics (ER) is linked to the need to develop digital skills and computational thinking in the younger generation. Through ER it is possible to train multiple cognitive skills and not only programming skills. To this end, it is decisive to outline a new competence profile for teachers that can influence this aspect by activating ER training courses. The paper presents the «Robotics Interest Questionnaire» (RIQ), a validated questionnaire in Italian able to measure with some precision the factors involved in teaching robotics, and discusses the data collected on teachers of all levels (823 teachers). The results provide normative values useful, for example, to allow the diagnostic use of the RIQ in the startup phase of teacher training, in order to hypothesize the level possessed by the participants and orientate the didactic design and the content-methodological choices of the intervention, as well as the final evaluation of the training outcomes thanks to its ability to highlight, when used before and after, improvements in the dimensions investigated: knowledge and interest, sense of self-efficacy, problem solving and collaboration.

Social robot assisted music course based on speech sensing and deep learning algorithms

In the field of social robot teaching, research has focused on how to use technological means to provide better learning support and personalized interactive experiences. Social robots can interact with students and provide personalized learning support, thereby improving their learning effectiveness and engagement. The speech sensing model of social robots can perceive students’ emotions and feedback in real-time through technologies such as speech recognition and sentiment analysis, thereby providing intelligent responses and guidance. The deep learning recommendation model for music course resources extracts music features through deep learning techniques, and combines session interest extraction techniques to personalized recommend music resources suitable for students’ interests and abilities. By analyzing students’ interests and learning goals, robots can provide music learning resources that meet their needs based on recommendation algorithms, further stimulating their learning interest and enthusiasm. The experimental results show that the use of social robots in the learning environment significantly improves the learning effectiveness and participation of students. Through personalized interaction and intelligent response guidance, students are more likely to understand and master music knowledge, while experiencing joyful and positive learning emotions. The study validated the effectiveness of social robot assisted music courses based on speech sensing and deep learning algorithms, demonstrating its advantages in improving student learning effectiveness and engagement.

Discovering public attitudes and emotions toward educational robots through online reviews: a comparative analysis of Weibo and Twitter

PurposePublic reviews on educational robots are of great importance for the design, development and management of the most advanced robots with an educational purpose. This study explores the public attitudes and emotions toward educational robots through online reviews on Weibo and Twitter by using text mining methods.Design/methodology/approachOur study applied topic modeling to reveal latent topics about educational robots through online reviews on Weibo and Twitter. The similarities and differences in preferences for educational robots among public on different platforms were analyzed. An enhanced sentiment classification model based on three-way decision was designed to evaluate the public emotions about educational robots.FindingsFor Weibo users, positive topics tend to the characteristics, functions and globalization of educational robots. In contrast, negative topics are professional quality, social crisis and emotion experience. For Twitter users, positive topics are education curricula, social interaction and education supporting. The negative topics are teaching ability, humanistic care and emotion experience. The proposed sentiment classification model combines the advantages of deep learning and traditional machine learning, which improves the classification performance with the help of the three-way decision. The experiments show that the performance of the proposed sentiment classification model is better than other six well-known models.Originality/valueDifferent from previous studies about attitudes analysis of educational robots, our study enriched this research field in the perspective of data-driven. Our findings also provide reliable insights and tools for the design, development and management of educational robots, which is of great significance for facilitating artificial intelligence in education.

1170 Bridging the Gap in Surgical Robotics Education

Abstract Aim Despite rapid evolution of surgical robotics systems, training opportunities are very limited especially for medical students and junior doctors. We organised a free-of-charge regional robotics workshop in collaboration with CMR Surgical with the goal of increasing exposure to surgical robotics technology. We also evaluated the delegates’ perception on current surgical robotics training and the workshop. Method CMR Surgical was invited to exhibit their Versius® robot and Virtual-Reality trainer for a one-day workshop at Glenfield Hospital, Leicester. The workshop was advertised across universities and hospital trusts in East Midlands. Registration form included pre-workshop questionnaire which assessed the motivation and barriers to attending surgical robotics courses, and their familiarity with robotics surgery. After 1-hour hands-on exercise supervised by consultants and CMR Surgical trainers, delegates were asked to complete post-workshop questionnaire to evaluate shift in familiarity, interest, and confidence in basic robotic skills. Results 75 delegates registered with 93% having never attended similar workshop before and the barriers were perceiving that robotics surgery skills are for advanced surgeons only (37%), cost (26%), no accessible courses (24%), time constraints (9%) and others (4%). The primary motivation to attend this workshop were learning basic robotic skills (49%), exploring innovative technology (44%) and networking (7%). 30 delegates were shortlisted for 1-hour hands-on experience into six groups consisting of 18 students and 12 junior doctors. Post-workshop feedback showed a positive shift in familiarity, interest, and confidence in basic robotic skills. Delegates also expressed increased interest in surgical specialties after this workshop. They also found VR station was enjoyable and believed it has potential in training future robotic surgeons. Conclusions These findings highlight the feasibility and importance of creating accessible training opportunities to bridge the gap in surgical robotics education.

Effects of educational technology intervention on creative thinking in educational settings: a meta-analysis

Purpose This study aims to meta-analytically investigate the impact of educational technology interventions on the development of creative thinking in educational settings. In recent years, the debate among researchers has persisted regarding the impact of various educational technologies, including interactive learning environments, digital instruction and platforms, and educational games and robotics, on students' creative thinking in diverse educational settings due to inconsistent findings. Design/methodology/approach This study, conducting a meta-analysis by synthesizing 35 relevant empirical studies with 2,776 participants, aims to investigate the association between educational technology interventions and the Torrance Tests of Creative Thinking (TTCT) and its subscales (fluency, flexibility, originality and elaboration). Findings No evident publication bias was found. From a general perspective, the results demonstrate a moderate level of influence of educational technology on the overall TTCT scale, with high heterogeneity attributed to the adopted instruments, mixed methods and target outcomes. Additionally, the results indicate that only three of the TTCT subscales (fluency, flexibility and originality) are influenced by educational technologies. Among the interventions, interactive learning environments yielded medium to the largest mean effect size. Furthermore, moderator analyses suggest that the effects of interventions on two subscales of TTCT (flexibility and originality) are moderated by school types, research design and the duration of intervention. The conclusion drawn is that interventions promoting students' creative thinking in different educational settings are efficacious. Originality/value Despite the low homogeneity of the results, which might have influenced the findings, the large fail-safe N suggests that these findings are robust. The study examined potential causes of heterogeneity and emphasized the importance of further research in this area.

La Robótica Educativa: Potenciando el pensamiento matemático y habilidades sociales en el aprendizaje

In educational environments, trends are addressed that allow learning to be acquired in various ways, among these is educational robotics, which has become a versatile tool capable of enhancing student performance at various stages of their learning. The purpose of this document is to explore the aspects related to educational robotics that contribute to the development of social skills and mathematical thinking in students. To achieve this objective, an exhaustive search was carried out that includes articles and publications related to the topic, classification and documentary analysis. This research allowed us to identify the possible contributions of educational robotics to social skills and mathematical thinking, in addition to establishing that it is a growing trend in different educational and social areas. The analysis carried out highlights that educational robotics is an effective tool to promote mathematical thinking. The literature supports the idea that students involved in the manipulation and use of robots experience significant improvements in their understanding of mathematics. In addition, it has been observed that this practice also enhances socio-emotional skills, such as empathy, cooperation, communication and collaboration among students. The period for the documentary review was established between 2015 and 2023, consulting a total of 50 articles from the databases of Dialnet, Redalyc, SciELO, Latindex, Google Scholar and institutional repositories, 28 studies were related to this work

Impact of Artificial Intelligence in Education Benefits and Challenges

As today’s world is developing in all aspects of human abilities, it is also reflecting in all areas where humans can reach. But these developments in no way should harm the natural existence of humans through their job or earning capacity. When Artificial Intelligence (AI) was initially brought into public, there was a major question about the job security of millions of peoples as AI and robotics in combination may replace a wide range of employees from their current job. Similar scenarios exist in the case of education sector also, as in future the teachers or professors may be replaced by AI leaded robotic teachers. It has several advantages and disadvantages in Education sector. This paper deals with an analysis of the impact of AI in Education sector.

Toward Ethical Deployment of Social Robots in Education

Purpose: This study explores the role of social robots, also known as socially assistive robots (SARs), in educational settings. It highlights their potential benefits in language learning, STEM education, and personalized learning. The study also aims to identify and address the ethical concerns associated with integrating social robots into education. Method: The paper reviews existing literature on the use of social robots in education and analyzes their potential benefits and ethical issues. The analysis focuses on various educational contexts and the interactions between students and social robots. The review also considers technological advancements and their implications for ethical concerns. Results: Social robots can significantly enhance language learning, STEM education, and personalized learning experiences for students. However, it also identifies several ethical concerns: excessive emotional attachment to robots, privacy issues, potential abuse of robots, bias in the information provided by robots, and accessibility challenges for disadvantaged groups. Conclusion: Addressing the ethical issues related to the use of social robots in education is crucial for maximizing their benefits while ensuring fairness and safety for students. The paper emphasizes the need for collaborative efforts among stakeholders to develop effective and ethical applications of social robots in education, and go forward to both technological advancements and ethical implications.

Utilize Educational Robots to Design Logistic Systems

The use of educational robots is new in terms of their utilization for designing logistic systems. The current methodology for designing logistic systems is not directly oriented towards the use of educational robots. This indicates the need to develop a methodology is directly oriented toward the use of educational robots in logistic system design. The aim of this article is to highlight the possibilities of creating a new methodology for designing logistic systems applying using educational robots or small physical models in general. This article brings a new perspective on the possibilities of designing logistic systems. We consider educational robots, infinite conveyor belts, and so on, such as small physical models. From these elements, we can assemble a functional logistic system for study. This method is necessary solution for the accredited field of study industrial logistics.

APRENDIZAGEM BASEADA EM PROJETOS NAS PERSPECTIVAS “STEAM” E “ROBÓTICA CRIATIVA E SUSTENTÁVEL” NO ENSINO TÉCNICO INTEGRADO AO ENSINO MÉDIO: REVISÃO SISTEMÁTICA DA LITERATURA

This article is the result of an excerpt from a research project under development (2023-2026), with the support of the São Paulo Research Foundation (FAPESP), within the scope of the Basic Education Research Program - PROEDUCA - FAPESP/SEDUC. The objective of this article is to identify and analyze studies already developed regarding the use of Project-Based Learning (PBL) from a STEAM perspective, focusing on the introduction of creative and sustainable robotics in technical education integrated with high school. The present study was developed through a Systematic Literature Review (SLR) carried out in the first semester of 2023, through the search for dissertations and theses in the database of the Digital Library of Theses and Dissertations (BDTD), using Bardin's Content Analysis methodology for organization, treatment, and interpretation of the data. However, no studies were identified that addressed the use of Project-Based Learning (PBL) from a STEAM perspective, focusing on the introduction of creative and sustainable robotics in technical education integrated with high school. In conclusion, this study highlights the existence of a research field lacking investigations and suggests the need to expand discussions and practices related to the use of Project-Based Learning (PBL) from a STEAM perspective, with an emphasis on the introduction of creative and sustainable robotics in technical education integrated with high school. It is understood that this is a fruitful field to expand the discussion on school curricula, as well as an opportunity to recompose unlearned content.

Eye-tracker and fNIRS: Using neuroscientific tools to assess the learning experience during children's educational robotics activities

In technology education, there has been a paradigmatic shift towards student-centered approaches such as learning by doing, constructionism, and experiential learning. Educational robotics allows students to experiment with building and interacting with their creations while also fostering collaborative work. However, understanding the student's response to these approaches is crucial to adapting them during the teaching-learning process. In this sense, neuroscientific tools such as Functional Near-Infrared Spectroscopy and Eye-tracker could be useful, allowing the investigation of relevant states experienced by students. Although they have already been used in educational research, their practical relevance in the teaching-learning process has not been extensively investigated. In this perspective article expressing our position, we bring four examples of learning experiences in a robotics class with children, in which we illustrate the usefulness of these tools.

Examining the Impact of Modified P3 Task Taxonomy-Enriched Educational Robotics PD Program on Teachers’ STEM Content Knowledge

Examining the Impact of Modified P3 Task Taxonomy-Enriched Educational Robotics PD Program on Teachers’ STEM Content Knowledge

Enhancing computational thinking in early childhood education with educational robotics: A meta-analysis

This paper deals within a context where technology plays a pivotal role in education. In this sense, it is essential to highlight the emergence of new competencies and skills in education due to technological advancements. Legislative frameworks have been developed to incorporate digital literacy, access to robotics, and computational thinking, between others. Hence, this review and meta-analysis aim at identifying the influence of robotics activities on computational thinking through a PRISMA-guided review. The findings reveal that interventions conducted in early childhood education significantly impact computational thinking. Results also showcase that, despite perceived barriers related to technology accessibility, the presence of legislation and contexts prioritizing these competencies is more relevant than the digital access gap.

Experience of intelligent speech robot in music online classroom based on deep learning and virtual reality

This study designs and implements an intelligent voice robot music online classroom teaching platform, providing students with a more personalized and interactive learning experience. Research the application of deep learning technology to establish a speech recognition model for music teaching, achieving accurate recognition and understanding of student speech; Combining speech recognition technology and robot interaction technology, construct an intelligent speech robot teaching platform to achieve interactive speech learning; Finally, utilizing virtual reality technology to create an immersive music teaching environment, enhancing students’ sense of participation and learning effectiveness. Through research and analysis of the needs of students and teachers, the functions and characteristics of the intelligent voice robot music online classroom teaching platform have been determined. We have established a comprehensive platform architecture and implemented functional modules such as speech recognition, virtual reality environment construction, and teaching resource management. Designed diverse interactive teaching and learning modes, enhancing the fun and effectiveness of learning. This study successfully designed and implemented an intelligent voice robot music online classroom teaching platform based on deep learning and virtual reality, injecting new vitality and possibilities into music teaching.

Sustainable development pathways: Exploring the impact of green finance on urban metabolic efficiency

AbstractImproving urban metabolic efficiency is crucial for sustainable development. This paper examines how green finance affects urban metabolic efficiency and its underlying mechanisms using city‐level green finance data from China between 2010 and 2022. Additionally, the non‐linear impact of green finance on urban metabolic efficiency is analyzed using a PLFC model. The research findings indicate that green finance notably improves urban metabolic efficiency via its constraint effect, incentive effect, and innovation compensation effect. The conclusion remains valid after conducting robustness tests. The analysis of mechanisms indicates that the incentive effect outweighs the constraint effect. Heterogeneity analyses demonstrate that the impact of green finance on urban metabolic efficiency varies depending on regions, city sizes, and city attributes. Furthermore, further investigation demonstrates that green finance exhibits a non‐linear impact on urban metabolic efficiency, with education level and robotics application serving as significant moderating factors. This paper offers fresh insights into the correlation between green finance and urban metabolic efficiency, along with valuable references and insights for crafting more targeted policies.

Educational robotics or unplugged coding activities in kindergartens?: Comparison of the effects on pre-school children's computational thinking and executive function skills

This study compares the effects of coding education with educational robot and unplugged coding activities on pre-school students' computational thinking and executive function skills. This study used a pre-test and post-test comparison group quasi-experimental design. The study was conducted in a public kindergarten with 48 pre-school students (24 educational robot- BeeBot® group and 24-unplugged coding group) aged 5-6. The TechCheck-K test was used to measure computational thinking skills, and Executive Functions Battery-Computerized Touch was used to measure executive function skills. The process started with pre-test applications and ended with post-tests after four weeks (16 different sessions) of the implementation in both groups. The study found a statistically significant difference between the computational thinking pre-test and post-test scores of pre-school students in both groups in favor of the post-test. It was determined that there was a statistically significant difference in favor of the educational robot group between the post-test scores of computational thinking skills. In addition, when the findings regarding executive functions were evaluated, there was a statistically significant difference between the pre-test and post-test scores of total executive function in favor of the post-test in both groups. However, it was observed that there was no statistically significant difference between the post-test scores of both groups in terms of total executive function skills scores. In addition, when the post-test scores of pre-school students in two groups were evaluated, it was determined that there was no significant difference in computational thinking and executive function skills according to gender. Consequently, it was determined that coding education with an educational robot was more effective for gaining computational thinking skills than unplugged coding activities for pre-school students. However, it was observed that there was no difference between the two groups in terms of the development of executive function skills in pre-school education.

Integrated Data Processing Architecture Applied to Learning Objects Repository for Educational Robotics: Proposing Approach

Educational Robotics has emerged as a multidisciplinary field integrating Information and Communication Technologies, Engineering, and Artificial Intelligence areas in education. Furthermore, Educational Robotics offers an innovative approach to teaching and learning by incorporating the construction and programming of robots. However, the small number of platforms for sharing Educational Robotics Learning Objects with a large amount of well-described metadata poses a challenge for efficient search and retrieval of relevant educational content. This study presents an architecture for data processing and ingestion in the RepositORE system, a Learning Objects Repository for Educational Robotics that stores educational content and associated metadata based on the Dublin Core standard. Based on microservices architecture, the proposed system aims to facilitate the location and reuse of learning objects by adapting the RepositORE system to work as a client service. The theoretical framework explores the concepts of learning objects, repositories, and the significance of Educational Robotics in education, and reviews related works. The proposed architecture and system can potentially enhance the accessibility and discoverability of Educational Robotics Learning Objects, fostering effective teaching and learning experiences.

Physical Robots in Education: A Systematic Review Based on the Technological Pedagogical Content Knowledge Framework

Driven by the wave of artificial intelligence, the educational practice and application of robots have become increasingly common. Despite extensive coverage in the literature on various aspects of educational robots, there are still unexplored avenues, particularly regarding robotic support, robotic personality, and challenges in their applications. This study presented a systematic review of high-quality empirical research on the use of physical robots in educational settings. A total of 92 relevant papers from the Web of Science database were analyzed. Employing the technological pedagogical content knowledge (TPCK) framework, we investigated research questions across seven components, including the learning domain, teaching strategy, robot types, learning results, problems with using robots, robotic support, and robotic personality. The findings revealed that robots are most prevalently employed in language learning applications. When opting for teaching strategies, educators tend to favor those that incorporate physical interaction. Concurrently, humanoid robots emerge as the preferred choice among many. These robots, in human–robot interaction scenarios, often exhibit an agreeable personality. In terms of evaluating learning results, cognitive aspects like thinking, creativity, self-regulation, and inquiry ability are especially emphasized. Such results are frequently influenced by the informational and emotional support provided by robots. Nonetheless, challenges encountered by teachers, learners, and robots in this process are not to be overlooked. The findings of this study contributed to future applications of robotics in education.

Social entertainment robot based on artificial intelligence algorithm application in interactive mode of music classroom

With the rapid development of artificial intelligence technology, in-depth research on the application of social entertainment robots in the field of education has become increasingly important. Therefore, this study aims to explore how to use social entertainment robots based on artificial intelligence algorithms to improve the interactive mode in music classrooms, in order to enhance learning effectiveness and classroom atmosphere. The study introduced the detection algorithm of social entertainment robots and designed a complete detection process for accurately locating and identifying social entertainment robots in music classrooms. A machine data classification detection algorithm has been proposed to accurately determine the behavior and function of social entertainment robots. The social entertainment robot teaching module guides students to actively participate in music classroom activities through simulated conversations and interactive demonstrations. Interactive tests were conducted in actual music classrooms to evaluate the effectiveness of social entertainment robots in the classroom and student feedback. Through experiments, it has been proven that social entertainment robots based on artificial intelligence algorithms can effectively enhance the interactivity and fun of music classrooms. It not only promotes communication and cooperation among students, but also enhances learning participation.

Personalized recommendation of entertainment robots in fine arts education based on human–computer interaction and data mining

In the current digital entertainment environment, the art learning mode of human–computer interaction can effectively enhance students’ interest. Entertainment robots, as a novel personalized interaction tool, can provide a more intelligent and entertaining way for art teaching. This article analyzes the personalized recommendation of entertainment robots in art education based on human–computer interaction and data mining.On the basis of collecting a large number of fine art education resources and organizing and labeling them, data mining technology is used to extract user background information and interest preferences. Information retrieval technology is used to filter out content related to user interests from the massive art education resources based on the extracted user interests. We also use recommendation algorithms to sort and personalize the recommended content based on the user’s historical behavior and other user evaluations, in order to improve the accuracy of recommendation results and user satisfaction. The effectiveness and practicality of this personalized recommendation model were verified through user surveys and data analysis. The experimental results indicate that this model can quickly and accurately recommend suitable fine art education content for users, improving their learning effectiveness and experience.