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In this paper, we describe a teaching scenario using a virtual environment (known also in the context of the 'metaverse'). This is motivated by the challenges that arise during the pandemic. More and more teaching scenarios are transferred to online learning settings, which allow learning at any time and at any time. One of the possibilities are virtual 3D environment. These allow more intensive immersion than for example video conferences. Furthermore, they offer new didactic concepts, for example, for group activities. The benefit of using virtual 3D environments we demonstrate by a concrete learning scenario: the simulation of robot programming. A further advantage when using virtual 3D environments are personal assistants (conversational/ pedagogical agents), for example, to the ease the work load borne by teachers; meanwhile, this works well also with natural language due to advantage stage of artificial intelligence implementations.

The article is devoted to the study of the issue of training future police officers to use unmanned aerial vehicles (UAVs) in their professional activities. Based on the results of the theoretical analysis of scientific and applied works, modern trends in the development of drones in the activities of law enforcement agencies were identified, and the problem of their implementation in practical activities was outlined. An online survey was conducted in order to study the opinion of scientific, scientific and pedagogical workers and graduates of higher education institutions with specific learning conditions that train police officers about the need to train future police officers in the control of UAVs. The need to introduce into the system of primary professional training the training of service skills using drones is substantiated. On the basis of the study of the content of the training program for unmanned aircraft systems of the first class according to the basic qualification level of the first level, it is proposed to introduce the general professional educational unit "formation of skills and skills of controlling an UAV" into the training program of the primary professional training of police officers in the specified specialty.

In today's conditions, the needs of the labor market are changing in parallel with technological developments and the need for individuals trained in STEM is increasing. For this reason, it is a priority to increase the skills and awareness of teachers who will guide individuals trained in the field of STEM. In this study, a STEM training with educational robotics applications was designed for classroom teachers. The education included theoretical and practical STEM instruction conducted by expert academicians, utilizing next-generation educational robotic kits to facilitate sample STEM activities. The primary aim was to equip teachers with skills aligned with the elementary school curriculum, emphasizing a focus on STEM learning outcomes. As a result of the training, teachers were able to develop their own STEM activities. The study, which was modeled with a one-group pretest-posttest research design, examined the changes in the attitudes towards STEM and STEM awareness of the participants as a result of the STEM education they received. In conclusion, it is observed that the participants' attitudes towards STEM education and their awareness of STEM have increased by the end of the education. Additionally, the participants believe that STEM educational activities should be included in the curriculum.

The aim in this study was to determine the effectiveness of STEM-based robotic coding education for primary school students in terms of their decision-making skills. Mixed method research was conducted. Pretest-posttest control group designs were used in the quantitative phase, and a case study was performed in the qualitative phase of the research. The study sample consisted of 65 third graders. Pretesting of the experimental and control group students was performed using the decision-making skills scale. STEM-based robotic coding training was given to the experimental group for 6 weeks. Afterwards, the decision-making skills scale was applied as a posttest to both the experimental and control groups. The quantitative data were analyzed with paired and independent samples t-tests. A statistically significant increase was observed in the experimental group students' decision-making skills in favor of the posttest. There was no significant difference between the pre- and posttest scores of the control group students. An interview with 15 experimental group students was conducted to collect qualitative data, and the interview results were analyzed using content analysis. The robotic coding education positively affected the students' decision-making and problem-solving skills and their willingness to share ideas.

The purpose of the current study is to examine the effect of adapting the engineering design process to robotic coding, STEM, and the nature of science applications on teachers' self-efficacy towards engineering education and attitudes towards robotic coding. A weak experimental design with a single-group pre-test and post-test, one of the quantitative research methods, was used in the study. The sample of the study consists of 20 science teachers from all over Turkey who meet the application requirements within the scope of the project 2237 supported by TÜBITAK and working in schools affiliated to the Ministry of National Education. The sample was determined using the purposive sampling method. In this study, teachers were given theoretical and practical training on engineering design process-based STEM, robotic coding, and the nature of science for a total of 36 hours over one week. Quantitative data were analyzed using dependent groups t-test and correlation analysis in the SPSS 23 program. They evaluated their ability to apply these activities in their classes. As a result of the analysis of the quantitative data of the study, it was observed that their self-efficacy towards engineering education and attitudes towards the use of robotic coding in the class showed a positive increase.

Purpose: To align with the artificial intelligence and robotics (AIR) research and policy agenda, this paper puts forth an adapted five big ideas framework specifically tailored to teaching young children about artificial intelligence (AI) via robotics. Design/Approach/Methods: Grounded in early childhood education research, the proposed framework emphasizes the use of robotics and play-based learning to make AI accessible and encourage engagement among young children who have not started formal schooling. Findings: We comparatively analyze the commonalities and differences in AI big ideas between the original K-12 framework and the redeveloped early childhood education framework. To pique children's interest, key concepts are presented through interactions with robotics and robot role-play. This paper also provides recommendations for age-appropriate topics, storytelling, and play-based teaching methods. Originality/Value: This framework aims to equip researchers and educators with strategies for successfully integrating introductory AI education into early childhood classrooms. Teaching AI in a developmentally responsive manner can help nurture young children's curiosity toward and understanding of an increasingly AI-driven world.

In light of the growing diversity of students in the classroom, there is a pressing need to address the potential for discrimination against minorities, arising from cultural, socioeconomic, special needs, learning styles, and other differences. It is, therefore, essential to establish inclusive learning environments that guarantee equitable learning outcomes for all children and young people. This study aims to determine the impact of educational robotics (ER) in promoting emotional, cognitive, and social inclusion attributes through active methodologies among secondary students in public institutions. The applied methodology is composed of elements typical of active methodologies implemented in education and cited in the theoretical framework. The instruments employed to measure the classroom intervention process across various stages demonstrated a gradual improvement in the reference attributes of inclusive education. The findings suggest that ER can serve as a valuable tool for promoting inclusion in diversity contexts.

This study examines interdisciplinary and transdisciplinary interconnections within STEAM (Science, Technology, Engineering, Art, and Mathematics), the humanities, and their collective impacts on civilizations over time. This study includes a comprehensive overview of STEAM education and its integration with historical context and explores relationships beyond the acronym of STEAM itself, with an emphasis on STEAM advancements, the humanities, and digital citizenship for contemporary learners. The role of humanities in relation to STEAM is considered for delving into the historical background of robotics, the technological evolution from simple machines to complex tools for machine learning, engineering innovations during Industrial Revolutions, the Renaissance for creativity, and the Maker Movement for makerspaces in fostering innovation. The researchers consider how scientific, technological, engineering, and mathematical advancements have shaped societal development, as well as the historical roles of artistic expression on cultures. An analysis of interdisciplinary and transdisciplinary connections among STEAM disciplines within historical contexts creates a holistic educational view of societal evolution. The researchers also reflect on the contemporary implications of historical STEAM developments, advocating for the integration of historical context into STEAM curricula -- and STEAM curricula into the humanities -- for cultivating critical thinking, creative thinking, and a deeper understanding of civilization's interconnectedness.

Educational robotics (ER) is a constructivist approach to education that promotes experiential learning through actual activities for teaching and learning science, technology, engineering, and mathematics (STEM) subjects. Empirical findings have indicated that primary school students have limited interest in learning mathematics due to the inability to rationalize real-world applications without practical application. Therefore, this study aims to determine the implications of using ER to evaluate their effect on primary school students' mathematics learning achievement, interest, and attitude. A total of 40 respondents from year five participated in this quasi-experimental study that explored the difference between using ER and PowerPoint hands-on methods as instructional approaches to complement teaching and learning. The findings indicated that ER improved mathematics learning achievement and perceived interest with a high effect size, and students also indicated a positive attitude toward using ER to aid in learning mathematics.

This study explored the integration of neural networks and artificial intelligence in image recognition for object identification. The aim was to enhance students' learning experiences through a "Learning by Teaching" approach, in which students act as instructors to train AI robots in recognizing objects. This research specifically focused on the cell division unit in the first grade of lower-secondary school. This study employed a quasiexperimental research design involving four seventh-grade classes in a rural lower-secondary school. The experimental group (41 students) were taught via an AI robot image recognition technology, whereas the control group (40 students) were taught via a more conventional textbook-centered approach. The research followed a pre-test design, with three classes lasting 45 min each, totaling 135 min of teaching time over two weeks. Evaluation tools include the "Cell Division Two Stage Diagnostic Test" and the "Science Learning Motivation Scale." The results indicate that learning through teaching AI robot image recognition technology is more effective than textbook learning in enhancing students' comprehension of the "cell division" concept and boosting motivation to learn science.

Educational robotics integrates aspects from various scientific disciplines, encompassing the entire spectrum of science, technology, engineering, and mathematics (STEM) education. Its effective application is heavily reliant on educators tasked with implementing it within a school setting. This study aimed to investigate the potential adoption of educational robotics among preschool and primary education teachers. The study involved 191 preschool teachers (62.2%) and 115 primary school teachers (37.8%). Data was gathered using a structured questionnaire, AKAER, demonstrating strong internal consistency with a Cronbach's alpha reliability coefficient of [alpha]=0.892. Educators, irrespective of their specialization, gender, or scientific background, acknowledge the significance of educational robotics and express eagerness to incorporate it. A substantial percentage of educators expressed discomfort in using educational robotics and related if they had trained or not. Nonetheless, more than 70.0% of the surveyed educators expressed interest in receiving training on educational robotics to proficiently integrate it into their teaching methodologies. To ensure that the new generation of students can reap the benefits of modern teaching tools like educational robotics, closely tied to STEM education and the cultivation of 21st century skills, we must not only supply schools with the required materials but prioritize the provision of adequately trained and informed educators.

This qualitative study explored the views of teachers and an occupational therapist about the potential use of humanoid robots as an assistive tool in educating autism spectrum disorder (ASD) children. Seven participants with extensive experience handling early intervention programs for ASD children were selected via purposive sampling. Semi-structured interviews and focus group discussion (FGD) were applied as data collection method. Data gained were analyzed using thematic analysis. Four main themes were identified from the study, they are: (1) Teachers' knowledge about robots, (2) Robots increase children's engagement, (3) Roles of robots in intervention, and (4) advantages and disadvantages of using robots. All participants had observed a robot-mediated intervention involving interactions between ASD children and a humanoid robot. It was observed that most of the children at the center liked interacting with the robot, suggesting that the use of robots could benefit ASD children. However, these interactions must be monitored and limited to a certain period to avoid over-dependence on robot use. This study provides a novel perspective on robotics and a practical example of how to use robots to enhance learning outcomes for ASD children.

Purpose: Chatbots and artificial intelligence (AI) have the potential to alleviate some of the challenges faced by humans. Faculties frequently swamped with teaching and research may find it difficult to act in a parental role for students by offering them individualized advice. Hence, the primary purpose of this study is to review the literature on chatbots and AI in light of their role in auto-advising systems. The authors aimed to gain insights into the most pertinent topics and concerns related to robo academic advisor and identify any gaps in the literature that could serve as potential avenues for further research. Design/methodology/approach: The research employs a systematic literature review and bibliometric techniques to find 67 primary papers that have been published between 1984 and 2023. Using the Scopus database, the researchers built a summary of the literature on chatbots and AI in academic advice. Findings: Chatbot applications can be a promising approach to address the challenges of balancing personalized student advising with automation. More empirical research is required, especially on chatbots and other AI-based advising systems, to understand their effectiveness and how they can be integrated into educational settings. Research limitations/implications: This research's sample size may restrict its findings' generalizability. Furthermore, the study's focus on chatbots may overlook the potential benefits of other AI technologies in enhancing robo academic advising systems. Future research could explore the impact of robo academic advisors in diverse societal backgrounds to gain a more comprehensive understanding of their implications. Practical implications: Higher educational institutions (HEIs) should establish a robo academic advising system that serves various stakeholders. The system's chatbots and AI features must be user-friendly, considering the customers' familiarity with robots. Originality/value: This study contributes to a better understanding of HEIs' perceptions of the adoption of chatbots and AI in academic advising by providing insightful information about the main forces behind robo academic advising, illuminating the most frequently studied uses of chatbots and AI in academic advising.

The incorporation of Computer Science teaching in educational systems has increased in recent years. Given international interest, Chile has promoted projects to promote the development of students' digital skills. Focusing on this new educational context, this research reports the results regarding the identification of computational concepts and practices that can be articulated with the contents and skills of the curriculum. of Chilean mathematics. for first grade of primary school based on the use of the Bee-Bot robot. For this, the study followed a qualitative approach, developing a case study of the Chilean study program with the content analysis technique and using, as analysis categories, computational concepts and practices from the field of educational computing. In total, 30 learning objectives of the study program were analyzed. The results indicate that, although there is little articulation between computational concepts and first grade content proposed in the curriculum, there is greater articulation between computational practices and mathematical skills suggested in the Chilean curriculum. It is concluded that Computational Thinking can be developed from the earliest school levels using the Bee-Bot robot (or similar), and this is demonstrated by the structure of the Chilean primary mathematics curricular program.

The integration of education and robotics has emerged as a crucial development in the technological landscape. This study focuses on the use of a robot teaching assistant to enhance the learning efficiency of 8th-grade students in hands-on STEM activities centered around the theme of "Smart City." It explores the impact of educational robots on students' learning outcomes and their development of hands-on skills through diverse learning methods. Conducted over 12 weeks with 103 participants, the study employed a quasi-experimental design. Students were split into two groups: The Experimental Group (EG), using the 6E model with robot teaching assistants, and the Control Group (CG), using only the 6E model. The analysis of covariance revealed that the EG exhibited superior performance in STEM knowledge, motivation, and hands-on skills compared to the CG. Further analysis indicated that learning motivation significantly influenced hands-on performance in the EG, particularly in high-scoring subgroups. The findings suggest that combining the 6E model with educational robots effectively enhances STEM learning and student engagement. Educational robots as teaching assistants not only aid in knowledge acquisition but also significantly boost students' motivation and hands-on skill development. This implies a promising direction for integrating advanced technology in educational practices to foster more effective learning environments.

This research aimed to investigate the structural relationships among teachers' computational thinking (CT), design thinking (DT), robotics teaching beliefs, and robotics pedagogical content knowledge (RPCK). A total of 98 in-service and pre-service teachers who participated in a robotics teaching professional development workshop served as the sample of the study. A survey including the Computational Thinking Scale, the Design Thinking Disposition Scale, the Robotics Teaching Beliefs Scale and the Technological Pedagogical Content Knowledge-Robotics Scale was conducted after the workshop. A confirmatory factor analysis was employed to validate the measurement constructs, and Partial Least Squares - Structural Equation Modeling (PLS-SEM) analysis was utilized to examine the relationships among the factors. The results revealed that both CT and DT dispositions could positively predict teachers' robotics teaching beliefs, which subsequently predicted their RPCK. Moreover, a direct positive relationship between CT and RPCK was identified, while such a relationship was not evident for DT. The model demonstrates the critical role of CT in shaping teachers' beliefs and pedagogical strategies of robotics teaching, and provides insights into the indirect influence of DT. Finally, the Model of Robotics Teaching Professional Development (MRTPD) was proposed to profile how to promote teachers' pedagogical content knowledge of robotics teaching from their CT and DT dispositions.

Background: Implementation issues often hinder reaching the potential of care technology to improve daily lives of people with intellectual disabilities. We investigated barriers to and facilitators of implementing different technology modalities (app/social robot/sensor/domotics) in long-term care. Method: Care professionals (N = 83) from 12 Dutch disability care organisations completed a customised measurement instrument for determinants of innovations (MIDI) questionnaire. Results: Out of 27 determinants, 20 were identified as facilitators and 16 as barriers. We highlight common barriers: few colleagues who work with the technology; no (awareness of) formal ratification of technology use; no arrangements regarding turnover of staff using the technology; unsettling organisational changes; technological defects and limited IT preconditions. Conclusions: The results, which could be combined and compared across study sites, provide insight into which implementation determinants were already well addressed, and where there is ground to gain when implementing care technology in disability care organisations.

Low-stakes assessment has gained attention in recent years due to its link to enhancing learning effects and its essential role in learning evaluation. Unlike high-stakes assessments, low-stakes assessments have little or no consequences for learners' academic performance, and are designed to support the feedback-oriented learning process. Providing multiple low-stakes assessments to students yields significantly greater long-term retention of knowledge and skills. However, learners may not give their best efforts when taking low-stakes assessments, which could lead to poorer learning outcomes. Using emerging technologies such as social robots in the learning environment could foster interactive learning, engagement, and motivation for learning assessments. Therefore, integrating low-stakes assessments and robots might encourage students to exert greater effort while performing learning tasks. This study aimed to discover the impacts of robot-based multiple low-stakes assessments on students' oral presentation performance, collective efficacy, and learning attitude. A quasi-experiment was conducted in two sixth-grade classes of elementary students. The Robot-based Multiple Low-Stakes Assessment (Robot-MLSA) was randomly assigned to one class, while the Computer-based Multiple Low-Stakes Assessment (C-MLSA) was assigned to another class. The findings showed that the Robot-MLSA could enhance students' oral presentation performance, support their collective efficacy, and improve their learning attitude toward robots. Furthermore, an in-depth discussion of students' learning perceptions and experience is provided to explore the effectiveness of the Robot-MLSA.

Robotics, an emerging tool in STEM education, promises a multitude of educational benefits, ranging from hands-on learning experiences to fostering critical thinking and collaborative skills. However, the integration of robotics in classrooms is primarily contingent upon science teachers' inclination and willingness to adopt this technology. To bridge this gap, this research aimed to explore the adoption of robotics within STEM education by science teachers, by merging the Theory of Planned Behavior, Technology Acceptance Model, and Self-Determination Theory into a unified conceptual framework. Our hypothesis-driven approach tested using data from 605 science teachers across various regions in Turkey. The results indicate a significant positive correlation between science teachers' perceptions of the usefulness and ease of use of robotics and their intent to adopt it in their classrooms. Moreover, intrinsic motivational factors such as perceived autonomy and relatedness played a pivotal role in influencing teachers' behavioral intention towards robotics. The findings revealed that, compared to existing theories, our unified model offers a heightened understanding of the determinants influencing teachers' intentions to use robotics in STEM education. Ultimately, our research not only paves the way for a theoretically enriched understanding of technology adoption in STEM but also presents actionable insights for educators, curriculum designers, and policymakers aiming to capitalize on the myriad opportunities offered by robotics in contemporary education.

Educational robots have unrivaled advantages and value in developing students' computational thinking. Currently, there are fewer studies on the overall effects of educational robots on K12 students' computational thinking, especially at the instructional style and cross-grade level. In order to investigate the overall effect of educational robots on students' computational thinking, the study used a meta-analytic approach to analyze 27 experimental and quasi-experimental research papers from the last decade. It was found that: educational robots have a positive and significant effect on K12 students' computational thinking development (SMD = 0.558), and their application effects are influenced by moderating variables such as school level, teaching style, participation style, experimental period, and sample size. Specifically: educational robots have a positive and significant effect on K12 students, with the most significant effect at the early childhood level; there is a significant difference in the development of students' computational thinking when using educational robots in different teaching modes, with the best effect being achieved in the design-based teaching mode; (3) participating in educational robots in small groups is more likely to promote the development of computational thinking in K12 students; (4) Different experimental cycles have a positive effect on students' computational thinking, but a long experimental cycle does not mean a good effect, etc.; (5) There is a significant difference between different sample sizes of educational robots on K12 students' computational thinking, and arranging a medium-sized (50-100 students) educational robotics activity can achieve a better learning effect.

Contribution: This study qualitatively uncovered meaning for why and what was motivating to undergraduates participating in an educational human-robot interaction (HRI) experience. A data corpus of four documents (groups) was evaluated from a quasi-experimental, nonequivalent control (n = 23) and treatment (n = 61) research design revealing three themes attributing meaning for why and what was motivating to students. Background: Engineering education literature has indicated a positive impact on student motivation and academic success from HRIs. However, rigorous research that attributes meaning for why and what are motivating to students in these HRI experiences is not readily available. Intended Outcomes: Results of this study represent substantial findings that answer questions of why and what are motivating in HRI experiences. However, future research is needed to further understand the nuanced dynamics and multidimensional aspects of motivation in HRIs. Application Design: To analyze the qualitative open-ended survey responses from students, structured term frequency (tf), tf -- inverse document frequency (tf-idf), latent Dirichlet allocation (LDA) modeling, and content analysis were used, as these approaches are typical in computational text mining. Findings: When describing motivation toward the HRI, students were found to form a common lexicon to attribute why and what was motivating (e.g., "…[being] abl[e]" [to] see [the] robot follow [the line]…"). This suggests that the tangible, visual, immediate feedback experienced by students was why and what motivated them.

This study investigated the effect of project-based Arduino robot application on students' computational thinking skills development in robotics programming course using the quasi-experimental research design. The participants consist of 73 students in tertiary institutions in South-East Nigeria that offer Computer and Robotics Education programme. There was no sampling as the entire second-year trainee teachers of computer and robotics education in the selected institutions participated in the study. The instrument used for data collection was the Robotics Programming Computational Thinking Scale (RPCTS). Mean and standard deviation were used to answer the research questions, while Analysis of Covariance (ANCOVA) was used to test the hypotheses at an alpha level of 0.05. The result of the study showed that students who were taught using Project-based Arduino Robot Application (PARA) had higher mean computational thinking scores than those taught using the conventional lecture method, and there was a significant difference in the mean computational thinking scores of students based on method of instruction. Also, the male students taught robotics programming using PARA had higher mean computational thinking scores compared to their female counterparts, and there was a significant difference in the mean computational thinking scores of male and female students taught robotics programming using PARA. Schools and other stakeholders in education should support the training of teachers on how to develop and used project-based approaches in teaching/learning robotics programming-related courses.

The presence of social robots in children's daily environments has steadily increased. With the advancement of artificial intelligence (AI), social robots have influenced children's learning and development. This study innovatively utilized the Web of Science database and conducted a bibliometric analysis of 517 publications on social robots supporting children's learning and development before September 2022. Unlike most existing reviews, this study employed a synergistic combination of two complementary visualization tools, VOSviewer and CiteSpace, to map the intellectual structure and analyze the knowledge evolution path in this emerging interdisciplinary field. Specifically, VOSviewer generated visualizations depicting collaboration networks, research hotspots, and trends based on co-occurrences. CiteSpace enabled quantitative measurements of node centrality and burstness to reveal pivotal entities and emerging topics. Combining visual mapping and quantitative analysis by VOSviewer and CiteSpace allowed comprehensive landscape mapping for an in-depth investigation into the development of this field. This study proposes future research directions, including children's perceptions of social robots, social robots enhancing children's learning, social robots supporting children's social and emotional development, and social robots for children with special needs. The findings also inform the design and application of child-friendly social robots equipped with generative AI techniques.

Various researchers have reported that learners still have a limited conceptual knowledge of linear motion which may affect their learning achievement and motivation towards this subject matter. For this purpose, an investigation was conducted to find out the effect of the Project-Based Learning (PBL) approach with educational robotics on senior students' conceptual understanding of linear motion and learning motivation. This study used a quasi-experimental non-equivalent group design with a quantitative research approach. Participants were 78 senior students selected purposively from one school whose teachers have been trained on PBL by Rwanda Quality Basic Education for Human Capital Development project. A linear motion achievement test and a 5-point Likert motivation scale questionnaire were administered to the same groups of students. Descriptive and inferential statistics were used to analyse data quantitatively using Ms Excel and SPSS. Results have shown that students who were taught through PBL had more motivation toward learning linear motion and conceptualized better linear motion. The study recommends implementing Project-Based Learning (PBL) approaches, including educational robotics, and providing professional development for teachers to improve senior students' conceptual understand and motivation in linear motion.

Computational Thinking (CT) is essential for developing creativity, problem-solving, and digital competence in the 21st century. Coding tools like robotic toys and tablet apps have become popular in early childhood education to support CT development, but there is a debate on which tool is more effective. Little evidence exists on the effect of coding on children's Social-Emotional Competence (SEC), which is crucial for lifelong development and extends beyond cognitive development. This experimental study aimed to compare the effectiveness of two 9-week programs on promoting 73 preschool children's CT and SEC, one using coding robots and the other using coding apps. The results showed that children who participated in the Coding Robot Program had higher CT scores than those in the Coding App Program, after controlling for age, gender, family socioeconomic status, and baseline CT scores. While the SEC scores showed no substantial disparities between the groups, it was revealed that the initial performance levels moderated the intervention effects on emotional regulation and overall SEC. This suggests that the Coding Robot Program could be especially advantageous for a subset of children who initially have difficulties with emotional regulation and social skills. Implications of this study are presented for research and practice.

Educational robots represent a unique form of teacher presence. Exploring how the communication features of robot instructors affect student learning experience could contribute to the advancement of educational robots. This study examined the impact of speech rate, voice type, and emotional tone of robots on students' cognitive load, attitudes toward robot-assisted teaching, and learning performance. We recruited 477 Chinese primary school students assigned to either the speech rate, voice type, or emotional tone experiment. The results indicate that speech rate significantly influenced students' cognitive load, with the medium speed condition resulting in higher germane load compared to both fast and slow speed conditions. Moreover, students had a lower preference for adult male voices over adult female, boy, or girl voices. However, voice type did not significantly impact attitudes toward robot-assisted teaching or learning outcomes. Emotional tone did not affect students' cognitive load, attitudes, or learning performance. These findings provide valuable insights for instructors and designers when configuring the communication features of educational robots in classroom environments. Additionally, students generally prioritized the intelligence of the robot over its communication features, and they did not perceive the teaching content as difficult in all experiments. This study has methodological and practical significance.

While numerous studies of robot-assisted language learning (RALL) for English-as-a-foreign-language (EFL) learners' language skill development have been done, a comprehensive and theoretically-driven meta-analysis on its effects is still in paucity. To fill the gap, drawing on Activity Theory (AT), this study reported a meta-analysis from 47 independent studies out of 29 literature samples involving 1791 EFL learners on RALL for language skill development published during 2004-2023. The results indicated that the overall effect size was g = 0.69, 95% CI [0.49, 0.90], suggesting that RALL outperforms non-RALL conditions. In addition, educational levels and intervention durations were found to be significant moderators. Based on the results, implications for practice were discussed.

Experiential learning in biomedical engineering curricula is a critical component to developing graduates who are equipped to contribute to technical design tasks in their careers. This paper presents the development and implementation of an undergraduate and graduate-level soft material robotics design course focused on applications in medical device design. The elective course, offered in a bioengineering department, includes modules on technical topics and hands-on projects relevant to readings, all situated within a human-centered design course. After learning and using first principles governing soft robot design and exploring literature in soft robotics, students propose a new advance in the field in a hands-on design and prototype project. The course described here aims to create a structure to engage students in fabrication and the design approaches taken by practitioners in a specific field, applied here in soft robotics, but applicable to other areas of biomedical engineering. This teaching tips article details the pedagogical tools used to facilitate design and collaboration within the course. Additionally, we aim to highlight ways in which the course creates (1) opportunities to engage undergraduates in design in preparation for capstone courses, (2) outward facing opportunities to connect with practitioners in the field, and (3) the ability to adapt this hands-on experience within a typical lecture structure as well as a hybrid online and in-person offering, thus expanding its utility in bioengineering departments. We reflect on course elements that can inform future design-based course offerings in soft robotics and other design-based multidisciplinary fields in bioengineering.

Contribution: This work examines the impact of a unique precollege STEM education initiative during its two pilot years. The study contributes to the growing body of research by unpacking the needs of and the impact on an important stakeholder group (i.e., the teachers) in the engineering education ecosystem to help inform the future design and development of teacher professional learning models. Background: Efforts to provide precollege students with engineering or robotics-specific experiences are on the rise. These efforts are typically undertaken independently of one another. A first-of-its-kind collaboration between two precollege STEM initiatives aimed to break down existing silos between programs and offer a blended engineering and robotics curriculum targeting underserved schools. Research Questions: 1) How does a program designed to blend two existing engineering and robotics programs at the secondary school level impact teachers? and 2) What program elements are deemed valuable by participating teachers who are implementing a blended engineering and robotics program at the secondary school level? Methodology: Four focus groups were conducted with teachers (n = 16) over a period of two years. Data was analyzed using open coding and constant comparison methods. Findings: Four themes of growing confidence, exercising agency, responsive professional development, and support structures emerged across the four datasets. Collectively these themes capture pragmatic understandings of offering a new, blended precollege STEM program and advance an argument for the involvement of all stakeholders to support the teachers.

In today's societies, technology occupies a central position in different social spheres. In educational environments, robotics can act as an assistive tool for students with disabilities. More specifically, this tool helps autistic students in the development of attention, which is the fundamental skill in the cognitive and social development of the child, in activities in social contexts that are less stressful than human-human interaction. In this line, the aim of the study is to explore the application of robotics to favour communication and social interaction of autistic students, analysing attention. To this end, a pilot study was designed with the NAO robot in which four autistic students carried out activities related to imitation, play and social interaction. For data collection, the field notebook and an automatic system based on neural networks were used to calculate the child's attention during the activity. The results show that 75% of the subjects focus their attention on the robot during the interaction. Therefore, it is concluded that the robot acts as an activator of attention and social interaction in the tasks developed.

Technological tools are being used in support sessions with children with autism spectrum disorder (ASD), producing a high level of encouragement and engagement in these individuals. A four-step study comprising a focus group session, thinking aloud sessions, an online questionnaire, and a pilot study was conducted. First, a focus group session was conducted with professionals (n = 10) with different backgrounds that support children with ASD on a daily basis. Considering the outputs from the focus group, thinking aloud sessions with two specialists and an online questionnaire with 138 participants were conducted. Finally, a pilot study with four children with ASD was performed in order to test the constraints of the system. The goal of this article is to present findings concerning the design of social stories in a storytelling game that uses a new object with playware technology (OPT) as tangible interface with children with ASD. The storytelling game allows promoting the recognition of emotions in a triadic setup involving a robot, a child, and a professional or researcher. The key issue in this activity is to find the adequacy of the scenarios. The participants pointed out the main aspects to take into account in the development of the storytelling scenarios. New designs of the story scenarios were developed and the final design of the OPT was elaborated. The pilot study allowed to conclude that the children understood the mechanics of the games and successfully interacted with the new OPT.

Science teachers have been urged to use emerging technologies, such as robots, in ways that empower K-12 students as active participants responsible for their learning and knowledge development within the scientific domain. And yet, little is known about whether the use of robots effectively supports students' epistemic agency in science learning. The purpose of this qualitative case study was to investigate to what extent elementary preservice teachers use educational robots in ways that promote epistemic agency in science lessons. Seven data sources were gathered for this study: individual reflections about lesson planning and lesson design, team reflection about teaching with robots, robotics-enhanced science lessons, posters, video-recorded presentations about designed lessons, and participant interview. A framework of epistemic practices for science inquiry was adopted to analyze the data followed by qualitative thematic analysis. Results indicate that the use of robots in science lessons promotes content assimilation rather than self-driven inquiry, robot movement rather than evidence drives science explanations, science activities with robots are situated in a social vacuum, and robot assembly and programming are underutilized in the lessons. Implications for preservice science teacher education and future research are discussed.

Science, technology, engineering, and mathematics (STEM) curriculum and learning activities may help students learn social-emotional learning (SEL) competencies needed to support independence and community living, as well as 21st-century career development skills. Including robotics and coding curriculum in elementary classrooms can offer all students engaging academic experiences that include opportunities for students to problem solve, discuss ideas, and collaborate to find solutions. This article presents a vignette about a teacher's use of technology and robotics to engage a student with autism while supporting their SEL needs. The vignette was inspired by real scenarios in classrooms where educators have utilized technology to support students with disabilities and promote inclusive learning environments. Options for attainment and use of robotics and coding in the classroom are presented, including a future option through an open-educational resource, Project RAISE.

Computer science is often integrated within early childhood education (ECE) through the use of educational robots. This requires adequate preparation of ECE teachers to program and debug, which can be done with scaffolding. In this paper, we use a QUANT + qual mixed method approach incorporating lag sequential analysis, ICAP framework coding, sentiment analysis, and supplementary qualitative analysis. Students tended to engage more with tasks in the revision and evaluation phases than in the exploration phase, and became less dependent on scaffolding prompts and more competent in debugging, as debugging task complexity increased. This study addresses a key gap in the scaffolding literature in that it examined learners' interactions with scaffolding for evidence of decreased reliance on scaffolding.

Educational Robotics (ER) is an upcoming trend in education. It has been introduced in classrooms to improve the learning environment. It provides opportunities for young learners by promoting knowledge-building activities. STEM (Science, Technology, Engineering, and Mathematics) education is viewed as a catalyst to ensure a successful future in the context of real-world issues. ER is an innovative tool that can provide a roadmap for quality education. This study aims to investigate "What skill-set does ER (Educational Robotics) develop in young learners?", "How does robotics intervention affect young learners?", and "Whether Educational Robotics (ER) facilitates STEM education?". We systematically reviewed the literature on robotics and the importance of STEM, identifying the role of robotics in both formal and informal elementary and secondary classrooms, after-school programs, and summer camp activities. We used the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) methodology to analyze 20 relevant articles. We searched articles by using keywords and the snowballing technique. The study of recent applications of ER suggests that it aids in a precise and flexible understanding of STEM concepts.

Early Age Robotics (EAR) education has become extremely popular throughout the world. It has proven to be not only interesting and enjoyable, but also effective at helping even the youngest of children (aged 4-7) develop skills and reap educational benefits. But what about their families? Are parents as happy with EAR programs as are the children? What are their attitudes and beliefs regarding it? In this novel empirical study, we seek to answer these questions and succeed in refuting some commonly held beliefs. This study is based on a unique EAR program running since 2016 for over 2000 children. Using qualitative and quantitative research methods, we analyzed interviews with 29 parents and surveys submitted to 203 parents whose children (aged 4-7) studied technology and robotics as a compulsory component of their curriculum. We uncovered an interesting phenomenon of parents becoming transformed from being passive consumers of the educational system into new, twenty-first-century parents, more confident about their ability to learn and to help promote their children's abilities. They are more motivated and involved, and ready to invest in both their own and their children's learning. Also encouraging is the gender equality found in this technological area. We recommend introducing a new PEAR (Parents in EAR) model, offering practical proposals for enhancing and expanding robotics education. The study confirms parents' satisfaction with technology, their willingness to learn more about robotics, and their satisfaction with their children's participation in an EAR program. This transformation should be considered by EAR stakeholders.

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.

Educational robotics has been adopted to create interactive and engaging learning environments to develop computational thinking (CT) in K-12 learners. This study systematically examined 22 peer-reviewed empirical research articles on the use of educational robotics to develop CT in young learners (pre-kindergarten to 6th grade) published between 2012 and 2021. The findings revealed that using robotics activities to develop CT has mostly been studied in the formal education settings with the duration of robotics curricular activities ranging from 80 minutes to 24 hours. The five CT skills studied most often include Sequencing, Conditionals, Loops, Debugging, and Algorithmic Thinking. The different versions of LEGO Mindstorms are the most frequently adopted robotic kits in the examined studies. The most frequently adopted learning and instructional strategies in the robotics activities include collaborative learning, project-based learning, and embodied learning. This paper identified and discussed developmentally appropriated CT skills, robotics kits, and pedagogical approaches suitable for supporting CT development in young learners. The findings can guide educators and instructional designers for future robotics activity design and development endeavors. This paper also identified gaps in the current research and recommended directions for advancing research in adopting robotics to develop CT in young learners.

Uzbekistan has not adopted robotics education as the school curriculum yet. However, several robotics learning centers have introduced robotics education in an informal setting. This research paper aims to highlight the essence of robotics education in Uzbekistan investigating the perception of parents and children to their full potential and identifying impediments to the process of implementing robotics in Uzbekistan. This research study involves primary and secondary research methods. A systematic literature review was conducted to examine the reflection of robotics education among primary and secondary school children. Official statistical data was gathered to prove the scope of demographics. Primary data was collected through the survey among parents whose children attended robotics classes. Ultimately, the authors have used empirical evidence to provide recommendations and solutions on how to implement robotics education effectively in Uzbekistan. Much emphasis has not been put on robotics education in Uzbekistan, despite reforms in the field of STEM education. Moreover, the condition (including teachers, lesson materials, classrooms, computers, and robotics kits) to implement robotics classes as more developed countries are doing has not been created properly, which hampers the introduction of robotics at schools. In addition, the majority of parents are not fully aware of the authentic value of robotics education in children's lives. Hence, Uzbek schools are lagging in the field of robotics.

Tangible programming combines the advantages of object manipulation with programmable hardware, which plays an essential role in improving programming skills. As a tool for ensuring the quality of projects and improving learning outcomes, the PDCA cycle strategy is conducive to cultivating reflective thinking. However, there is still a lack of empirical research on the effect of introducing the PDCA cycle strategy into programming education. In this study, using a PDCA cycle strategy, in a four-pronged model of "(P)draw up a plan, (D)assemble and programming, (C)test and debug, display and reflect (A)," and its effects on students' programming skills and their reflective thinking were explored. There were 65 children between the ages of 7 and 8 years participated in this study. There were 31 students in each of the experimental group and the control group. A combination of qualitative and quantitative research methods was adopted in this research, and students' programming processes and results were observed and counted. The study results revealed that after attending the 'Magic Card Robot' course that applied the PDCA cycle strategy, the experimental group students outperformed their counterparts in programming skills (sequencing, repetitive and conditional structures). Meanwhile, the experimental group students' reflective thinking levels were higher than those of the control group students. These findings imply that tangible programming education using the PDCA cycle strategy in the course has potential.

What is the optimal penalty for errors in infant skill learning? Behavioral analyses indicate that errors are frequent but trivial as infants acquire foundational skills. In learning to walk, for example, falling is commonplace but appears to incur only a negligible penalty. Behavioral data, however, cannot reveal whether a low penalty for falling is beneficial for learning to walk. Here, we used a simulated bipedal robot as an embodied model to test the optimal penalty for errors in learning to walk. We trained the robot to walk using 12,500 independent simulations on walking paths produced by infants during free play and systematically varied the penalty for falling--a level of precision, control, and magnitude impossible with real infants. When trained with lower penalties for falling, the robot learned to walk farther and better on familiar, trained paths and better generalized its learning to novel, untrained paths. Indeed, zero penalty for errors led to the best performance for both learning and generalization. Moreover, the beneficial effects of a low penalty were stronger for generalization than for learning. Robot simulations corroborate prior behavioral data and suggest that a low penalty for errors helps infants learn foundational skills (e.g., walking, talking, and social interactions) that require immense flexibility, creativity, and adaptability.

Taking into account the profound impact of technology on modern education, especially during the COVID-19 pandemic, increasing academic interest has focused towards the design and application of such tools on different learning contexts. A specific area of Human-Computer Interaction, called affordance theory, focuses on the perception, design and use of different technologies by educators and learners in learning contexts. This paper explores the impact of affordances in the process of creative problem in the context of playful educational robotics, with an intension of informing the design of future educational experiences around the field. The study capitalizes upon previous affordance propositions and frameworks in order to establish an affordance-based framework in the scope of playful educational robotics contexts, through the adoption of a qualitative research methodology, which was considered more appropriate as an exploratory tool. As part of the qualitative analysis, the study is mapping different types of affordances, related to such technologies, as well as an iterative creative problem-solving process that stems from learners' interactions with robotic artifacts, like the CreaCube playful robotics activity, which is presented in this study.

Artificial intelligence aims to restructure and process re-engineering education and teaching processes and accelerate the evolution of the whole education system from information to intelligence. Robotic Process Automation (RPA) robots learn by observing people at work, analyzing user processes repeatedly, and adjusting or correcting automated processes. By using Natural Language Processing (NLP) and Machine Learning (ML), knowledge representation, inference, large-scale parallel computing, and Rapid Domain Adaptation, RPA robots can automatically extract the data needed for decision-making and continuously learn from users' feedback. We have used RPA and predictive analytics to provide distance learning students with the Intelligent Tutoring Robot (ITR), which can provide an automatic response. By optimizing the ITR in the above context, we have examined the feasibility of transforming a prediction model, using a student learning database, into an early-warning system. This article adopts the randomized control-group pretest-posttest design, dividing 123 students into a control group to describe interactions between ITR and students and experimental groups to describe interactions between human teachers and students. The findings present no significant difference between the control and the experimental groups in terms of academic performance, however higher average marks were achieved in the former group.

Technology education has become increasingly important during the last few decades. Previous studies, however, have paid insufficient attention to technology education for young children aged 3-8 years, compared to research in other age groups. This study presented a comprehensive overview of technology education in early childhood education studies, including curriculum, tools, research methods, and learning effects. The study found that technology education in ECE has grown fast as a result of technical breakthroughs, greater research funding, and increasing international interest in this field. Based on a systematic review approach, we confirmed the research focused on themes such as curriculum, robotics, programming, attitudes, and opinions between 2003 and 2021. This review examined 25 research papers on technology education in early childhood education. This study also indicated that future research directions, including comparing robot learning to traditional learning, using robots to improve students' skills, thinking and problem-solving abilities, and assessing the effectiveness of using robots in learning and teaching. This study offers a holistic view of technology education research in early childhood education and provides future researchers with directions.