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Robobo SmartCity: An Autonomous Driving Model for Computational Intelligence Learning Through Educational Robotics
Abstract
This paper presents the Robobo SmartCity model, an educational resource to introduce students in Computational Intelligence (CI) topics using educational robotics as the core learning technology. Robobo SmartCity allows educators to train learners in Artificial Intelligence (AI) fundamentals from a feasible and practical perspective, following the recommendations of digital education plans to introduce AI at all educational levels. This resource is based on the Robobo educational robot and an autonomous driving setup. It is made up of a city mockup, simulation models, and programming libraries adapted to the students' skill level. In it, students can be trained in CI topics that support robot autonomy, as computer vision, machine learning, or human-robot interaction, while developing solutions in the motivating and challenging scope of autonomous driving. The main details of this open resource are provided with a set of possible challenges to be faced in it. They are organized in terms of the educational level and students' skills. The resource has been mainly tested with secondary and high school students, obtaining successful learning outcomes, presented here to inspire other teachers in taking advantage of this learning technology in their classes.
... According to Amo et al. (2021) and Naya-Varela et al. (2023), ER is congruent with the use of active methodologies that promote STEM disciplines, such as learning by doing, cooperative learning and project-based learning (PBL). According to Chang and Chen (2020), the ER is a very valid tool to address integrated learning models such as interdisciplinary learning through integrated STEM education. ...
... In order to promote student learning in STEM disciplines, various integrated proposals have emerged, such as the one addressed by researchers Naya-Varela et al. (2023), who use ER in secondary and high school students as a teaching-learning resource for computational intelligence and artificial intelligence through the use of autonomous robots, favoring the resolution of challenges. ...
... Regarding educational experts, in the case of Greece, they explicitly state in their evaluation the need for students to be trained in cooperative and collaborative learning techniques, as effective communication skills are needed to deal with such practices. The Spanish and Turkish experts infer the need for such practices to set out in detail how to approach methodologies such as cooperative learning and the engineering design process (EDP) in the activities, as well as to carry out a thorough evaluation of their implementation in order to improve their usefulness and impact.Looking at the global scientific literature, there are a large number of studies and practices that address PBL together with cooperative and collaborative learning(Camargo et al., 2015;Foukarakis & Syrris, 2018;Galino & Tanaka, 2021;Hartigan & Hademenos, 2019; Karaahmetoglu & Korkmaz, 2019;Karaman et al, 2017;Naya-Varela et al., 2023; Sklirou, 2019;Valko & Osadchyi, 2021;Valls Pou et al., 2022;Vega & Cañas, 2019;Zhong et al., 2022), so there is theoretical and practical consistency in the use of both methodologies in good practices. ...
Integrated STEM education and educational robotics (ER) represent two topics of maximum interest in the current educational reality, being necessary an investigation of their theoretical and practical approaches. To this end, a search and compilation of the characteristics of ten good practices that have implemented both approaches in Higher Education was carried out in each of the five European countries. These practices were then evaluated by teachers and educational researchers to select the two best practices in each country. The theoretical and practical consistency of the characteristics of the ten best practices with those of other studies at global level was then discussed and several conclusions and improvements in European practices were drawn. The results support the use of cooperative and collaborative learning together with project-based learning by integrating at least two STEM disciplines in an interrelated way, including the use of reflective methodologies such as inquiry-based science teaching and the engineering design process using integrated models such as transdisciplinary approaches to enhance student learning and engagement. The consistent use of the commercial robot kits and the need for customized robots is highlighted, and the use of low-cost open-source programming boards and open design robots is included as an improvement. The promotion of co-education is highlighted as lacking, with a need to improve practices aimed at researching and improving girls’ interest in pursuing STEM studies. Finally, a few limitations and future lines of research are indicated.
... The choice of sensors and actuators varies widely and is largely dictated by the specific requirements of the use case. The greater the number of different sensors and actuators in a robot, the more varied tasks can be designed [4,14]. Possible sensors and actuators can be cameras, microphones, environmental sensors, loudspeakers, LEDs, or screens [14]. ...
... The greater the number of different sensors and actuators in a robot, the more varied tasks can be designed [4,14]. Possible sensors and actuators can be cameras, microphones, environmental sensors, loudspeakers, LEDs, or screens [14]. However, it is important to note that if the robot can be expanded, upgrading sensors and actuators is also feasible. ...
The emergence of educational robots has revolutionized the manner in which students access education, leading to a surge in the popularity of educational robots. The process of selecting the right robot hardware for educational purposes holds great importance, as it can significantly impact the learning experience and subsequent outcomes. Due to the continuously growing market of educational robots, several critical factors must be carefully considered to effectively choose the most suitable robotic kit for a specific educational activity. Our study has two primary objectives: Firstly, it aims to identify crucial criteria for selecting an educational robot by conducting a thorough review of existing literature. Secondly, our goal is to offer a comprehensive guideline that meticulously outlines seven steps for choosing the most suitable robot. In addition, we provide guidance on the practical application of our policy through the use of a case study.
... Building upon Chin's groundwork, Martin Naya-Varela et al.'s [24] introduction of the Robobo SmartCity model extends the scope of educational robotics into the realm of computational intelligence (CI), offering a tangible, hands-on experience with AI fundamentals through the lens of autonomous driving. The model's success with secondary and high school students in enhancing understanding of complex CI topics, including computer vision, machine learning, and human-robot interaction, showcases the broader applicability and effectiveness of robotics in education. ...
... The findings from studies such as those by Kai-Yi Chin [8] and Martin Naya-Varela et al. [24] highlight the immediate benefits of integrating robotics into educational settings. Robotics not only enhances student engagement and motivation but also facilitates a deeper understanding of complex subjects like computational intelligence and artificial intelligence. ...
... The digital learning model for teachers is a model that leverages digital technology to improve teaching effectiveness by providing students with a personalized learning experience [1] . With this model, teachers analyze data on students' learning behaviors, interests, and cognitive abilities, then provide customized learning paths for each student based on the results of the analysis [2] . For example, for different cognitive abilities, teachers deliver personalized learning materials, tutoring suggestions, and homework arrangements to meet each student's learning needs [3] . ...
Digital Learning Models for Teachers is an important development in the field of education to improve the effectiveness of teaching through digital technology to create learning experiences with personalization and customization by providing teachers with more accurate feedback on their teaching. However, the current problem is that the learning question types need to be recommended according to the individual needs of students, which leads to inadequate learning effects. To solve the abovementioned problem, this paper proposed a personalized recommendation algorithm based on a graph neural network for teachers’ digital learning models(PRAGNN). In particular, firstly, the method of integrating DINA cognitive diagnosis and gray partial correlation evaluation is used to construct a student model by modeling the mastery of knowledge points and cognitive ability level for students. Secondly, a graph convolutional neural network is introduced and combined with the sequential relationship between subject knowledge points to automatically capture the semantic information of higher-order structures in the knowledge points to achieve personalized recommendations. Ultimately, the algorithm achieved 85.7% accuracy through comparative experiments. This research provides a new idea for the construction of a personalized recommendation system for the digital learning model of teachers, which is expected further to improve the learning effect in the field of education.
... This platform uses Bluetooth as communication access. Robobo SmartCity uses high computing and communication systems and is equipped with sophisticated actuators [26]. ...
The industrial revolution 4.0 brings the era of society 5.0 which has an impact on various aspects of life, one of which is the field of education by starting to apply the use of AI in learning. AI is very relevant to be applied to STEM-based science learning. The purpose of this study is to analyze the effectiveness of AI-based STEM implementation in science learning, analyze learning media that use AI based STEM, and analyze the ethics and potential use of AI in future science learning. The research method used is a literature study on international journal databases on ERIC, Scopus, and Springer. Based on the literature review, it was found that the implementation of AI based STEM is effective in science learning. AI can increase creativity, activeness, train technological literacy skills, train problem solving and support to generate creative ideas. There are also AI learning media that can be applied to STEM learning. In addition, the implementation of AI use in education also pays attention to the code of ethics so that the use of AI can be useful. In conclusion, AI based STEM is effective, there are AI based STEM media that have been used in science learning, and there is potential for the use of AI in science learning in the future.
... In this way, the BN can update its probabilities in real time based on changing conditions, such as varying light or weather conditions, and maintain high detection accuracy. The BN can also be used to classify objects based on sensor data and contextual information such as the location or movement pattern of the object [7]. With this probabilistic classification approach, the AI system can make better decisions about how to respond to different types of objects, minimising false positives or negatives and maximising safety [8]. ...
Embedded Artificial Intelligence (AI) systems are important components of autonomous vehicles. However, incorporating AI into autonomous vehicles is technically complex, due to the constraints of computation, real-time processing of data, uncertainty handling, and hardware limitations. Bayesian Networks (BNs) are a promising method that allows probabilistic modelling in adaptive learning and environment perception. Here we report on an overview of the application of BNs on autonomous driving, with an emphasis on how BNs can be optimized for embedded system resource constraints, including both computational and energy. Various optimization techniques are discussed, such as model pruning, approximation, acceleration using hardware accelerators, such as Field-Programmable Gate Arrays (FPGA) and Application Specific Integrated Circuit (ASICs), and advanced cooling and power management to ensure AI reliability under high computational load. By reviewing these approaches, we aim to contribute to the development of more robust and green AI systems for autonomous driving.
... All the previous robots were not designed for teaching AI, so they lack of basic features required in this scope to deal with the five ideas commented above (Naya-Varela et al. 2023): (1) In terms of sensors, they should allow natural interaction with humans and the environment, which means including camera, microphone, and tactile sensing; (2) Support a wide range of actuations, like locomotion, manipulation, speech production (speaker) or visual communication (LCD screens); (3) Support the execution of complex algorithms, like those related to computer vision, reasoning, or machine learning; (4) Being equipped with a wide spectrum of communication technologies, like WiFi, Bluetooth, 5G or similar, and support internet connection; (5) Support different programming languages adapted to the educational levels, which allow to integrate external AI libraries or functionalities; (6) Have a simulation model, so students can work in a controlled and simple fashion before moving to the real robot, reducing also the number of physical platforms at schools and their required investment; (7) Including adapted teaching materials to face the five main AI topics, that teachers can use directly. ...
Artificial Intelligence (AI) will have a major social impact in the coming years, affecting today’s professions and our daily routines. In the short-term, education is one of the most impacted areas. The autonomous decision making that can be achieved with tools based on AI implies that some of the traditional methodologies associated with the fundamentals of the learning process in students, must be reviewed. Consequently, the role of teachers in the classroom may change, as they will have to deal with such AI tools performing parts of their work, and with students making a common use of them. In this scope, the AI in Education (AIEd) community agrees on the key relevance of developing AI literacies to train teachers and students of all educational levels in the fundamentals of this new technological discipline, so they can understand how these tools based on AI work and pilot the adaptation in an informed way. This implies teaching students about the fundamentals of topics like perception, representation, reasoning, learning, and the impact of AI, with the aim of delivering a solid formation in this area. To support them, formal teaching and learning resources must be developed and tested with students, properly adapted to different educational levels. The main contribution of this proposal lies in the presentation of the Robobo Project, a technological tool based on intelligent robotics that supports such formal AI literacy training for a wide range of ages, from secondary school to higher education. The core part of this paper is focused on showing the possibilities the Robobo Project offers to teachers in a simple way, and how it can be adapted to different levels and skills, leading to a long-term educational proposal. Validation results that support the feasibility of this technology in the education about AI, obtained with students and teachers in different educational levels during a period of six years, are presented and discussed.
... This is also consistent with frameworks and policies, as emerged through the SWOT analysis and with our reflection on Theory of Mind and child-robot interactions. Naya and Varela [69] argued that coding and educational robotics can expose students to a real world, where-as Dennett showed us-algorithms do not usually work as intended. Some authors [70] have suggested using robotics for this purpose as a branch of AI that includes design thinking, mathematics, and computational thinking. ...
The pervasiveness of technologies leads us to talk about a code society. From an educational point of view, coding, computational thinking, and educational robotics are an open possibility. Nevertheless, new elements such as artificial intelligence are rapidly changing educational technology perspectives. In this work, we will analyze school policies and theoretical bases in order to understand if, and under what kind of, condition coding, computational thinking, and educational robotics still represent the qualifying elements of a framework for digital literacy and digital citizenship.
... Furthermore, different simulation tools suitable for various educational levels and skills are available [17]. One of these tools is RoboboSim [15], a 3D realistic simulator used in this TU to introduce students to reinforcement learning. ...
This work presents the objectives, methodologies, and preliminary outcomes of the first training activity (TA1) within the AIM@VET project, an EU initiative aimed at integrating artificial intelligence (AI) into vocational education and training (VET) to align with labor market demands. Addressing the noticeable gap in AI education across various educational levels, AIM@VET, involving six partners from Spain, Portugal, and Slovenia, focuses on developing teacher-centered learning modules in key AI application areas: computer vision, robotics, and ambient intelligence. The project’s methodology involves universities in content preparation and VET teachers in content delivery to students, with an iterative feedback loop enhancing the curriculum’s relevance and effectiveness. TA1 demonstrated a practical approach to applying AI concepts through a mix of theoretical lessons and hands-on tasks, significantly improving students’ technical AI skills and readiness for the digital workforce. The activity underscored the importance of standardizing lesson creation protocols to produce a unified curriculum, thereby facilitating improved coordination among partners. This chapter will detail the project’s framework, its execution, and an analysis of the results obtained in the project’s first steps.
... Educational robotics, notably employing tools like the Bee-Bot, has emerged as a promising avenue for nurturing CT in pre-primary children. Studies have unveiled the remarkable engagement of children as young as four in CT activities through robotics, showcasing their adeptness in effectively interacting with and programming such robotic entities (Alam, 2023a;Alam & Mohanty, 2022c;Conde et al., 2020;Eguchi, 2023b;Kachisa & Gustavsson, 2019;Naya-Varela et al., 2023). Yet, prevailing research predominantly delves into cursory explorations of children's interactions with these tools, the facilitation of learning through educational robotics, and the introduction of robotics and programming concepts to young learners. ...
The researchers developed an Integrated Constructive Robotics in Education (ICRE) model that represents a pioneering framework designed to revolutionize educational landscapes by integrating robotics into pedagogical settings. This research introduces the ICRE model, elucidating its multifaceted dimensions and envisioning its profound impact on educational paradigms. The ICRE model emerges as a comprehensive framework that amalgamates constructivist principles with robotics technology, fostering an environment conducive to active, experiential learning. Anchored in constructivist pedagogy, the model accentuates hands-on, immersive experiences where students engage in designing, programming, and manipulating robots. This tactile engagement not only stimulates curiosity but also empowers students to witness direct outcomes, cultivating a profound sense of agency and ownership in their learning journey. Central to the ICRE model is its versatility, catering to interdisciplinary activities that transcend conventional disciplinary boundaries. By nurturing a deeper conceptual understanding and honing higher-order cognitive skills within Science, Technology, Engineering, and Mathematics (STEM) subjects, the model serves as a catalyst for holistic development. The transformative potential of the ICRE model extends beyond technical skill acquisition, encapsulating motivational, cooperative, and creative dimensions. It addresses gender disparities within STEM education, endeavoring to mitigate gaps in interest and skills. Furthermore, the ICRE model emphasizes the importance of teacher training, equity in access, and collaboration between educators, researchers, and industry professionals. This paper unfolds a detailed conceptual framework of the ICRE model, articulating its core principles, applications, and implications. It navigates through its developmental journey, positing future trajectories and recommendations for its sustained evolution.
... The above can be observed in the number of studies and reviews that have focused on the use of rigid robotics as in [28]- [30]. Furthermore, recent studies have developed educational platforms composed primarily of rigid robots [20], [21], [23], [111], [112]. The above suggests that while robotics has been an element of interest in recent years, soft robotics are underused as an educational platform. ...
Educational robotics (ER) is a discipline of applied robotics focused on teaching robot design, analysis, application, and operation. Traditionally, ER has favored rigid robots, overlooking the potential of soft robots (SRs). While rigid robots offer insights into dynamics, kinematics, and control, they have limitations in exploring the depths of mechanical design and material properties. In this regard, SRs present an opportunity to expand educational topics and activities in robotics through their unique bioinspired properties and accessibility. Despite their promise, there is a notable lack of research on SRs as educational tools, limiting the identification of research avenues that could promote their adoption in educational settings. This study conducts a Systematic Literature Review (SLR) to elucidate the impact of SRs across academic levels, pedagogical strategies, prevalent artificial muscles, educational activities, and assessment methods. The findings indicate a significant focus on K-12 workshops utilizing soft pneumatic actuators. Furthermore, SRs have fostered the development of fabrication and mechanical design skills beyond mere programming tasks. However, there is a shortage of studies analyzing their use in higher education or their impact on learning outcomes, suggesting a critical need for comprehensive evaluations to determine their effectiveness, rather than solely relying on surveys for student feedback. Thus, there is an opportunity to explore and evaluate the use of SRs in more advanced settings and multidisciplinary activities, urging for rigorous assessments of their influence on learning outcomes. By undertaking this, we aim to provide a foundation for integrating SRs into the educational robotics curriculum, potentially transforming teaching methodologies and enriching students' learning experiences.
... Sin embargo, es esencial abordar la brecha de acceso a estas oportunidades, asegurándose de que estudiantes de todos los géneros y grupos demográficos tengan igualdad de acceso a la robótica educativa. Al hacerlo, se fomenta un ambiente inclusivo que promueve la diversidad y empodera a la próxima generación de líderes en STEM, impulsando así la innovación y el progreso en la sociedad (Naya-Varela et al., 2023). ...
INTRODUCCIÓN. El porcentaje de mujeres que cursan titulaciones STEM (Science, Technology , Engineering and Mathematics) es inferior al de hombres, debido a condicionamientos socia-les, estructuras institucionales, asesoramiento deficiente y entornos de aula de educación tem-prana hacia otras áreas. En concreto, algunos estudios empiezan a evidenciar la brecha de género que se produce en este ámbito primordial para el desarrollo de la sociedad. En esta línea, la robótica educativa se ha convertido en una herramienta efectiva para contribuir a despertar vocacio-nes en el ámbito STEM. MÉTODO. El objetivo de este trabajo fue desarrollar la actitud y compe-tencia STEM a través de la robótica en las maestras en formación del Grado en Educación Primaria, para ello se aplicó un diseño cuasiexperimental con pretest-postest, donde participaron un total de 104 estudiantes. RESULTADOS. El grupo experimental que trabajó de forma práctica con robótica educativa durante 13 semanas obtuvo una mayor puntuación postest que indicó un aumento de la actitud y competencia STEM en comparación con el grupo control. No obstante, no se encontraron diferencias significativas intragrupo ni intergrupo. DISCUSIÓN. Aprender de forma práctica materias STEM motiva hacia la predisposición de profundizar en programación, mejora las actitudes y competencias STEM a través de la robótica educativa en las aulas, favorece la inclusión de las estudiantes en dichas materias y reduce la brecha de género existente. Finalmente, fomentar la motivación y vocación en materias STEM puede incidir en el hecho de que las maestras en formación incorporen en su posterior ejercicio de la docencia elementos STEM como la robótica, pudiendo desarrollar experiencias positivas y motivadoras en las aulas de edu-cación primaria, para que el alumnado pueda disfrutar aprendiendo robótica y propiciando que se despierte la curiosidad por el aprendizaje de estas materias.
... A hybrid approach by combining Faster RCNN and YOLOv5, known as Ensem-bleNet, has been shown in [30] to improve the overall perfor-mance of vehicle detection in dense traffic scenarios. Integration of convolution neural networks with 2D object detection algorithms in predicting 3D bounding boxes are witnessing an immense improvement in performance, leading to many advancements in autonomous driving and robotics [31]- [33]. Authors in [9] claim a high-accuracy 3D object detection model which utilizes a multi-view 3D network with RGB images and LiDAR point cloud as input for prediction of the 3D bounding boxes. ...
In the absence of depth-centric sensors, 3D object detection using only conventional cameras becomes ill-posed and inaccurate due to the lack of depth information in the RGB image. We propose a multi-camera perception solution to predict the 3D properties of the vehicle obtained from the aggregated information from multiple static infrastructure-installed cameras. While a multi-bin regression loss has been adopted to predict the orientation of a 3D bounding box using a convolutional neural network, combining it with the geometrical constraints of a 2D bounding box to form a 3D bounding box is not accurate enough for all the driving scenarios and orientations. This paper leverages a vision transformer that overcomes the drawbacks of convolutional neural networks when there are no external LiDAR or pseudo-LiDAR pre-trained datasets available for depth map estimation, particularly in occluded regions. By combining the predicted 3D boxes from various cameras using an average weighted score algorithm, we determine the best bounding box with the highest confidence score. Comprehensive simulations for performance analysis are shown from the results obtained by utilizing the KITTI standard data generated from the CARLA simulator.
This study utilizes a mixed-methods approach, combining thematic analysis and bibliometric analysis, to explore the complex landscape of artificial intelligence (AI) integration in STEM education. Through a meticulous search of the journal articles in the Web of Science and Scopus databases, utilizing keywords "STEM" and "artificial intelligence," we identified 490 publications from various research domains, including Education, Social Sciences, Philosophy, History, Psychology, Arts and Humanities, Communication, and Behavioral Sciences. After a stringent screening and the removal of duplicates, 66 articles published between January 2009 and February 2024 were extracted. Our findings indicate a notable upward trajectory in the number of publications , particularly since 2021, with 2023 emerging as the pinnacle year, housing 50% of the total publications. The thematic analysis of the articles reveals five overarching themes: 1) Integration of Modern Technology in Education; 2) AI in Educational Support Systems; 3) AI in Curriculum Development; 4) Impact of AI on Student Learning Outcomes; and 5) Inclusivity, Diversity, Equity, and Policy Considerations. Furthermore, our study illuminates emerging trends, influential works, and collaborative networks within this field, while also exploring the extent of Open Access availability, thereby fostering opportunities for knowledge dissemination and collaboration. In sum, this research enriches our comprehension of the current landscape and future trajectories of AI integration in STEM education, offering valuable insights for researchers, educators , and policymakers.
Resumen: Introducción: La robótica educativa proporciona un ecosistema de aprendizaje práctico en un entorno lúdico con una combinación de actividades, herramientas, y tecnologías pedagógicas, que atraen y motivan a estudiantes en el nivel de educación media a aprender y aplicar las habilidades y conocimientos en informática, programación, tecnología, matemáticas y ciencias. Metodología: Para la revisión bibliométrica se utiliza la pregunta ¿Cuál es el uso que se hace de la Robótica Educativa en la educación media? Con el interés de realizar un procedimiento metódico y riguroso se empleó la metodología PRISMA. Resultados: Las evidencias de los hallazgos encontrados se presentan sistematizadas mediante matriz de análisis y tablas de frecuencia. Discusión: La robótica educativa y los concursos de robótica además de educación STEM (educación técnica) también fortalecen elementos (i) intrasubjetivos, (ii) intersubjetivos y (iii) proyecto de vida, los cuales pueden caracterizarse como desarrollo de competencias socioemocionales (educación humanística) que se forman bajo un enfoque pedagógico de escuela activa, aprendizaje experiencial y métodos centrados en el estudiante, que estimulan el pensamiento crítico y creativo que conducen a la creación libre y genuina del componente socioemocional Conclusiones: La educación socioemocional, habilidades de trabajo en equipo y comunicación son aprendizajes transversales a la robótica. educativa.
The latest technologies in natural language processing (NLP) provide creative, knowledge retrieval and question-answering technologies in the design of intelligent education, which can provide learners with personalized feedback and expert guidance. Entrepreneurship education aims to cultivate and develop the innovative thinking and entrepreneurial skills of students, making it a practical form of education. However, a knowledge retrieval and question-answering teaching assistant system for entrepreneurship education has not been proposed. This observation motivated us to develop a reading comprehension framework to address the challenges of domain-specific knowledge gaps and the weak comprehension of complex texts encountered by Intelligent education models in practical applications. The proposed framework mainly includes: question understanding, relevant knowledge retrieval, mathematical calculation and answer prediction. The techniques involved in the above modules mainly include text embedding, similarity retrieval, graph convolution and long-short term memory network. By integrating this model into entrepreneurship courses, learners can participate in real-time discussions and receive immediate feedback, creating a more dynamic and interactive learning environment. To assess the effectiveness of the proposed model, this paper conducts answer prediction on single-choice exercises related to entrepreneurship education courses. This study employing the potential of using a question-and-answer format to enhance intelligent entrepreneurship education, paving the way for a more effective and engaging online learning experience.
This paper presents a proposal of specific curriculum in Artificial Intelligence (AI) for high school students, which has been organized as a two-year subject. The curriculum was designed based on two premises. The first one is that, although the proposal is targeted to scientific programmes, the involved students and teachers do not have any previous knowledge about AI. Accordingly, the teaching units have been designed with the aim of supporting teachers in a new discipline for them and, in addition, providing an introductory level to students. The main didactical objective is to establish the fundamentals of AI from a practical perspective, learning technical concepts by using them to solve specific problems. The approach that has been followed in the teaching units is focused on developing embedded intelligence solutions, that is, programming real-world devices which interact with real environments. To this end, and to address a second fundamental premise of low investment capability at schools, it has been decided to use Smartphones as the central technological element to implement such embedded intelligence at classes. This curriculum has been developed within the Erasmus + project entitled "AI + : Developing an Artificial Intelligence Curriculum adapted to European High School". The project was carried out by a team of AI experts and high school teachers who created the teaching units, and a group of students that tested them for three years, providing feedback to make the curriculum feasible for its introduction in schools in the short-term. The main results obtained from its implementation within the project scope are presented and discussed here, with the aim of contributing to the AIEd community progress by means of a practical pilot experience. Although the curriculum has been designed and tested at European level, it has been created with a general perspective of AI education, so it can be applied worldwide.
The number of available tools for dynamic simulation of robots has been growing rapidly in recent years. However, to the best of our knowledge, there are very few reported quantitative comparisons of the most widely-used robot simulation tools. This article attempts to partly fill this gap by providing quantitative and objective comparisons of four widely-used simulation packages for mobile robots. The comparisons reported here were conducted by obtaining data from a real Husky A200 mobile robot driving on mixed terrains as ground truth and by simulating a 3D mobile robot model in a developed identical simulation world of these terrains for each simulator. We then compared the simulation outputs with real, measured results by weighted metrics. Based on our experiments and selected metrics, we conclude that CoppeliaSim is currently the best performing simulator, although Gazebo is not far behind and is a good alternative.
Artificial Intelligence (AI) has spread across industries (e.g., business, science, art, education) to enhance user experience, improve work efficiency, and create many future job opportunities. However, public understanding of AI technologies and how to define AI literacy is under-explored. This vision poses upcoming challenges for our next generation to learn about AI. On this note, an exploratory review was conducted to conceptualize the newly emerging concept “AI literacy”, in search for a sound theoretical foundation to define, teach and evaluate AI literacy. Grounded in literature on 30 existing peer-reviewed articles, this review proposed four aspects (i.e., know and understand, use, evaluate, and ethical issues) for fostering AI literacy based on the adaptation of classic literacies. This study sheds light on the consolidated definition, teaching, and ethical concerns on AI literacy, establishing the groundwork for future research such as competency development and assessment criteria on AI literacy.
This paper focuses on long-term education in Artificial Intelligence (AI) applied to robotics. Specifically, it presents the Robobo SmartCity educational framework. It is based on two main elements: the smartphone-based robot Robobo and a real model of a smart city. We describe the development of a simulation model of Robobo SmartCity in the CoppeliaSim 3D simulator, implementing both the real mock-up and the model of Robobo. In addition, a set of Python libraries that allow teachers and students to use state-of-the-art algorithms in their education projects is described too.
Artificial intelligence (AI) is envisioned as a new tool to accelerate the progress towards the achievement of SDG 4. Policies and strategies for using AI in education are central to maximizing AI’s benefits and mitigating its potential risks. Fostering AI-ready policy-makers is the starting point of the policy development process.
This publication offers guidance to policy-makers in understanding AI and responding to the challenges and opportunities in education presented by AI. Specifically, it introduces the essentials of AI such as its definition, techniques, technologies, capacities and limitations. It also delineates the emerging practices and benefit-risk assessment on leveraging AI to enhance education and learning, and to ensure inclusion and equity, as well as the reciprocal role of education in preparing humans to live and work with AI.
The publication summarizes three approaches to the policy responses from existing practices: independent approach, integrated approach and thematic approach. In a further step, it proposes more detailed recommendations and examples for planning AI and education policies, aligned with the recommendations made in the 2019 Beijing Consensus on AI and Education.
Educational robotics (ER) seems to have a positive effect on students and, in many cases, might help them to successfully assimilate knowledge and skills. Thus, this paper focuses on ER and carries out a literature review on educational robotics simulators with Graphical User Interfaces (GUIs). The review searches for relevant papers which were published in the period 2013–2020 and extracted the characteristics of the simulators used. The simulators that we describe in this article cover various robotic technologies, offering students an easy way to engage with virtual robots and robotics mechanisms, such as wheeled robots or drones. Using these simulators, students might cover their educational needs or prepare themselves for educational robotic competitions by working in as realistic as possible conditions without hardware restrictions. In many cases, simulators might reduce the required cost to obtain a robotic system and increase availability. Focusing on educational robotics simulators, this paper presents seventeen simulators emphasizing key features such as: user’s age, robot’s type and programming language, development platform, capabilities, and scope of the simulator.
Motivated by the recent explosion of interest around Educational Robotics (ER), this paper attempts to re-approach this area by suggesting new ways of thinking and exploring the related concepts. The contribution of the paper is fourfold. First, future readers can use this paper as a reference point for exploring the expected learning outcomes of educational robotics. From an exhaustive list of potential learning gains, we propose a set of six learning outcomes that can offer a starting point for a viable model for the design of robotic activities. Second, the paper aims to serve as a survey for the most recent ER platforms. Driven by the growing number of available robotics platforms, we have gathered the most recent ER kits. We also propose a new way to categorize the platforms, free from their manufacturers’ vague age boundaries. The proposed categories, including
No Code
,
Basic Code
, and
Advanced Code
, are derived from the prior knowledge and the programming skills that a student needs to use them efficiently. Third, as the number of ER competitions, and tournaments increases in parallel with ER platforms’ increase, the paper presents and analyses the most popular robotic events. Robotics competitions encourage participants to develop and showcase their skills while promoting specific learning outcomes. The paper aims to provide an overview of those structures and discuss their efficacy. Finally, the paper explores the educational aspects of the presented ER competitions and their correlation with the six proposed learning outcomes. This raises the question of which primary features compose a competition and achieve its’ pedagogical goals. This paper is the first study that correlates potential learning gains with ER competitions to the best of our knowledge.
Students in primary and secondary schools in
Slovak republic are not very interested in study computer
science, especially programming. At our department, we are
trying to motivate primary and secondary school students to
learn programming through multiple activities, such as
computer science extracurricular activity and doing
workshops in primary and secondary schools. This
contribution deals with using Makeblock mBot robots for
teaching programming in primary and secondary schools.
Purpose of Review
With the growing interest for STEM/STEAM, new robotic platforms are being created with different characteristics, extras, and options. There are so many diverse solutions that it is difficult for a teacher/student to choose the ideal one. This paper intends to provide an analysis of the most common robotic platforms existent on the market. The same is happening regarding robotic events all around the world, with objectives so distinctive, and with complexity from easy to very difficult. This paper also describes some of those events which occur in many countries.
Recent Findings
As the literature is showing, there has been a visible effort from schools and educators to teach robotics from very young ages, not only because robotics is the future, but also as a tool to teach STEM/STEAM areas. But as time progresses, the options for the right platforms also evolve making difficult to choose amongst them. Some authors opt to first choose a robotic platform and carry on from there. Others choose first a development environment and then look for which robots can be programmed from it.
Summary
An actual review on learning robotics is here presented, firstly showing some literature background on history and trends of robotic platforms used in education in general, the different development environments for robotics, and finishing on competitions and events. A comprehensive characterization list of robotic platforms along with robotic competitions and events is also shown.
Educational robotics has gained increased importance and attention worldwide as an excellent teaching tool for STEM (Science, Technology, Engineering, Mathematics). However, catching the enthusiasm of young learners who are not already interested in STEM remains challenging. In this paper, we describe our outreach concept where young people from Vienna and surroundings visit the technical university with their teachers for a three-hour program. Our focus is on technological literacy, the understanding of what a robot is and how it works and may look like, as well as different robotic application areas. Theory and hands-on are combined in an age-appropriate concept based on constructivism. In order to evaluate our approach, we have developed a short post-questionnaire. Our results with 255 young people ages 7 to 17 show that after the visit 84% are more interested in technology and 80% are more interested in robotics. 85% of the young learners find that robots are complex machines after the visit. Despite that fact, 85% of those who find robots complex are more interested in robotics, 85% want to come back to learn more about robotics, and 91% will tell their families about these activities.
Teaching robotics to engineering students can be a challenging endeavor. In order to provide hands-on experiences, physical robot platforms are required. Previously, obtaining these platforms could be expensive, and required a lot of technical expertise from teaching staff. However, more recent models address these issues, therefore providing more opportunities for hands-on sessions. In this paper, we describe how we used the Turtlebot 3 mobile robot in master courses at KU Leuven. We provide an overview of the main functionalities, and suggest a number of improvements to further lower the learning curve for students. Additionally, we elaborate on the curriculum and learning outcomes of two courses that utilized Turtlebots in practically oriented sessions.
There has been a steady increase in the number of studies investigating educational robotics and its impact on academic and social skills of young learners. Educational robots are used both in and out of school environments to enhance K–12 students’ interest, engagement,and academic achievement in various fields of STEM education. Some prior studies show evidence for the general benefits of educational robotics as being effective in providing impactful learning experiences. However, there appears to be a need to determine the specific benefits which have been achieved through robotics implementation in K–12 formal and informal learning settings. In this study, we present a systematic review of the literature on K–12 educational robotics. Based on our review process with specific inclusion and exclusion criteria, and a repeatable method of systematic review, we found 147 studies published from the years 2000 to 2018. We classified these studies under five themes: (1) general effectiveness of educational robotics; (2) students’ learning and transfer skills; (3)creativity and motivation; (4) diversity and broadening participation; and (5) teachers’ professional development. The study outlines the research questions, presents the synthesis of literature, and discusses findings across themes. It also provides guidelines for educators, practitioners, and researchers in areas of educational robotics and STEM education, and presents dimensions of future research.
Jeannette Wing's 2013 call for education to make coding a key skill coincided with a boom in new education robots. Not surprisingly most of these new robots focus on developing student's computational thinking abilities and programming know-how. Is that all robots can offer? To find the answer I'll explore the history of education robots: specifically the ideas of Seymour Papert. What we'll find is something with far more potential than providing learners with a way of developing their coding skills. And against accepted wisdom, I'll suggest that as technology develops the need for coders will (in the long-term) dwindle but the power of robots to help educate children for the future will increase.
In Press (publication due August 2019)
Building on Seymour Papert's view of empowering students by mastering programming, this study conceptualized programming empowerment as consisting of four components: meaningfulness, impact, creative self-efficacy, and programming self-efficacy. A sample of 287 primary school students in grades four to six completed a corresponding survey. Confirmatory factor analysis validated the proposed components of the programming empowerment instrument. A structural equation model indicated that students with greater interest in programming perceived it as more meaningful, had greater impact, had greater creative self-efficacy, and had greater programming self-efficacy. Also, students with attitudes toward collaboration that were more positive than others had greater creative self-efficacy. Boys showed more interest in programming than girls did. Students in higher grade levels than others viewed programming as less meaningful and had lower programming self-efficacy. These results support future studies that evaluate the impacts of interest-driven computational thinking and programming curricula with ample collaboration opportunities.
Educational robotics are increasingly appearing in educational settings, being considered a useful supporting tool for the development of cognitive skills, including Computational Thinking (CT), for students of all ages. Meanwhile, there is an overwhelming argument that CT will be a fundamental skill needed for all individuals by the middle of the twenty-first century and thus, should be cultivated in the early school years, as part of the child’s analytical thinking and as a principal component of Science-Technology-Engineering-Mathematics (STEM) education. This study reviews published literature at the intersection of CT and educational robotics, particularly focused on the use of educational robotics for advancing students’ CT skills in K-12. The reviewed articles reveal initial evidence suggesting that educational robotics can foster students’ cognitive and social skills. The paper discusses specific areas for further inquiry by learning researchers and learning practitioners. Such inquiry should start from a widely agreed definition of CT and validated measurement instruments for its assessment. A practical framework for the development of CT via robotics is next in demand, so as instructional designers and educators can implement it consistently and at scale.
Robotics and control theory education at schools has been shown to provide some interesting results and forms a community of people who are keen on robotics since their secondary school. The paper presents an overview of a unique experience of Robotics Center for schoolchildren and its activities and describes the outcomes: courses for children and adults, organizing competitions, robotics camps and quests. Collaboration with universities is also shown to enhance its efficiency.
The Robobo Project is a STEM-based project that aims to bring educational robotics, in primary and high school, closer to real-world applications. It is based on the use of a smartphone-based robotic platform called Robobo, a very flexible programming environment, and a set of lessons to integrate them. The smartphone provides high-level hardware capabilities in terms of sensors, communications and processing capabilities that allow to create more practical and realistic lessons that exploit human-robot interaction, with a small investment. In this paper, we present the main elements of The Robobo Project in terms of hardware and software, and two illustrative educational projects that can be developed within it.
Interest in robotics field as a teaching tool to promote the STEM areas has grown in the past years. The search for solutions to promote robotics is a major challenge and the use of real robots always increases costs. An alternative is the use of a simulator. The construction of a simulator related with the Portuguese Autonomous Driving Competition using Gazebo as 3D simulator and ROS as a middleware connection to promote, attract, and enthusiasm university students to the mobile robotics challenges is presented. It is intended to take advantage of a competitive mindset to overcome some obstacles that appear to students when designing a real system. The proposed simulator focus on the autonomous driving competition task, such as semaphore recognition, localization, and motion control. An evaluation of the simulator is also performed, leading to an absolute error of 5.11% and a relative error of 2.76% on best case scenarios relating to the odometry tests, an accuracy of 99.37% regarding to the semaphore recognition tests, and an average error of 1.8 pixels for the FOV tests performed.
This paper presents a comprehensive literature review on tangible programming languages which are designed to program real robots and robotic mechanisms. Tangible programming interfaces appear to be more accessible to novice programmers and possibly reduce the age threshold for participation, making this way robot programming an educational toy even for preschool and elementary students. Moreover, this paper makes a short examination on the resent research findings on the field of tangible robot programming and argues that the combination of tangible programming and robot construction may offer unique opportunities for educational robotics.
Teaching robotics is challenging because it is a multidisciplinary, rapidly evolving and experimental discipline that integrates cutting-edge hardware and software. This paper describes the course design and first implementation of Duckietown, a vehicle autonomy class that experiments with teaching innovations
in addition to leveraging modern educational theory for improving student learning. We provide a robot to every student, thanks to a minimalist platform design, to maximize active learning and introduce a role-play aspect to increase team spirit, in which the entire class is modeled as a fictional start-up (Duckietown Engineering Co.). The course formulation leverages backward design by formalizing intended learning outcomes (ILOs) enabling students to appreciate the challenges of: (a) heterogeneous disciplines converging in the design of a minimal self-driving car, (b) integrating subsystems to create complex system behaviors, and (c) allocating constrained computational resources. Students learn how to assemble, program, test and operate a self-driving car Duckiebot) in a model urban environment (Duckietown), as well as how to implement and document new features in the system. Traditional course assessment tools are complemented by a full scale demonstrations to the general public. The “duckie” theme was chosen to give a gender-neutral, friendly identity to the robots so as to improve student involvement and outreach possibilities. All of the teaching materials and code is released online in the hope that other institutions will adopt the platform and continue to evolve and improve it, so to
keep pace with the fast evolution of the field.
Educational robots have become an often asked educational tool for a hands-on introduction to modern information and communication technology. The ”Roberta - Learning with Robots” initiative aims to engage and motivate girls and boys to take a sustained long-term interest in information technology and natural sciences since the project inception in 2002. With more than 35.000 children and young people in over 600 documented Roberta courses a year – Roberta has become a permanent fixture in the German education landscape and the pedagogical concept, created books, course material and additional tools are being used successfully in other European countries. However, programming educational robots and maintaining complex computer hardware is still a hassle for teachers in the classrooms - as frequently reported from student participants and Roberta network teachers. A main goal of the presented successor initiative Open Roberta is to overcome technical challenges by providing an open, fully web based programming environment for teachers and students alike that can be used directly in the web browser at home or in the classroom. The presented software - the Open Roberta Lab consists of visual programming tools for the development and connection of real educational robots without long-winded system installations, preparation tasks or technology getting in the way. A further technical aspect of the paper is the introduction of the NEPO® meta programming language as an essential part of the Open Roberta Lab.
Taking distributed robotic system research from simulation to the real world often requires the use of small robots that can be deployed and managed in large numbers. This has led to the development of a multitude of these devices, deployed in the thousands by researchers worldwide. This paper looks at the Khepera IV mobile robot, the latest iteration of the Khepera series. This full-featured differential wheeled robot provides a broad set of sensors in a small, extensible body, making it easy to test new algorithms in compact indoor arenas. We describe the robot and conduct an independent performance evaluation, providing results for all sensors. We also introduce the Khepera IV Toolbox, an open source framework meant to ease application development. In doing so, we hope to help potential users assess the suitability of the Khepera IV for their envisioned applications and reduce the overhead in getting started using the robot.
The wider availability of 3D printing has enabled small printable robots (or printbots) to be incorporated directly into engineering courses. Printbots can be used in many ways to enhance lifelong learning skills, strengthen understanding and foster teamwork and collaboration. The experiences outlined in this paper were used in our teaching during the last academic year, although much of the methodology and many of the activities have been used and developed over the past 8 years. They include project based assignments carried out by multidisciplinary and multicultural teams, a number of theoretical and practical classroom and laboratory activities all aimed at familiarizing students with fundamental concepts, programming and simulation, and which now form part of our regular robotics courses, and some brief descriptions of how printable robots are being used by students carrying out final projects for Bachelor and Master degrees. The online resources show many of these activities in action.
Thymio II is a small robot developed for education. It aims at offering a wide public the possibility to understand the basics of robotics and programming. To achieve this, it aims at being appealing to a large age range and serve as a medium for several types of activities. In this study, we tested it in five different workshops of the EPFL Robotics Festival with various activities. The workshops target different age groups and the participants can control the robot via different means: built-in buttons, graphical programming and text programming. At the end of the activities, participants were asked to fill a short survey to give their impressions about the robot, their appreciation of the tasks and their motivations to take part. We could show through this feedback that Thymio II appeals to young children as much as to teenagers, to both girls and boys, and allows them to have fun and learn new things.
Humanoids; a most intriguing subject to behold by both the engineers and the world at large. With the introduction of humanoid robot NAO by Aldebaran-Robotics in 2008, a performant biped robot is now available and affordable for research laboratories and the mass market. In this paper, an exploration of current trends in control methods of biped walks, behavior interface tools for motion control for NAO and imminent findings in both research areas are discussed. Future directions are for researchers to devise a unique controller with low power consumption without compromising the robot's speed and robustness.
Scratch is a visual programming environment that allows users (primarily ages 8 to 16) to learn computer programming while working on personally meaningful projects such as animated stories and games. A key design goal of Scratch is to support self-directed learning through tinkering and collaboration with peers. This article explores how the Scratch programming language and environment support this goal.
As of 2021, more than 30 countries have released national artificial intelligence (AI) policy strategies. These documents articulate plans and expectations regarding how AI will impact policy sectors, including education, and typically discuss the social and ethical implications of AI. This article engages in thematic analysis of 24 such national AI policy strategies, reviewing the role of education in global AI policy discourse. It finds that the use of AI in education (AIED) is largely absent from policy conversations, while the instrumental value of education in supporting an AI-ready workforce and training more AI experts is overwhelmingly prioritized. Further, the ethical implications of AIED receive scant attention despite the prominence of AI ethics discussion generally in these documents. This suggests that AIED and its broader policy and ethical implications—good or bad—have failed to reach mainstream awareness and the agendas of key decision-makers, a concern given that effective policy and careful consideration of ethics are inextricably linked, as this article argues. In light of these findings, the article applies a framework of five AI ethics principles to consider ways in which policymakers can better incorporate AIED’s implications. Finally, the article offers recommendations for AIED scholars on strategies for engagement with the policymaking process, and for performing ethics and policy-oriented AIED research to that end, in order to shape policy deliberations on behalf of the public good. Available openly at: https://rdcu.be/cw5aY
This paper is a brief review of the literature on the use of educational robotics in primary school. The purpose is to explore the application of robotics and, more specifically, the advantages robotics offers to students, the challenges that arise from its application, and what is its place in the curricula. Educational robotics is an innovative and useful tool. It positively affects critical thinking, computational thinking, problem-solving, algorithmic thinking, creativity, and collaboration. The literature reveals that difficulties arise either at the technical level or due to teachers’ lack of relevant knowledge or the lack of relevant provisions for their effective integration into primary school curricula.
This paper examines the political economy of artificial intelligence (AI) and education in China, through an analysis of government policy and private sector enterprise. While media and policy discourse often portray China’s AI development in terms of a unified national strategy, and a burgeoning geopolitical contestation for future global dominance, this analysis will suggest a more nuanced internal complexity, involving differing regional networks and international corporate activity. The first section considers two key policy documents published by the central Chinese government, which are shown to implicate educational institutions as influential actors in national and regional strategies for AI development, with a significant role in plans to train domestic expertise. The second section outlines three prominent private education companies: New Oriental Group, Tomorrow Advancing Life (TAL), and Squirrel AI. These companies are selected to represent important aspects of China’s development of educational AI applications, including the influence of a well-established private education sector, and a growing interest in international corporate activity. The paper concludes with the suggestion that while central government policy reserves a significant role for education in the national AI strategy, the private sector is utilising favourable political conditions to rapidly develop educational applications and markets.
Following the recommendations of the European Commission, with the aim of positioning the EU as a leader in the technological revolution that is yet to come, Artificial Intelligence (AI) teaching at University degrees should be updated. Current AI subjects should move from theoretical and virtual applications towards what is called “specific AI”, focused on real embedded devices, using data from real sensors and interacting with their environment to solve problems in the real world. These real devices must have the computing power to process all the information that comes from their sensors and also full network connectivity, to allow the connection with other intelligent devices. This work belongs to an Erasmus Plus proposal in such direction, called TAIREMA, which aims to provide a set of tools to include low-cost embedded devices at classes to support AI teaching. One of these tools is a smartphone-based robot called Robobo, which is the main topic of this paper. We will present its main features, mainly in software aspects, and we will describe some specific teaching units that have been developed in classes during the last year in AI subjects.
Teaching robotics in secondary school is common nowadays, although with heterogeneous approaches in different countries, mainly in the specific technology that is used. Even with such lack of standardization, there are many common elements in these early stages of educational robotics, focused on basic assembling, simple sensing, and locomotion, which are a consequence of the simplicity of the robots that are used. In this paper, we aim to go one step ahead, and propose an approach of how the next stage in educational robotics should be. To this end, we analyze the current situation of this subject in reference to the robotics market and society, and then we propose a structure for the curriculum development. This approach is based on the use of the Robobo robot, as a clear example of the type of device that allows to perform such update of the subject, and on the use of a STEAM methodology, where a global view of how to face a robotics problem is presented.
Educational institutions planning to invest in Educational Robotics are faced with a wide selection of products. Yet, we have not been able to find any review studies on the effect of these products, to guide the institutions to get the most out of their investments. For this review, 29 Educational Robotics products were therefore selected, and eight major databases were searched for effect studies involving these. The search yielded 301 results, of which 17 were selected for synthesizing. The studies and their respective findings are discussed in the review. Unfortunately, there were not enough studies to compare the effect of the products and more research is therefore needed. In addition, the studies methodologies and design have been analyzed, and a series of recommendations for how future experimental/quasi-experimental studies within the field can be design and conducted, have been established.
Robots are technological tools of great interest in primary education for many reasons, but mainly for their compatibility with science, technology, engineering, and mathematics (STEM). However, it is very important to minimize the impact of the technical issues associated to robotics on the teachers, providing simple and functional tools that allow them to focus their attention in the creation of STEM content. To this end, this chapter presents a methodology, based on realistic mathematics, for the integration of educational robotics in primary schools. This methodology has been tested during one semester in the Sigüeiro Primary School (Spain) in the subject of mathematics, with students of different ages ranging from 7 to 11 years old. Two different educational robots, with different features, were used to highlight that the methodology is independent of the robotic platform used. Motivation surveys were administered to the students after the classes. Surveys reported highly successful results, which are discussed in the chapter.
This paper reports on a research study that examined how Australian primary school teachers integrated robotics and coding in their classrooms and the perceived impact this had on students’ computational thinking skills. The study involved four primary school teachers, (Years 1–6) from four schools, introducing LEGO® WeDo® 2.0 robotics kits in their classrooms. The data collected from questionnaires, journal entries, and semi-structured interviews were analyzed using computational thinking and teaching frameworks. The results demonstrate that exploring with and using the robot kits, and activities, helped the teachers build their confidence and knowledge to introduce young students to computational thinking. The study identified that teacher professional development (PD) needs to focus explicitly on how to teach developmentally appropriate robotics-based STEM activities that further promote computational concepts, practices, and perspectives.
Educational Robotics has been presented as a great pedagogical tool because it demonstrates an attractive way of working the theoretical knowledge put into practice. Thus, several educational technologies have emerged with different approaches, with the purpose of applying robotics in the educational area in a more attractive and playful way. This article presents the conduction of a Systematic Review of Literature (SRL), whose objective is to identify the teaching approaches used with educational robotics. With this, we present experiences reports, and at the same time show the skills and competencies that are explored through robotics and education. This review uses scientific papers published in the period from 2011 to 2016.
Autonomous driving is not one single technology but rather a complex system integrating many technologies, which means that teaching autonomous driving is a challenging task. Indeed, most existing autonomous driving classes focus on one of the technologies involved. This not only fails to provide a comprehensive coverage, but also sets a high entry barrier for students with different technology backgrounds. In this paper, we present a modular, integrated approach to teaching autonomous driving. Specifically, we organize the technologies used in autonomous driving into modules. This is described in the textbook we have developed as well as a series of multimedia online lectures designed to provide technical overview for each module. Then, once the students have understood these modules, the experimental platforms for integration we have developed allow the students to fully understand how the modules interact with each other. To verify this teaching approach, we present three case studies: an introductory class on autonomous driving for students with only a basic technology background; a new session in an existing embedded systems class to demonstrate how embedded system technologies can be applied to autonomous driving; and an industry professional training session to quickly bring up experienced engineers to work in autonomous driving. The results show that students can maintain a high interest level and make great progress by starting with familiar concepts before moving onto other modules.
This book describes recent approaches in advancing STEM education with the use of robotics, innovative methods in integrating robotics in school subjects, engaging and stimulating students with robotics in classroom-based and out-of-school activities, and new ways of using robotics as an educational tool to provide diverse learning experiences. It addresses issues and challenges in generating enthusiasm among students and revamping curricula to provide application focused and hands-on approaches in learning . The book also provides effective strategies and emerging trends in using robotics, designing learning activities and how robotics impacts the students’ interests and achievements in STEM related subjects.
The frontiers of education are progressing very rapidly. This volume brought together a collection of projects and ideas which help us keep track of where the frontiers are moving. This book ticks lots of contemporary boxes: STEM, robotics, coding, and computational thinking among them. Most educators interested in the STEM phenomena will find many ideas in this book which challenge, provide evidence and suggest solutions related to both pedagogy and content. Regular reference to 21st Century skills, achieved through active collaborative learning in authentic contexts, ensures the enduring usefulness of this volume.
John Williams
Professor of Education and Director of the STEM Education Research Group
Curtin University, Perth, Australia
Learning with educational robotics provides students, who usually are the consumers of technology, with opportunities to stop, question, and think deeply about technology. When designing, constructing, programming, and documenting the development of autonomous robots or robotics projects, students not only learn how technology works, but they also apply the skills and content knowledge learned in school in a meaningful and exciting way. Educational robotics is rich with opportunities to integrate not only STEM but also many other disciplines, including literacy, social studies, dance, music, and art, while giving students the opportunity to find ways to work together to foster collaboration skills, express themselves using the technological tool, problem-solve, and think critically and innovatively. Educational robotics is a learning tool that enhances students’ learning experience through hands-on mind-on learning. Most importantly, educational robotics provides a fun and exciting learning environment because of its hands-on nature and the integration of technology. The engaging learning environment motivates students to learn whatever skills and knowledge needed for them to accomplish their goals in order to complete the projects of their interest. For school-age children, most robotics activities have mainly been part of informal education, such as after school programs and summer camps (Benitti in Computers & Education, 58:978–988, 2012; Eguchi 2007b; Sklar and Eguchi in Proceedings of RoboCup-2004: Robot Soccer World Cup VIII, 2004), even though it has the potential to make learning more effective in formal education. It is very difficult for teachers to include robotics in regular curriculum because of the heavy focus on standardized testing and pressure to cover academic standards set by the government and/or their States. This chapter aims to promote robotics in classroom by connecting robotics learning with various STEM curriculum standards.
The chapter on ‘STEM Education by Exploring Robotics (SEEbots)’ describes a wide range of educational robotics modules for increasing STEM learning at pre-college level and at the college level. The recent advances in electronics technology and computer technology are making a variety of novel and versatile robotics modules within the budget of educational institutions for creating interest among the students toward STEM learning, and to broaden participation of students seeking STEM careers. The suggested robotics modules are based on the experiences gained in teaching robotics for STEM education to middle school level to college level, through projects sponsored by funding agencies. The information described is intended for educators as a reference guide to designing their robotics courses for STEM learning in secondary or post-secondary introductory robotics educational program.
This article presents the results of an online survey of faculty opinions on the state of robotics education with a focus on three topics: degree programs, introductory robotics courses, and educational resources. There were 67 institutions represented, the majority of which are doctoral granting universities located in the United States. I confirmed the existence of seven bachelor programs awarding approximately 140 degrees annually in addition to 26 graduate programs conferring 268 master's and 83 doctoral degrees annually.
Robotics is becoming a mainstream phenomenon, entering all areas of our lives. In addition to cutting-edge research and development, robotics is becoming equally important in the classroom and home education. Numerous educational kits have appeared on the market recently, ranging from simple toolboxes and toys to complex, configurable R&D sets. Their value in formal teaching lies in modularity and the applicability of the associated curriculum. Some kits have already attracted major crowds of users, forming strong communities. The aim of this article is to review the currently available educational robotics kits along with their possible usability in formal education, focusing the analysis on system capabilities, modularity, and teaching materials available. The summary of these teaching aids should ease the decisions of robotics experts and instructors when choosing their tools for teaching and demonstration.
RoboCupJunior is an international educational robotics initiative, aiming to promote STEM content and skill learning among participating youth through educational robotics competition inaugurated in 2000. What makes RoboCupJunior quite unique is its relationship with RoboCup which aims to promote robotics and AI research, by offering a publicly appealing, but formidable challenge including development of soccer robots, search and rescue robots, and robots functions at home and at work. This paper introduces a case of RoboCupJunior and the effectiveness of its practice for enhancing learning of STEM contents and skills for innovation and creativity among participating students. It presents the survey results from one of the World Championships held in 2012, the anecdotal and personal account of participating US students on their learning experience from their participation in 2013 World Championship, and participating students' technological and innovative contributions to highlight the impacts RoboCupJunior has had through over a decade of its practice.
Robotic systems have a high potential for creative learning if they are flexible, accessible and engaging for the user in the experimental process of building and programming robots. In this paper we describe the Fable modular robotic system for creative learning which we develop to enable and motivate anyone to build and program their own robots. The Fable system consists of self-contained modules equipped with sensors and actuators, which users can use to easily assemble a wide range of robots in a matter of seconds. The robots are user-programmable on several levels of abstraction ranging from a simple visual programming language to powerful conventional ones. This paper provides an overview of the design of Fable for different user groups and an evaluation of critical issues when we attempt to integrate the system into an everyday teaching context.
Twenty-first century education systems should create an environment wherein students encounter critical learning components (such as problem-solving, teamwork, and communication skills) and embrace lifelong learning. A review of literature demonstrates that new technologies, in general, and robotics, in particular, are well suited for this aim. This study aims to contribute to the literature by studying teachers' perceptions of the effects of using robotics on students' lifelong learning skills. This study also seeks to better understand teachers' perceptions of the barriers of using robotics and the support they need. Eleven primary/elementary teachers from Newfoundland and Labrador English Schools District participated in this study. The results of this study revealed that robotics is perceived by teachers to have positive effects on students' lifelong learning skills. Furthermore, the participants indicated a number of barriers to integrate robotics into their teaching activities and expressed the support they need.
Abstract— This paper gives an overview of ROS, an open- source robot operating,system. ROS is not an operating,system in the traditional sense of process management,and scheduling; rather, it provides a structured communications layer above the host operating,systems,of a heterogenous,compute,cluster. In this paper, we discuss how ROS relates to existing robot software frameworks, and briefly overview some of the available application software,which,uses ROS.