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Educational robots as collaborative learning objects for teaching Computer Science
Abstract
We present the constructionism-based approach towards using collaborating educational robots for teaching the abstract concepts of Computer Science (CS) such as task decomposition. We present the collaborative robot-based e-learning environment, which enables us to implement the principles of constructionism and collaborative learning for teaching students how to solve CS problems using LEGO multi-robots as tangible Collaborative Learning Objects (CLOs). We extended the existing approaches by a) providing a framework of robotic CLO based learning environment; and b) demonstrating the use of task decomposition and allocation principles for teaching CS algorithms and programming.
... Few learning environments proposed delve into the collaboration of learning agents or learners. The authors of (Burbaite et al, 2013) deal with collaborative robots, where "autonomous agents-robots pursue joint goals". Robots react with learners and accumulate information about the learners' affective behaviour towards a LO, while they exchange and combine this information to gain a clearer insight over the learner's styles. ...
... While some approaches are heavily oriented on the learner-centric nature of the LOs for linear education (both in terms of instructional tools and of the educational scheme), others focus on the educational tools (multiple agents) and their interaction with the learners. Consequently, re-usability is a major common attribute of all examined approaches ( (Kurilovas et al, 2014a), (Falconer et al, 2006), (Rodríguez et al, 2013), (Limongelli et al, 2012), (Burbaite et al, 2013), (Garrido and Onaindia, 2013), (Tsai et al, 2006)), with personalisation of some sort (usually according to pre-defined manual information from the teachers) being the second most prominent attribute ( (Kurilovas et al, 2014a), (Falconer et al, 2006), (Burbaite et al, 2013), (Garrido and Onaindia, 2013), (Tsai et al, 2006)). Interoperability of LOs is also a major attribute ( (Kurilovas et al, 2014a), (Falconer et al, 2006), (Rodríguez et al, 2013), (Limongelli et al, 2012)), while the rest of the target criteria are selectively present. ...
... While some approaches are heavily oriented on the learner-centric nature of the LOs for linear education (both in terms of instructional tools and of the educational scheme), others focus on the educational tools (multiple agents) and their interaction with the learners. Consequently, re-usability is a major common attribute of all examined approaches ( (Kurilovas et al, 2014a), (Falconer et al, 2006), (Rodríguez et al, 2013), (Limongelli et al, 2012), (Burbaite et al, 2013), (Garrido and Onaindia, 2013), (Tsai et al, 2006)), with personalisation of some sort (usually according to pre-defined manual information from the teachers) being the second most prominent attribute ( (Kurilovas et al, 2014a), (Falconer et al, 2006), (Burbaite et al, 2013), (Garrido and Onaindia, 2013), (Tsai et al, 2006)). Interoperability of LOs is also a major attribute ( (Kurilovas et al, 2014a), (Falconer et al, 2006), (Rodríguez et al, 2013), (Limongelli et al, 2012)), while the rest of the target criteria are selectively present. ...
The traditional educational paradigm has been nowadays transformed to tech-aided personalised learning, tailored to individual learning styles and needs, applicable in any environment. Such an educational framework should provide capabilities for adaptive, affective and interactive learning, taking advantage of technological means to recognize the learners’ performance, behaviour and progress over the learning process. A novel methodology is proposed to model an educational framework able to represent and optimally foster these needs, along with a methodology for non-linearly adapting networked learning objectives. In addition, the framework is supported with an ontology that enables personalised and contextualised decision-making over learning activities on autonomous devices, enabling their dynamic modularisation during the learning process.
... Therefore, their proposal is focused on specific resources that are needed to create collaborative objects, rather than explicitly defining how the object could promote such a type of collaborative behaviour. Burbaite et al. (2013) discuss a more pragmatic approach, where educational robots represent collaborative learning objects. Their framework promote features such as engagement and exploration by means of collaborative tasks that support and ensure group learning activities and groups work on the critical analysis of provided concepts and information. ...
... Independently of the approach, the studies that present experimental results show that learners have higher engagement when using collaborative objects. This fact is demonstrated, for example, in the work of Burbaite et al. (2013), where collaborative learning objects increased the students' engagement in learning as compared to other traditional approaches. ...
While virtual learning environments (VLEs) present several advantages, such as space-time flexibility, they are still not including proper opportunities and resources for students to engage in collaborative activities with their peers. Recent approaches, for example, are based on resources that are not standard for VLEs or usual for students. Thus, their integration with VLEs is not simple. This paper conducted a theoretical investigation to identify strategies that could induce collaborative behaviours in students. These strategies were implemented as learning objects running in a VLE and a quasi-experimental research design was conducted with 133 students. The results show that the approach promotes collaborative interactions between students and also tend to improve their learning outcomes. Moreover, learning objects use a conceptualization that is already established over the e-learning community, simplifying their integration with VLEs.
... During technology advancement, original technology-based firms in education and training are growing. Education is now moving from the usual classroom-centered learning to web-based sources (e-learning) and portable tools (m-learning) [8], immersive education in a context-awareness studying environment, context-awareness circumstances ready to give personalized content anywhere (i-learning) [9] plus a context-awareness method that extends virtual educative knowledge into the physical environment based on what the students want [10]. ...
... On the other hand, Robots provide the skills from microelectronics technology as well as give learners the chance for project-based education. Educational robotics provide the following benefits: ease of elearning activity increases attention in math, builds architecture plus science career, improves learner success scores [11], supports problem-solving, and supports collective learning [8]. In [12], presented a methodology to produce Robot-oriented Generative Education Objects (GLOs) to explain computer science (CS) subjects like programming. ...
Educational Robotics' (ER) use of Artificial Intelligence (AI) ranges from (Science, Technology, Engineering and Mathematics) STEM area, logical mathematical, debugging, LEGO robots, and a lot more. There is an urgent need for (ER) research on policy and use. However, this paper presents a framework for the representation of knowledge about using Educational Robotics and Context-Awareness technology in the learning environment. This framework enables smart class performance in higher education. The purpose of this study presents a new strategy in many aspects. Expanding and optimizing the students' answers and develop the users' participation in communication. The framework introduces a context controller system on the mobile terminal to connect and prepare the data from the robotics indicators. Additionally, it mixes different AI identification services in the cloud to obtain the context information through investigating and understanding the data. We also present a vision of use robotics and context-aware technology in the learning environment to improve and optimize the most benefits from the context information.
... This STREAM project in robotics exemplifies the benefits of integrating research into STEAM education. Through the process of conducting research, designing and implementing a solution, and communicating their findings, the students developed a range of skills including problem-solving, critical thinking, creativity, communication, and collaboration [1,15]. They gained a deeper understanding of the STREAM disciplines and saw firsthand how these fields can be integrated to solve real-world problems. ...
... • Science, TEchnnology and Mathematics (STEM) education: DTT can be used to create immersive and interactive STEM learning environments that replicate real-world scenarios. For example, students can use DTT to explore and interact with virtual environments that simulate different engineering or physics concepts [16], or control robots [11], which can help to improve their understanding and retention of the material. ...
... Some previous work run by the authors (Ponticorvo et al., 2020a) have indicated that ER can be effectively used to promote knowledge related to STEM and to enhance different skills such as computational thinking, problem-solving, complex systems management and collaborative learning, and positive and collaborative relations between students (Rubinacci et al., 2017a;Rubinacci et al., 2017b;Truglio et al., 2018a;Truglio et al., 2018b). ER allows to establish a relation of interdependence among students, who must achieve a common goal (Burbaite et al., 2013;Kamga et al., 2016), coordinate their efforts, learn to divide their tasks, and learn to complete the task, considering other group members. This represents a chance also for students with a low level of inclusion to participate in a group activity, thus improving their relationships with other students. ...
In the present paper, the experience of the C0D1NC project (Coding for inclusion) is described. In this project an innovative methodology based on peer-education is the core of the educational approach. High school students become “teachers” as they are trained to teach coding and robotics to younger students. This approach favors inclusion and digital inclusion. To affirm this, we evaluated different aspects: relations between peers, perceived self-efficacy, and attitude towards technology at the beginning of activities (pre-test) and the end (post-test). Results indicate that this approach can be effective to favor personal growth, improved relations between peers, and increased self-efficacy too.
... On the other hand, teachers can use the data obtained from the IoT devices as parameters for problem-solving questions that assess students' critical thinking skills and other activities for them. As a teaching aid, the IoT can be implemented in teaching and learning using robots [5], [6], [7], data loggers [8], and wearable devices [9], [10]. ...
The role of education in promoting global warming awareness is important to enable students to understand and address the impact of global warming. The use of Internet of Things (IoT) with collaborative learning strategies can enhance students’ understanding of global warming. This study aimed to develop an IoT-based smart weather system enhancing the critical thinking skills of elementary students. It consists of weather-measuring sensors that capture data on temperature, humidity, air pressure, light intensity, and altitude. The data is stored in the Blynk cloud and displayed on smartphones. The IoT devices are placed in three different geographic locations. This paper presents the system design, including the system architecture and user interfaces. The data captured by the IoT sensors from the three measurement sites form the foundation to promote the development of collaborative learning. This result implies the need for teachers to creatively establish learning strategies in various subjects to improve students’ critical thinking skills.
... S. Evripidou et al. have investigated and analyzed existing platforms of educational robotics and their learning outcomes [12]. R. Burbaite et al. proposed a framework that allows teachers to educate students on computer science algorithms and programming using multiple robots [13]. I. Plauska et al. proposed the use of educational robots to encourage learning about IoT in college classes [14]. ...
In many robotics studies, deep neural networks (DNNs) are being actively studied due to their good performance. However, existing robotic techniques and DNNs have not been systematically integrated, and packages for beginners are yet to be developed. In this study, we proposed a basic educational kit for robotic system development with DNNs. Our goal was to educate beginners in both robotics and machine learning, especially the use of DNNs. Initially, we required the kit to (1) be easy to understand, (2) employ experience-based learning, and (3) be applicable in many areas. To clarify the learning objectives and important parts of the basic educational kit, we analyzed the research and development (R&D) of DNNs and divided the process into three steps of data collection (DC), machine learning (ML), and task execution (TE). These steps were configured under a hierarchical system flow with the ability to be executed individually at the development stage. To evaluate the practicality of the proposed system flow, we implemented it for a physical robotic grasping system using robotics middleware. We also demonstrated that the proposed system can be effectively applied to other hardware, sensor inputs, and robot tasks.
... Human-robot interfaces have many applications, including prosthetics and artificial wrists [1,2], manufacturing and industrial assembly lines [3], surgery in medical robotics [4], hand rehabilitation [5], assisted living and care [6], soft wearable robotics [7], territory patrolling [8], drone-based delivery and logistics [9], military robotics applications [10], smart agriculture [11,12], and student teaching [13,14]. However, achieving efficient object grasping and dexterous manipulation capabilities in robots remains an open challenge [15]. ...
We developed an anthropomorphic multi-finger artificial hand for a fine-scale object grasping task, sensing the grasped object’s shape. The robotic hand was created using the 3D printer and has the servo bed for stand-alone finger movement. The data containing the robotic fingers’ angular position are acquired using the Leap Motion device, and a hybrid Support Vector Machine (SVM) classifier is used for object shape identification. We trained the designed robotic hand on a few monotonous convex-shaped items similar to everyday objects (ball, cylinder, and rectangular box) using supervised learning techniques. We achieve the mean accuracy of object shape recognition of 94.4%.
... Robots are also used in undergraduate education to accompany instruction related to programming skills and issues related to humanmachine interface [19]. Moreover, various robotics competitions, such as First Robotics, Robocup Junior, and Eurobot Junior are engaging K-12 and undergraduate students in the designing, building, and programming of autonomous robots [34][35][36]. ...
... The hand is connected by wires linked up to the motor cortex, which is the part of the human brain that controls the movement of muscles, and the sensory cortex, which recognizes the tactile sensations when a person touches some things. The research has opened a way for a multitude of applications, including prosthetics [2], industrial assembly lines [3], medical surgery [4], assisted living [5], manufacturing, military applications [6], education [7,8]. ...
We describe the design of the multi-finger anthropomorphic robotic hand for small-scale industrial applications, called AISRA (Anthropomorphic Interface for Stimulus Robust Applications), which can feel and sense the object that it is holding. The robotic hand was printed using the 3D printer and includes the servo bed for finger movement. The data for object recognition was collected using Leap Motion controller, and Naïve Bayes classifier was used for training and classification. We have trained the robotic hand on several monotonous objects used in daily life using supervised machine learning techniques and the gesture data obtained from the Leap Motion controller. The mean accuracy of object recognition achieved is 92.1%. The Naïve Bayes algorithm is suitable for using with the robotic hand to predict the shape objects in its hands based on the angular position of its figures. Leap Motion controller provides accurate results and helps to create a dataset of object examples in various forms for the AISRA robotic hand, and can be used to help developing and training 3D-printed anthropomorphic robotic hands. The experiments in object grasping experiments demonstrated that the AISRA robotic hand can grasp objects with different size and shape, and verified the feasibility of robot hand design using low-cost 3D printing technology. The implementation can be used for small-scale industrial applications.
... Nowadays, Science, Technology, Engineering, and Mathematics (STEM) education [16], [17] is gradually increasing its importance in other fields of study, such as biology [18]. Multidisciplinary teaching strategies [19][20][21] are necessary due to demanded professional profiles in a hyper-connected and technological society that continuously requests high-tech products and services. In this regard, students often lack in-depth mathematical knowledge and often tend to overlook mathematical tools [22] that could be useful for their future research career and scientific success. ...
The recent success of biological engineering is due to a tremendous amount of research effort and the increasing number of market opportunities. Indeed, this has been partially possible due to the contribution of advanced mathematical tools and the application of engineering principles in genetic-circuit development. In this work, we use a rationally designed genetic circuit to show how models can support research and motivate students to apply mathematics in their future careers. A genetic four-state machine is analyzed using three frameworks: deterministic and stochastic modeling through differential and master equations, and a spatial approach via a cellular automaton. Each theoretical framework sheds light on the problem in a complementary way. It helps in understanding basic concepts of modeling and engineering, such as noise, robustness, and reaction–diffusion systems. The designed automaton could be part of a more complex system of modules conforming future bio-computers and it is a paradigmatic example of how models can assist teachers in multidisciplinary education.
... This happens because ER allows one to establish a bridge between students, who become interdependent as they are required to reach a shared goal (Burbaite et al., 2013;Kamga et al., 2016), to coordinate themselves, to learn to divide tasks in subtasks, and to complete them, taking into account other group members (in terms of opinions, ideas, skills, and abilities). As a consequence, also those students who are not well-included in the class have the opportunity to be involved in group activity and to improve relationships with other students. ...
Robotics has gained, in recent years, a significant role in educational processes that take place in formal, non-formal, and informal contexts, mainly in the subjects related to STEM (science, technology, engineering, and mathematics). Indeed, educational robotics (ER) can be fruitfully applied also to soft skills, as it allows promoting social links between students, if it is proposed as a group activity. Working in a group to solve a problem or to accomplish a task in the robotics field allows fostering new relations and overcoming the constraints of the established links associated to the school context. Together with this aspect, ER offers an environment where it is possible to assess group dynamics by means of sociometric tools. In this paper, we will describe an example of how ER can be used to foster and assess social relations in students' group. In particular, we report a study that compares: (1) a laboratory with robots, (2) a laboratory with Scratch for coding, and (3) a control group. This study involved Italian students attending middle school. As the focus of this experiment was to study relations in students' group, we used the sociometric tools proposed by Moreno. Results show that involving students in a robotics lab can effectively foster relations between students and, jointly with sociometric tools, can be employed to portrait group dynamics in a synthetic and manageable way.
... (5) The students present their implemented robot to other students and the teacher at the semester workshop. Presentation framed as a learning object (LO) [41][42][43] is encouraged; that is, the students formulate their educational aims, describe the implementation of the projects using multimedia materials (videos, photographs, diagrams), and present conclusions what they have learned. The Moodle learning platform is used as a common media to discuss projects and share learning experience. ...
Science, technology, engineering, and mathematics (STEM) fields are core technological underpinnings of an advanced society and they are also related to the economic competitiveness of nations. Many countries are suffering from low achievement and low interest among learners in STEM subjects compared to others. In this paper, we argue that the robots can be used not only for teaching schoolchildren and university students to learn the STEM subjects, but also in social and humanistic sciences to increase engagement in technology and facilitate acquisition of transdisciplinary knowledge. As a case study, we present an approach to educational robotics adopted in Kaunas University of Technology, Lithuania. The approach allows to foster student creativity and improve their teamwork abilities, as well as knowledge in robotics and robot programming.
... Third, the robot's functionality can be extremely enlarged in creating smart environments, if we make essential architectural changes moving from the use of a single robot to the cooperating robots [BSD13]. For more complicated tasks, where the physical processes are concerned with simultaneous activities, the need of using ensembles of robots may arise. ...
The aim of this chapter is twofold. The first aim is to describe the context to ease the understanding of the subsequent topics. Here, by the context, I mean the analysis of research trends in the e-learning and domains (the latter is treated as a very significant branch of e-learning) so that the reader could be able first to understand the essence of the domain and then be aware of the intention of our approach which focuses on two novel concepts, smart learning object and smart educational environment, to teach computer science. The second aim is to present the primary knowledge on those smart items to be considered in detail later throughout the book.
... The paper builds upon our previous experience and methodological work in developing educational robotics and teaching materials for project based teaching of computer science students [5][6][7][8][9][10]. The paper is structured as follows: Section 3 provides an overview of the state-of-the-art in the development of pedagogical frameworks. ...
Globalization and sustainable development requires shifting education targets from acquisition of structures knowledge to the mastery of skills. Robot-aided learning can used as a tool of creativity in AHSS (Arts, Humanities and Social Sciences) classes thus attracting the attention of learners to cross-disciplinary subjects with elements of STEM (Science, Technology, Engineering, and Mathematics), which is expanded to STEAM (STEM + All). The presented FASTER pedagogical framework is based on the combination of project-based teaching, educational robotics and team based learning for achieving educational aims and supporting creativity in class. We describe the practical use of the framework in a university course, with specific examples of student projects. Finally, we discuss the educational implications of the framework and beyond.
... Few learning environments proposed delve into the collaboration of learning agents or learners. The authors of [12] deal with collaborative robots, where "autonomous agents-robots pursue joint goals". Robots react with learners and accumulate information about the learners' affective behaviour towards a LO, while they exchange and combine this information to gain a clearer insight over the learner's styles. ...
In next generation technology-enhanced learningenvironments, intelligent educational systems can benefit fromtapping into multi-agent, adaptive, gamified learning experiences,which transform the traditional instructional paradigm fromclassroom-based learning to personalised learning in any setting,whether collective or individual. Such settings enable learningtargeted to each individual’s learning styles and needs, throughthe use of autonomous technological agents as actuators of thelearning process. Learning components which will respond to theneeds of such an educational framework should provide capa-bilities for adaptive, affective and interactive learning, automaticfeedback and automatic assessment of the learners’ behaviouralstate. A novel methodology is proposed to model such compo-nents, which focuses on the representation and management oflearning objects (LOs) for any educational domain, any typeof learner and learning style and any learning methodology,while fostering non-linearity in the educational process. Thismethodology is supported by a strategy for modelling andadapting re-usable learning objectives, coupled with an ontologythat enables scalable and personalized decision-making overlearning activities on autonomous devices, enabling dynamicmodularisation of learning material during the learning process.
... Conceptually, the role of robots in the educational CSCL environment is Robot as Learning Object (RaLO), which extends the notion of an LO beyond the virtual domain (learning content) to a physical domain (robot hardware and actions in real-world environment) [11,12,13]. ...
Educational robots can serve as smart, mobile and tangible learning objects which can explicitly represent knowledge through actions and engage students through immersion and instant feedback. As pedagogical background, we employ the elements of Norman's foundational theory of action and the Internet-of-Things Supported Collaborative Learning (IoTSCL) paradigm, which is based on constructivism. We describe the application of educational robots in project-based teaching at the university course. Positive relationship between successful implementation of robotics project and assimilation of theoretical knowledge has been established.
... Studies that are concerned with collaborative learning aim to measure social interactions among the learners and group dynamics. Such studies are relatively new and less numerous in the domain of robots for education; examples are [24] (teaching geometry) and [7, 20, 44, 15] (teaching programming and robotics). We aim to not only improve the currently lacking subject coverage, but also equip our platform with natural collaborative aspects by designing low cost, replaceable robots that operate in large numbers. ...
One of the main issues with the acceptance of robotic tools in schools is the extracurricular aspect of the learning activities using these robots. In the Cellulo project, we developed a novel robotic platform that aims to provide a ubiquitous, versatile and practical tool for teachers with subjects varying among the different topics at their respective school curricula. In order to show the potential of Cellulo in the classroom as part of standard curricular activities, we designed a learning activity called Windfield that aims to teach the atmospheric formation mechanism of wind to early middle school children.
... Studies that are concerned with collaborative learning aim to measure social interactions among the learners and group dynamics. Such studies are relatively new and less numerous in the domain of robots for education; examples are [24] (teaching geometry) and [7,20,44,15] (teaching programming and robotics). We aim to not only improve the currently lacking subject coverage, but also equip our platform with natural collaborative aspects by designing low cost, replaceable robots that operate in large numbers. ...
This article presents a learning activity and its user study involving the Cellulo platform, a novel versatile robotic tool designed for education. In order to show the potential of Cellulo in the classroom as part of standard curricular activities, we designed a learning activity called Windfield that aims to teach the atmospheric formation mechanism of wind to early middle school children. The activity involves a didactic sequence, introducing the Cellulo robots as hot air balloons and enabling children to feel the wind force through haptic feedback. We present a user study, designed in the form of a real hour-long lesson, conducted with 24 children in 8 groups who had no prior knowledge in the subject. Collaborative metrics within groups and individual performances about the learning of key concepts were measured with only the hardware and software integrated in the platform in a completely automated manner. The results show that almost all participants showed learning of symmetric aspects of wind formation while about half showed learning of asymmetric vectorial aspects that are more complex.
... 3) Robot as Learning Object (RaLO), which extends the notion of an LO beyond the virtual domain (learning content) to a physical domain (robot hardware and physical processes that are demonstrated by the hardware) [36,37]. ...
We present a vision of using educational robots as smart mobile components (“things”) of Internet-of-Things. Such robots, beside their primary mission to facilitate learning, are able to communicate; have computing capabilities; as well as have sensors and actuators to sense and change their physical context. The robot serves both as the educational service that allows to visualize knowledge through explicit actions and behaviour as well as the enabler of learning and providing student engagement through immersion and instant feedback. The vision is based on the principles of contextualization, physicality and immersion. The pedagogical background is the proposed Internet-of-Things Supported Collaborative Learning (IoTSCL) paradigm based on constructivism, which provides a highly motivating learning environment in university, promoting collaboration among students, and achieving the creation of new knowledge in a reflexive process directed by the teacher. We demonstrate the implementation of the paradigm in the project-based setting at the university course and evaluate it using the Four-Phased Model of Interest Development.
... Learning materials and processes can be self-organized and adapted according to students' real-time interest and psychological statuses [33]. Things are implemented as Mobile Robots, which can move and interact with their environments [34]., which extends the notion of an LO beyond the virtual domain (learning content) to a physical domain (robot hardware and physical processes that are demonstrated by the hardware) [36, 37]. Connecting learning services and materials to physical objects enriched with sensors is a next step in the evolution of Learning Objects and e-learning environments. ...
Educational systems are complex adaptive systems with basic properties of openness, nonlinearity, feedback and adaptivity. Modelling and assessment of a teaching/learning process is a difficult task that involves many factors at multiple dimensions (pedagogical, technological, organizational, social, etc.). Common methods used for evaluation of teaching/learning effectiveness such as surveys, questionnaires and tests are subjective and lack of statistical control and standards for comparison. In this paper, we propose an empirical knowledge transfer model for closed teacher-learner systems and its extension for open teacher-learner systems. The model is based on the theory of communication in noisy channels with additive white Gaussian noise. We describe the pedagogical interpretation of the model’s parameters and describe its application in modelling the transfer of knowledge in the teaching/learning process.
... It could be equipped with smart things like RFID or NFC tags, or sensors and actuators …So the learning object could be constructed by a physical resource and a software resource. By definition, a physical learning object (PLO), which is a new type of learning objects, is a smart thing using sensors and/or actuators to interact with its environment and content and control its behavior [7]. ...
The Internet of Things paradigm when combined to Learning Enhanced Technology pushes instructional designers to rethink learning scenarios. The use of smart objects including smart learning objects in learning environments is an increasing trend to evolve the learner's progress in learning. Learning scenarios in such environments are characterized by the detection of the learner's contextual information are as well as the adaptation of pedagogical strategies and services according to this context. In order to enhance the user's experience, we propose ontological models that allow intelligent interpretation of contextual data including tracked one and so relevant adaptation of the learning scenario is proposed.
... A variant of constructivism, called constructionism [12], focuses on knowledge reconstruction by students using meaningful artefacts such as educational robots. The latter is especially suitable for engineering education where real physical (tangible) entities can be used as LOs [13,14]. The created artefacts can be used (or reused) as models and visual aids for further learning [15]. ...
The paper introduces context-aware Generative Learning Objects (GLOs) to support wide-scale reusability and automatic adaptability in teaching Computer Science (CS) topics. We introduce the theoretical background of the approach to support adaptation through transformations based on the principles of Design-for-Reuse and Design-with-Reuse, which are well known in Software Engineering (SWE), and validate the approach in the robotics-based CS course. We automatically adapt GLOs to the specific context of teaching using transformation tools (refactoring tool and metalanguage processor) to transform a set of context-aware GLOs into usable LOs within the educational Arduino robotics environment.
... The educational priorities must shift towards teaching students how to manipulate all digital devices (smart phones, tablet PCs, smart TVs, robots, etc.) that surround them for their own needs. Robots can be seen as multi-faceted tools with different roles in engineering education as follows: Robot as specialized computer with both computational and mechanical facilities to perform physical movementoriented tasks [1]; Robot as a mobile smart thing: a mobile platform for wireless sensors in the context of the Internet of Things [2];2012201320142015, funded by the European Social Fund (ESF). [3]: physical and reusable unit of knowledge that can be used to teach the concepts of programming, robot control and artificial intelligence; This paper presents an analysis of educational visual programming languages in the context of robotics-based teaching, identifies main problems and proposes solutions for improving visual languages and extending them to the Internet-of-Things domain. ...
Visual programming languages provide a more natural approach to specifying software/hardware systems with complex behaviour such as robots. They are especially important in education because they do not require formal knowledge of programming language syntax and are attractive to users. We present an analysis and comparison of two visual programming environments, Lego NXT-G and Microsoft Visual Programming Language, based on the cognitive and usability requirements, evaluate their application in robotics-based Computer Science education, identify main problems and propose solutions for using visual programming languages in the Internet-of-Things domain.
Bu araştırmanın amacı, eğitsel robotlarla blok tabanlı kodlama kursu hizmet içi eğitimine katılan öğretmenlerin hizmet içi eğitime yönelik tutum düzeylerini, eğitimde bilgi teknolojileri kullanımı öz-yeterlilik düzeylerini ve sınıf içi eğitsel robot kullanımı kabul düzeylerini belirlemektir. Araştırma deseni, karma yöntem araştırma desenlerinden gömülü (içe yerleşik) karma desendir. Araştırmanın nicel boyutunda veri toplama araçları olarak “Hizmet İçi Eğitime Yönelik Tutum Ölçeği”, “Eğitimde Bilgi Teknolojileri Kullanımı Öz-Yeterliliği Öğretmen Değerlendirme Formu” ve “Sınıf İçi Eğitsel Robot Kullanımı Kabul Ölçeği” kullanılmıştır. Araştırmanın nitel boyutunda ise araştırmacı tarafından hazırlanan yarı yapılandırılmış görüşme formu kullanılmıştır. Araştırmanın çalışma grubunu deney grubunda 48 ve kontrol grubunda 25 öğretmen oluşturmaktadır. Deney grubuna Lego Mindstorms Ev3 ve mBot ürünleri ile eğitim verilmiştir. Kontrol grubuna Scratch 3 programlama aracı ile eğitim verilmiştir. Normallik analizi için çarpıklık ve basıklık değerleri incelenmiştir. Veriler aritmetik ortalama, standart sapma ve bağımsız örneklem t testi kullanılarak incelenmiştir. Sonuç olarak eğitsel robot uygulamaları Scratch’a göre öğretmenlerin hizmet içi eğitime yönelik tutum düzeylerine daha fazla katkı sağlamamaktadır. Eğitsel robot uygulamaları Scratch’a göre öğretmenlerin eğitimde bilgi teknolojileri kullanımı öz-yeterlilik düzeylerine daha fazla katkı sağlamamaktadır. Ancak faktörler açısından bakıldığında Temel Beceri ve teknoloji faktörleri açısından eğitsel robot uygulamaları anlamlı düzeyde daha fazla katkı sağlamaktadır. Eğitsel robot uygulamaları Scratch’a göre öğretmenlerin sınıf içi eğitsel robot kullanımı kabul düzeylerine daha fazla katkı sağlamamaktadır.
Efforts to raise the bar of higher education so as to respond to dynamic societal/industry needs have led to a number of initiatives , including artificial neural network (ANN) based educational data mining (EDM) inclusive. With ANN-based EDM, humongous amount of student data in higher institutions could be harnessed for informed academic advisory that promotes adaptive learning for purposes of student retention, student progression, and cost saving. Mining students' data optimally requires predictive data mining tool and machine learning technique like ANN. However, despite acknowledging the capability of ANN-based EDM for efficiently classifying stu-dents' learning behavior and accurately predicting students' performance, the concept has received less than commensurate attention in the literature. This seems to suggest that there are gaps and challenges confronting ANN-based EDM in higher education. In this study, we used the systematic literature review technique to gauge the pulse of researchers from the viewpoint of modeling, learning procedure, and cost function optimization using research studies. We aim to unearth the gaps and challenges with a view to offering research direction to upcoming researchers that want to make invaluable contributions to this relatively new field. We analyzed 190 studies conducted in 2010-2018. Our findings reveal that hardware challenges, training challenges, theoretical challenges, and quality concerns are the bane of ANN-based EDM in higher education and offer windows of opportunities for further research. We are optimistic that advances in research along this direction will make ANN-based EDM in higher education more visible and relevant in the quest for higher education-driven sustainable development.
The technological growth follows an exponential trend, and we will hit the knee in the curve in 2029. From that time, challenges will rapidly change, and the job demand will ask for profiles that we can only partially predict. Therefore, there is the need to adapt educational programs to exponential growth as soon as possible to provide children of today (alias future citizens) with the necessary basic skills and the ability to easily combine them to face any challenge the future will pose. We consider computational thinking and robotics as fundamental skills since students should be provided with transversal critical thinking and be technologically-aware to meet job demands. Thus, i) we designed Roobopoli, a project focused on the direct experience of robotics, and ii) we propose an educational procedure to teach robotics by exploiting Roobopoli through a constructionism-based approach. We tested our approach both in formal and informal educational settings by involving students heterogeneous in age, skills, and personal attitudes. The engagement and the interest manifested by participants prove that the constructionism-based approach, in general, and Roobopoli, in particular, are positively accepted by students to learn robotics and to develop computational thinking. In this article, we will present both Roobopoli and the performed experiments by pointing out lessons learned.
This paper presents the design of an assessment process and its outcomes to investigate the impact of Educational Robotics activities on students' learning. Through data analytics techniques, the authors will explore the activities' output from a pedagogical and quantitative point of view. Sensors are utilized in the context of an Educational Robotics activity to obtain a more effective robot–environment interaction. Pupils work on specific exercises to make their robot smarter and to carry out more complex and inspirational projects: the integration of sensors on a robotic prototype is crucial, and learners have to comprehend how to use them. In the presented study, the potential of Educational Data Mining is used to investigate how a group of primary and secondary school students, using visual programming (Lego Mindstorms EV3 Education software), design programming sequences while they are solving an exercise related to an ultrasonic sensor mounted on their robotic artifact. For this purpose, a tracking system has been designed so that every programming attempt performed by students' teams is registered on a log file and stored in an SD card installed in the Lego Mindstorms EV3 brick. These log files are then analyzed using machine learning techniques (k-means clustering) in order to extract different patterns in the creation of the sequences and extract various problem-solving pathways performed by students. The difference between problem-solving pathways with respect to an indicator of early achievement is studied.
The current learning environments focus on the development of skills which are related to problem solving, creativity and critical thinking addressing the needs of learners in today’s society. Computer programming includes this kind of skills and it is placed at the center of attention of the educational policy. Approaching programming is a difficult task because of its complex concepts, thus educators are seeking effective methods for teaching it. This paper presents the design of digital learning objects for teaching programming concepts and the results of a pilot empirical study with special users. The results reveal that the proposed learning objects seem to be a useful tool for teachers, aligned with the learning goals and can be employed in authentic scenarios.
In this chapter, we analyse new possibilities for STEM and CS education with regard to the Internet-of-Things (IoT). Typically, researchers define the IoT as an emerging networked infrastructure penetrated by embedded smart devices, called things, which have identities, sensing-actuating and computing capabilities, are connected via the Internet, can communicate with each other and with humans and can provide semantics of some useful services such as education. With this chapter, we aim to achieve two objectives: (i) to introduce the terminology of IoT for the book readers to start more thorough studies and (ii) to show the relevance of this topic to the ones we have discussed so far in the previous chapters. We present the architecture for considering tasks relevant to the IoT and CS education. We discuss a framework for solving some IoT tasks and a case study and experiments with these tasks.
This monograph presents the challenges, vision and context to design smart learning objects (SLOs) through Computer Science (CS) education modelling and feature model transformations. It presents the latest research on the meta-programming-based generative learning objects (the latter with advanced features are treated as SLOs) and the use of educational robots in teaching CS topics. The introduced methodology includes the overall processes to develop SLO and smart educational environment (SEE) and integrates both into the real education setting to provide teaching in CS using constructivist and project-based approaches along with evaluation of pedagogic outcomes. Smart Learning Objects for Smart Education in Computer Science will appeal to researchers in CS education particularly those interested in using robots in teaching, course designers and educational software and tools developers. With research and exercise questions at the end of each chapter students studying CS related courses will find this work informative and valuable too.
Basic computational thinking, so necessary in today's society, can be learned in an engaging way with the use of educational robots. In order to reach very diverse groups of people, educational robots need to be simple, scalable and low cost.
Inspired by the success of the LOGO project, we have developed the Phogo pedagogical platform, built around a low cost robot (less than $80) capable of tracing its path with a marker pen. We also present a high-level Python-based control library that allows for transparent and easy wireless communication with the robots. The approach was tested in an informal workshop with a group of teenagers without any previous self-conscious computational knowledge. As the students were attracted by the robot and the simple approach, they were able to gain some insight about abstract programming concepts such as variables, functions, and flow control structures. The majority of the students were people with physical, cognitive or intellectual disabilities and they were able to follow, enjoy and learn as any other student making this an accessible activity to everyone.
Finally, we summarize our efforts documenting and publishing the Phogo system as open-source in order to promote its use in future workshops.
In this paper, we introduce a methodology to design robot-oriented generative learning objects (GLOs) that are, in fact, heterogeneous meta-programs to teach computer science (CS) topics such as programming. The methodology includes CS learning variability modelling using the feature-based approaches borrowed from the SW engineering domain. Firstly, we define the CS learning domain using the known educational framework TPACK (Technology, Pedagogy And Content Knowledge). By learning variability we mean the attributes of the framework extracted and represented as feature models with multiple values. Therefore, the CS learning variability represents the problem domain. Meta-programming is considered as a solution domain. Both are represented by feature models. The GLO design task is formulated as mapping the problem domain model on the solution domain model. Next, we present the design framework to design GLOs manually or semi-automatically. The multi-level separation of concepts, model representation and transformation forms the conceptual background. Its theoretical background includes: (a) a formal definition of feature-based models; (b) a graph-based and set-based definition of meta-programming concepts; (c) transformation rules to support the model mapping; (d) a computational Abstract State Machine model to define the processes and design tool for developing GLOs. We present the architecture and some characteristics of the tool. The tool enables to improve the GLO design process significantly (in terms of time and quality) and to achieve a higher quality and functionality of GLOs themselves (in terms of the parameter space enlargement for reuse and adaptation). We demonstrate the appropriateness of the methodology in the real teaching setting. In this paper, we present the case study that analyses three robot-oriented GLOs as the higher-level specifications. Then, using the meta-language processor, we are able to produce, from the specifications, the concrete robot control programs on demand automatically and to demonstrate teaching algorithms visually by robot's actions. We evaluate the approach from technological and pedagogical perspectives using the known structural metrics. Also, we indicate on the merits and demerits of the approach. The main contribution and originality of the paper is the seamless integration of two known technologies (feature modelling and meta-programming) in designing robot-oriented GLOs and their supporting tools.
First, the term ‘smart educational environment’ should be defined. There are standard educational environments that are based on using the Internet-based technology along with some e-learning-oriented systems such as Moodle. In the widest sense, the word ‘environment’ should be understood as the overall technological support (hardware, software and networking with remote terminals) and the infrastructure of the methodological support, including databases or digital libraries with the teaching content, management facilities and teaching instructions (for teachers and students) to support e-learning. The base actors (teachers and students), maintenance facilities and personnel might be also treated as components of the environment. In the narrow sense, by the educational environment, we mean the facilities for functioning e-learning processes to achieving teaching goals within the teaching organization. Using the m-learning paradigm, for example, on the smartphones basis, perhaps, one can treat as being the smart environment too.
The aim of this chapter is to introduce and discuss a taxonomy-based framework to understand the CS LO domain in large. I motivate the need of such a framework by the following reasons: (1) LO domain is commonly recognized as the heart of e-learning in general; (2) the LO concept is accepted and its role well understood for teaching CS as well; (3) the LO domain is continuously evolving in horizontal (meaning in general) and vertical dimensions (meaning in CS); and (4) a taxonomy-based approach is fundamental in many aspects (knowledge and artefacts systemizing, standardizing, sharing, gaining and teaching). Here, within the introduced framework, we highlight and consider (to some extent only) the following tasks: (1) concept-based modelling and experimentation using a restricted database of literature sources (about 500) and (2) creation of ontology-based models among those concepts that are most likely relevant to our approach.
The long term use of Parallax Boe-Bot robots in teaching has brought out some problems of the kit. To further use the robot's hardware platform, we made some modifications of the controller unit. In the process we developed a PCB with XESS XuLA FPGA board and Bluetooth module to replace the kit's initial controller. The Bluetooth module adds wireless programming functionality for the FPGA, which in turn is running on MicroBlaze soft-core processor. The outcome of the work is an over-the-air and in C language programmable Boe-bot robot kit. Simple tests were conducted to make sure the robot's power consumption can stand for one session of handson exercises.
We propose an approach and tools for designing heterogeneous meta-program (MP) through feature model (FM) transformations. Tools implement the State Machine (ASM) computational model. Firstly, to map the problem domain FM onto the solution domain FM, we use FAMILIAR and SPLOT tools. Next, to perform Model-to-MP transformations, we use newly developed tools. We present the process-based framework and background of the approach along with a case study, experimental validation and evaluation. The main contribution of the paper is the ASM-based transformation model, its implementation algorithm to describe the functioning of the developed tools.
Basic Programming is a first year mandatory course of the Computer Engineering degree. Both students and teachers face difficulties in this course, which has high failure and drop-out rates. Several authors have proposed the use of visual programming environments and robots to overcome the difficulties of this course, some of which have been successful. This paper presents the two-year experiment using Lego Robots carried out at the University of the Basque Country (UPV/EHU) with around 100 students, along with the results. Satisfactory results have been obtained regarding both motivation and the perception of the students of their learning process; moreover the drop-out rate decreased even though no statistical significance was obtained regarding the final marks of the course. From those results and the analysis of the data it was derived that robot sessions should be more integrated in the curriculum, giving them greater relevance in the final marks. In addition, it is indispensable to classify course students and adapt learning sessions to each student type due to the high student heterogeneity.
The difference between smart home (or smart agent) and intellectualized smart home (or intellectual smart agent) is delivered, and the framework for their modelling is described. Question of a sophisticated adequacy evaluation is raised to compare the reality and its model. The proposed approach was used to evaluate four different decision making technologies implemented in the models of the intellectualized smart home environment, and the comparison of those experimental technologies prepared by expert is presented.
In the modern pedagogical practices based on socio-cultural approaches on learning, students are seen as active agents who share ideas, solve open-ended problems, use various information sources, and create new knowledge together. Teachers, who want to implement such practices in their classrooms, often face with the demands of changing their traditional ways of designing teaching. Classic models of instructional design are not very applicable to collaborative learning because they mainly concentrate on individual processes of learning and are based on the strict pre-structuring of content and activities. The pedagogical design of collaborative learning is more indirect, focusing on organizing the preconditions for the eligible collaborative activity but not causally determining the learning results. Building on such views, the present paper introduces a framework of pedagogical infrastructures, consisting of technical, social, epistemological and cognitive components; to be used in designing and analysing technology enhanced collaborative learning units. Also the role of e-learning content in such educational settings is discussed through this presented framework.
This paper discusses the concept of a social robot. Developing from recent work on physical embodiment, the necessity for a socially embodied robot is presented. Current work via the Social Robot Architecture seeks to develop and demonstrate these concepts.
This paper presents a pilot project using an educational robotics curriculum that was developed to enhance teaching of standard physics and math topics to middle and early high school students in inner-city schools in New York City. The lessons are centered around the LEGO Mindstorms robotics kit and the RoboLab graphical programming environment. The pilot project, testing the curriculum in two summer programs for early high school students, was conducted in 2003 at two locations in Harlem, New York City, USA.
The field of Computer-Supported Collaborative Learning (CSCL) explores the design and use of collaboration technologies to support learning systems, such as school classrooms or small groups of people building knowledge together. I hope that CSCL environments can be designed that make possible and encourage groups to think and learn collaboratively. In my research, my colleagues and I look at logs of student groups chatting and drawing about mathematics in order to see how they build on each other's ideas to achieve more than they would individually. There are many theories useful for framing the cognitive work that groups undertake in CSCL and other collaboration settings, and they may in principle not be reducible to a single theory. Collaboration research explores questions involving numerous distinct-though interacting-phenomena at multiple levels of description. It may be most useful to clearly distinguish levels such as individual, small-group and community units of analysis, and to differentiate terminology for discussing these different levels. Seminal theoretical works influential within collaboration research suggest a post-cognitive approach to group cognition as a complement to analyzing cognition of individuals or of communities of practice. The traditional argument between quantitative vs. qualitative approaches may be moot; increasingly, studies mix methods to obtain a fuller picture, using cases studies to describe processes and statistics to generalize models of variables. Since CSCL combines researchers from technical backgrounds, including AI, with those from social sciences, the current tension may be more between those seeking cognitive explanations and those providing situated descriptions. For instance, many researchers want to guide students toward knowledge-building behaviors while others want to understand how students do the work of collaborative learning, without imposing interpretive standards. This may, for instance, involve coding stu-
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dent utterances into categories of pre-defined interest vs. analyzing the conversational moves and interactional practices that uniquely occur in specific traces of online interaction. The results can be as different as confirming hypotheses about general variables vs. exploring the complex network of social and technical phenomena at work in a unique situation of collaboration. A variety of studies of learning systems seem necessary to guide design of collaboration technologies.
In this paper, we discuss the applications and implications of the Programmable Brick-a tiny, portable computer embedded inside a LEGO® brick, capable of interacting with the physical world in a large variety of ways. We describe how Programmable Bricks make possible a wide range of new design activities for children, and we discuss experiences in using Programmable Bricks in three types of applications: autonomous creatures, active environments, and personal science experiments.
This paper discusses the issues pertinent to the development of a meaningful social interaction between robots and people through employing degrees of anthropomorphism in a robot’s physical design and behaviour. As robots enter our social space, we will inherently project/impose our interpretation on their actions similar to the techniques we employ in rationalising, for example, a pet’s behaviour. This propensity to anthropomorphise is not seen as a hindrance to social robot development, but rather a useful mechanism that requires judicious examination and employment in social robot research.
We build an analytical model for an application utilizing master-slave paradigm. In the model, only three architecture parameters
are used: latency, bandwidth and flop rate. Instead of using the vendor supplied or experimentally determined values, these
parameters are estimated using the analytical model itself. Experimental results on Cray T3E and SGI Origin 2000 indicate
that this simple model can give fair predictions.
Research on social robots is mainly comprised of research into algorithmic problems in order to expand a robot's capabilities to improve communication with human beings. Also, a large body of research concentrates on the appearance, i.e. aesthetic form of social robots. However, only little reference to their definition is made. In this paper we argue that form, function, and context have to be taken systematically into account in order to develop a model to help us understand social robots. Therefore, we address the questions: What is a social robot, what are the interdisciplinary research aspects of social robotics, and how are these different aspects interlinked? In order to present a comprehensive and concise overview of the various aspects we present a framework for a definition towards social robots.
Cognition, faculty related to perception, imagination, memory, and problem solving, refers to internal mental processes through which sensorial input is acquired, elaborated, used, and stored. One of its importances relies on the fact that it affects in a direct way the learning potential. It has been shown that, even thou cognitive processes develop side by side with biological maturity, this cognitive development can be enhanced by means of mediated learning as signaled by Feuerstein's Mediated Learning theory. Based on this theory is that we propose an intervention model that addresses school academic issues using technologically assisted small group collaboration, pursuing a dual academic objective: to thrive students' cognitive processes while addressing school curriculum topics. The purpose, therefore, is to balance the students' cognitive differences by means of in-school content-filled classroom activities. Our aim is to make use of peer mediation in a real world setting with a virtual construction of it. In this paper, we describe this novel intervention model along with an in-school usage experience. For this, we present an activity designed for high school students, specifically aimed to assist the learning of kinematics, graph interpretation, and graph plotting. In this activity the students work in groups of three, using a robot and wirelessly interconnected Personal Digital Assistants (PDA). By means of a controlled experiment, we show how technologically-supported peer mediation promotes the students' enrichment of their cognitive processes in each of the different stages of the mental act (input-elaboration- output), favoring communication skills, insight, and reasoning, while also restraining impulsive conduct and trial-and-error answers.
Computer-supported collaborative learning (CSCL) is an emerging branch of the learning sciences concerned with studying how people can learn together with the help of computers. As we will see in this essay, such a simple statement conceals considerable complexity. The interplay of learning with technology turns out to be quite intricate. The inclusion of collaboration, computer mediation and distance education has problematized the very notion of learning and called into question prevailing assumptions about how to study it. Like many active fields of scientific research, CSCL has a complex relationship to established disciplines, evolves in ways that are hard to pinpoint and includes important contributions that seem incompatible. The field of CSCL has a long history of controversy about its theory, methods and definition. Furthermore, it is important to view CSCL as a vision of what may be possible with computers and of what kinds of research should be conducted, rather than as an established body of broadly accepted laboratory and classroom practices. We will start from some popular understandings of the issues of CSCL and gradually reveal its more complex nature. We will review CSCL's historical development and offer our perspective on its future. CSCL within education As the study of particular forms of learning, CSCL is intimately concerned with education. It considers all levels of formal education from kindergarten through graduate study as well as informal education, such as museums. Computers have become important in this, with school districts and politicians around the world setting goals of increasing student access to computers and the Internet. The idea of encouraging students to learn together in small groups has also become increasingly emphasized in the broader learning sciences. However, the ability to combine these two ideas (computer support and collaborative learning, or technology and education) to effectively enhance learning remains a challenge—a challenge that CSCL is designed to address. Computers and education Computers in the classroom are often viewed with skepticism. They are seen by critics as boring and anti-social, a haven for geeks and a mechanical, inhumane form of training. CSCL is based on precisely the opposite vision: it proposes the development of new software and applications that bring learners together and that can offer creative activities of intellectual exploration and social interaction. CSCL arose in the 1990s in reaction to software that forced students to learn as isolated individuals. The exciting potential of the Internet to connect people in innovative ways provided a stimulus for CSCL research. As CSCL developed, unforeseen barriers to designing, disseminating and effectively taking advantage of innovative educational software became more
We introduce a concept of Robots As Learning Objects (RALO) and a framework of methodology for robotics-oriented teaching of Computer Science (CS) topics based on the Constructivist and Empirical Modelling paradigms. Our methodology views robotic technologies not as mere tools, but rather as vehicles of new ways of thinking and reasoning about teaching, learning and education at large. We formulate the pedagogy-driven activities , technology-driven processes, knowledge transfer channels with actors involved, tools and facilities used, and the pedagogical outcome in the robot-based constructivist learning process and describe our experience in using RALOs for teaching CS at high school (gymnasium) and university levels.
It is difficult to motivate learners to learn abstract Computer Science topics (e.g., data structures, algorithms and programming) with the adequate level of engagement. We present the process of constructing a LEGO robot, called the DRAWBOT (drawing robot), which enables to create the e-learning environment to demonstrate visually the solution of graph-based Computer Science tasks through teaching programming. Our research has confirmed the importance of using robot-based environments for teaching that was known so far in the literature on e-learning. We have extended the known approaches: a) by providing technical characteristics for the process to create the e-learning environment for the real setting; b) by smoothly integrating different phases of the process and considering it into entirety to support the constructivist learning model.
Robots motivate interest in the presentation of STEM field topics and provide a vehicle for model teaching. The four robots recognized in this paper have been selected for their price and applicability to model teaching. An overview of each kit is presented and essential topics that the tutorials teach are addressed. A comparison is provided evaluating the appropriateness of each platform.
This article presents a constructionist approach to introducing technology, in particular robotics, in the early childhood classroom. The authors demonstrate how this approach is well suited, since the four basic tenets of constructionism have a long-standing tradition in early childhood education: (a) learning by designing meaningful projects to share in the community, (b) using concrete objects to build and explore the world, (c) the identification of powerful ideas that are both personally and epistemologically significant, and (d) the importance of self-reflection as part of the learning process. This article introduces a methodology for teaching preservice teachers to integrate technology in the classroom. It also describes four different experiences in which preservice teachers designed and integrated robotic projects done with LEGO Mindstorms and ROBOLAB to engage their young students in exploring and learning new concepts and ways of thinking.
This chapter discusses how various theories of learning and forms of pedagogy shape the technologies used to instantiate them,
and how the evolution of computers and telecommunications is widening the range of instructional designs available. Three
alternative schools of thought on how people learn have strongly influenced the design of instructional technologies: Behaviorism,
Cognitivism, and Constructivism. Behaviorist instructional technologies are limited both in what they can teach and in the
types of engagement they offer to learners, but are useful for tasks involving learning facts and simple procedural skills.
Scholars disagree on how broad a range of knowledge and skills Cognitivist instructional technologies can teach, but they
are effective for well-defined content and skills that have a few correct ways of accomplishing tasks. Constructivist approaches
can teach a very broad spectrum of knowledge and skills, however, the efficiency of Constructivist technologies for material
that these other two schools of thought can teach is questionable. Emerging technologies such as multi-user virtual environments
and augmented realities enable new types of pedagogical strategies based on situated learning.
The design and implementation of a robot team consisting of three homogeneous mobile robots and an external server is presented. The main goal of the robot team is the updating of a map or representation of an indoor environment. A scheme for collective exploration was defined. This scheme enables robots to navigate and self-locate within an indoor environment, communicate to each other, create local maps of their environment to be merged into a global map, and coordinate individual actions in order to explore autonomously the environment. Finally, the performance of the robot team was evaluated in various environmental conditions.
This paper presents a design for a platform of collaborative robots and electronic devices. The platform design is based on the similarity between the type, functionality and characteristics of the robot or device. We categorize the participating devices by functionality rather than by architecture, therefore making it easy to support new robots or devices with similar functions but different architectures. This approach also allows users to develop, implement and port applications quickly and easily. We demonstrate the efficacy and correctness of our platform through a variety of robotic applications ranging from research to teaching.
It is commonly agreed that a well-balanced mix of collaboration, training and simulation eventually produce a superior learner. Today's collaborative design and learning environments in- tegrate variety of interactive objects as well as many technological aspects to achieve such balance. Unfortunately, the actual profit of the resulting learning systems is largely reduced by poorly rep- resented interactive objects as well as poor interlinking between such objects. In particular, such objects appear isolated: they neither can be modified sufficiently (e.g., by choosing parameters or enhancing functionality) nor be interlinked properly with their context (e.g., by synchronizing with a guided tour or metadata). We are presenting in this article a model for representing virtual and 3D scenes as learning objects. The model utilizes notions and techniques based on Scene Graphs, X3D, Java3D, and SceneBeans. The prototype accompanied with a simple client-server protocol for exchanging and viewing the 3D SceneBeans. This research aims to extend this protocol by utilizing Sun JXTA primitives to link to the POOL of other learning objects repositories.
This study reviews recently published scientific literature on the use of robotics in schools, in order to: (a) identify the potential contribution of the incorporation of robotics as educational tool in schools, (b) present a synthesis of the available empirical evidence on the educational effectiveness of robotics as an educational tool in schools, and (c) define future research perspectives concerning educational robotics. After systematically searching online bibliographic databases, ten relevant articles were located and included in the study. For each article, we analyze the purpose of the study, the content to be taught with the aid of robotics, the type of robot used, the research method used, and the sample characteristics (sample size, age range of students and/or level of education) and the results observed. The articles reviewed suggest that educational robotics usually acts as an element that enhances learning, however, this is not always the case, as there are studies that have reported situations in which there was no improvement in learning. The outcomes of the literature review are discussed in terms of their implications for future research, and can provide useful guidance for educators, practitioners and researchers in the area.
solve problems, and make decisions Anuradha A. Gokhale is an Associate Professor at Western Illinois University in the Department of Industrial Education and Technology, and is currently a Visiting Associate Professor at Illinois State University. -23- as a team. Therefore, the development and enhancement of critical-thinking skills through collaborative learning is one of the primary goals of technology education. The present research was designed to study the effectiveness of collaborative learning as it relates to learning outcomes at the college level, for students in technology. Purpose of Study This study examined the effectiveness of individual learning versus collaborative learning in enhancing drill-and-practice skills and criticalthinking skills. The subject matter was series and parallel dc circuits. Research Questions The research questions examined in this study were: 1. Will there be a significant difference in achievement on a test comprised of "drill-and practice
We consider the problem of how two heterogeneous robots can arrange to meet in an unknown environment from unknown starting locations: that is, the problem of arranging a robot rendezvous. We are interested, in particular, in allowing two robots to rendezvous so that they can collaboratively explore an unknown environment. Specifically, we address the problem of how a pair of exploring agents that cannot communicate with one another over long distances can meet if they start exploring at different unknown locations in an unknown environment.
We propose several alternative algorithms that robots could use in attempting to rendezvous quickly while continuing to explore. These algorithms exemplify different classes of strategy whose relative suitability depends on characteristics of the problem definition. We consider the performance of our proposed algorithms analytically with respect to both expected- and worst-case behavior. We then examine their behavior under a wider set of conditions using both numerical analysis and also a simulation of multi-agent exploration and rendezvous. We examine the exploration speed, and show that a multi-robot system can explore an unknown environment faster than a single-agent system, even with the constraint of performing rendezvous to allow communication.
We conclude with a demonstration of rendezvous implemented on a pair of actual robots.
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