Submitted Successfully!
To reward your contribution, here is a gift for you: A free trial for our video production service.
Thank you for your contribution! You can also upload a video entry or images related to this topic.
Version Summary Created by Modification Content Size Created at Operation
1 -- 3369 2023-04-02 20:26:43 |
2 Reference format revised. Meta information modification 3369 2023-04-03 07:03:30 | |
3 Description revised -3 word(s) 3366 2023-04-03 07:06:45 | |
4 remove blank line Meta information modification 3366 2023-04-06 08:22:18 |

Video Upload Options

Do you have a full video?

Confirm

Are you sure to Delete?
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Kalaitzidou, M.; Pachidis, T.P. Robots in STEAM Education. Encyclopedia. Available online: https://encyclopedia.pub/entry/42724 (accessed on 19 May 2024).
Kalaitzidou M, Pachidis TP. Robots in STEAM Education. Encyclopedia. Available at: https://encyclopedia.pub/entry/42724. Accessed May 19, 2024.
Kalaitzidou, Magdalini, Theodore P. Pachidis. "Robots in STEAM Education" Encyclopedia, https://encyclopedia.pub/entry/42724 (accessed May 19, 2024).
Kalaitzidou, M., & Pachidis, T.P. (2023, April 02). Robots in STEAM Education. In Encyclopedia. https://encyclopedia.pub/entry/42724
Kalaitzidou, Magdalini and Theodore P. Pachidis. "Robots in STEAM Education." Encyclopedia. Web. 02 April, 2023.
Robots in STEAM Education
Edit

Robotics is increasingly entering the field of education. The tools, methods, and approaches of robotics contribute to the development of all areas of STEAM education, both individually and interdisciplinary. The entry highlights the robots that are most effective in STEAM education and to classify robots used in education in terms of their frequency of use, features, flexibility, manufacturer, sensors, software, programming language, connection, recommended age, usefulness in education, and their cost. It turned out that there are packages for building robots, pre-assembled robots, and social robots. Their form can be animal, human, car, etc., and they have various properties; for example, they can move and fly. Moreover, most of the robots proposed for education use block-based programming; for example, the Scratch language. Common features of robots are that the robot follows a path, reacts to sounds, and recognizes obstacles, with various sensors; for example, vision. Finally, it turned out to be necessary to design an activity guide for each lesson, which will be accompanied by instructions and specific steps for teachers and students.

STEAM education robotics printable robots educational robots 3D robots

1. Introduction

The use of new technologies motivates students to learn at different educational levels. Robotics is one of the expressions of technology and takes place in various contexts of life [1]. Interest in robotics in education is growing more and more. In general, robots can be used as intelligent mobile learning objects that facilitate the understanding of complex and abstract concepts and phenomena, and students can touch them. That is why they have been the subject of much research [2][3][4][5]. The introduction of robots to school reality goes hand in hand with modern learning theories (e.g., social constructivism) which claim that knowledge arises through the interaction of the individual with the environment and is enhanced by practical activities and active involvement of the individual [6]. Robotics promotes student-centered learning, its interests, and the demands of society using innovative methods, and it is related to critical education, as it aims to develop active citizens in today’s society [7][8]. In addition, robot learning activities can provide environments that promote teamwork, collaboration, communication, and creativity. Therefore, it contributes to the development of all the basic skills of the 21st century.
Robotics can take place in a school in two ways, either as a learning object or as a means of teaching other cognitive subjects. It is inextricably linked to STEAM education. The term STEAM education means a set of educational activities focused on the fields of Natural Sciences, Technology, Engineering, Arts, and Mathematics. Robotics is one of the sections of STEAM education and, at the same time, it can contribute as a means for the development and understanding of its other fields; the tools, methods, and approaches of robotics contribute to the development of all areas of STEAM education, both individually and interdisciplinary.

2. STEAM Education

STEAM education attempts the transition from traditional teacher-centered teaching to teaching where exploratory learning plays a dominant role. Students collaborate in groups to solve problems through projects, using the scientific method (observation, hypothesis, experiment, theory, and law).
This is a general philosophy of adapting the whole educational system to combine Science and Technology. One field penetrates the other offering it its tools. Science offers the method of observation, prediction, experimentation, discovery, and reflection. Technology gives the technological means and the method of the invention of new ideas. Engineering provides information about the motion of physical bodies and the interaction of forces. The Arts offer creative expression through, for example, music, theater, painting, etc.

3. Robotics in STEAM Education

In recent years, the use of robotics as a tool for learning other subjects, such as Mathematics, Physics, Language, Visual Arts, etc., has begun to be explored [9]. Robots enable the student to understand complex and abstract concepts as they make them clearer and more specific. This is achieved through the student’s contact with the robot. The robot has the role of facilitator in learning; that is, it becomes the student’s assistant [10]. The authors in Ref. [11] note in their research that few articles explore robotics approaches and methodologies for STEAM education. Therefore, there are great research opportunities in this field. Research typically examines robotics approaches in STEAM education, proposes robotic machines, explores low-cost solutions, and looks for applications that are directly related to the real world, from elementary to high school [12][13][14]. At the same time, many studies have shown that the concepts of robotics and STEAM education are inextricably linked [9][15][16][17][18][19][20]. One is the other’s helper in fulfilling their goals. Both promote teamwork, and the development of creativity and imagination in students, based on testing, experimentation, and the discovery of new knowledge. Robotics helps to teach all STEAM fields simultaneously in an applied way [21].

4. Robots That Can Be Used in Education

Currently, on the market, there is a wide variety of robotic platforms (commercial or research-derived) for STEAM education and robotics that are usually offered “ready to use”. For example, Lego Mindstorms EV3, NAO, mBot, etc. Most include a microcontroller, which is the control unit, i.e., the brain of the robot system; various sensors that detect or measure the physical properties of the environment, such as temperature, light, touch, sound, humidity, etc.; various actuators for the conversion of energy into motion, sound, light, heat, etc.; materials such as cables, batteries, gears, wheels, plastic bricks, plastic or metal parts for the assembly of various mechanical structures, e.g., robot cars, cranes, drones, watermills, and many more. They also include a software application loaded on the microcontroller and a guide to support teachers and students [22]. However, in most cases, they are not accompanied by flexible and varied lesson plans and activities. A systematic literature review was carried out in major international journals (MDPI (Basel, Switzerland), IEEE (New York USA), etc.), online digital libraries, and search engines such as Eric, Google Scholar, etc., regarding robots that have been used in education. A wide variety of educational robots were identified, most of which focused on teaching computer science and programming. Of these, only robots that have been used to teach other subjects, such as Mathematics and Physics, were selected. The type of robots was considered, and both commercial and research robots were included. Next, some of these selected robots are described in detail and their effectiveness is highlighted. The study concerns the cost of each robot, its capabilities, its use in education, and its manufacturer.
A Lego robot is the Mindstorms EV3 (Figure 1a). The Mindstorms EV3 has coded wheels, and wireless communication with the computer and costs about EUR 450 [23]. There are a variety of Lego construction kits available on the market that allow students to build and program robots quickly and easily. They consist of building materials (bricks, gears, pulleys, and shafts) and programming software with an efficient graphical interface for the development of robotic applications based on Lego robots. Robot programming results in the juxtaposition of a sequence of visualized actions, possibly related to events and/or situations generated by the applied sensors. These actions are easily configured via the graphical user interface [24]. It has color, speech, touch and gyroscope sensors, and motors. Lego robotic kits are the most commonly used robots in education, from Kindergarten to University. Assembly is their main feature. Modular design allows students to create their own robots, thus helping them improve their visual–spatial skills and motivating them to experiment and innovate [1].
Figure 1. (a) Lego Mindstorms EV3; (b) Edison Robot V2; (c) Vex IQ Robotics (d) Thymio.
Another modular robotics platform that allows students to perform traditional-style programming is the Vex IQ Robotics (Figure 1c), which costs around EUR 400. It includes simple programming languages and has a sufficient number of ports and a variety of sensors. One of the downsides of Vex IQ Robotics is its modular design, which does not appeal to a wide range of kids [1].
Edison Robot V2 (Figure 1b) [25] is another learning platform, but of low cost (about EUR 60), which also has special notches for placing Lego bricks. It is flexible and its size is the size of a palm (7.5 × 4 × 8.5 cm). With its sensors, it can follow a light source or a black line, move when students clap, detect obstacles, and can be programmed to be remotely controlled [26]. Depending on the age, it can be programmed with EdBlocks, EdScratch, and EdPy, which are based on familiar programming languages but are designed to work with Edison. With Edison, each student can have a robot in the classroom.
In terms of fully assembled mobile robots, the EPFL Thymio (Figure 1d) [27] is a commercially assembled robot. Thymio’s platform is reprogrammable, rich in sensors and actuators, rechargeable, and appreciated by many students as it promotes creativity and fun learning, and it is cheap and durable [28]. Thymio has five basic components, these are the following: cables, wheels, a proximity sensor, a battery, and a button unit [29]. It has a thermometer and a three-axis accelerometer. It is open-source at the software level but also at the hardware level.
On 5 June 2014, Softbank Mobile, a Japanese company, in collaboration with Aldebaran Robotics, a French company, unveiled Pepper (Figure 2a) [30][31], the first personal humanoid robot in the world capable of helping people by reading and responding to human emotions. Pepper was scheduled to sell for less than USD 2000 in the US in February 2015 [32]. Of course, Peppers robots are only sold with the required network data and equipment security for 36 months. This costs USD 360 per month, which brings the total cost of ownership to over USD 14,000. It generally ranges from USD 14,000 to USD 14,600 [31]. The price also is approximately EUR 13,600. It has a height of 1.2 m and weighs 28 kg. It can be programmed to speak 15 languages, including Greek. Finally, it is equipped with a fully functional tablet and is an open and fully programmable platform.
Figure 2. (a) Pepper robot; (b) NAO robot; (c) Beebot robot; (d) mBot robot.
Another humanoid assembled robot is the SoftBankRobotics NAO robot (Figure 2b). The NAO robot is 58 cm in size, weighs no more than 5 kg, speaks, hears, sees, relates to the environment as programmed, and interacts naturally. It is able to perceive its environment through many sensors. It consists of two cameras, four microphones, nine touch sensors, two ultrasonic sensors, eight pressure sensors, an accelerometer, a gyroscope, a voice synthesizer, and two speakers. The robot is programmed by a block-based graphical software, Choregraphe, which communicates with NAO. This software is a graphical blockchain programming interface that provides specific tasks for NAO [33].
A cheap robot is the Beebot (Figure 2c) which costs EUR 100 [34] and is suitable for kindergarten and elementary school students. It has a bee shape and at the top, it has buttons for its programming. It is small and can be moved forward, backward, right, and left. It does not use any special software to program. Due to its appearance, it attracts young students. According to [35], it is effective in developing working memory, spatial awareness, and problem-solving ability in young students. Beebot creates a play environment suitable for children from 3 to 5 years old and is an ideal tool for teaching programming for these ages [36]. Of course, it can be used equally satisfactorily for the acquisition of mathematical and geometrical concepts [37][38].
Another robot is the mBot [39], which is an Arduino-based robot. MBot (Figure 2d) is a small mobile robot, which is cheap and has many possible expansion options. It costs EUR 100 and can be programmed using a block-based programming environment. It is created by the Chinese company, Makeblock, and based on the Scratch language that contains blocks. It is equipped with two motors for the wheels, an ultrasonic sensor, and a line sensor, and is aimed at primary and secondary school students. Students must build the robot for the first time, which can be used as part of the original workshops [40]. One of its main advantages is that it allows the user to program in a block language.
Another small intelligent robot for children is the Ozobot (Figure 3a) [41]. It contributes to the learning of STEAM education and can read colored lines drawn on paper. It has the shape of a sphere, about two and a half centimeters in diameter, its movement is based on very small wheels, and, at its base, color sensors are located. Color sensors allow it to read the color codes designed. In this way, he can perfectly follow a color line and interpret the intersections of lines. It costs about EUR 100. With Ozobot, you can design a variety of games such as racetracks, puzzles, mazes, etc. These games aim to cultivate and develop in students important skills such as creativity, autonomy, logic, and programming. Not only can Ozobot be programmed using color bars; it can also be programmed on a tablet through a block-based application called OzoBlocky, which is similar to Scratch. Thus, students will be able to carry out more complex programming as they progress in their learning (Figure 3b) [8].
Figure 3. (a) Ozobot; (b) programming Ozobot (left) (Source: adapted from [42]) and storytelling with Ozobot (right) (Source: adapted from [43]); (c) Cellulo.
Cellulo (Figure 3c) is a new robotics platform that explores the intersection of three ideas for robotics in education. These ideas are designing robots to be flexible, blending robots into the classroom by designing them to be pervasive objects and creating close interactions with paper, and finally understanding the practical limitations of real classrooms at each stage of design. The platform emerged from these considerations and is based on a unique combination of technologies. The robot connects wirelessly to a tablet (or smartphone) via Bluetooth and activity is coordinated with the QtQuick app. It also comes with optional additional dynamic content and activity sheets printed on plain paper. It is an affordable robot since it costs around EUR 125 and is suitable for use in the classroom. The role of the robot and paper depends on the goal of each activity, which makes the robot flexible [44]. Various concepts that can be approached are atmospheric pressure, force, Cartesian plane, planetary motion, molecules, and atoms.
Another robot based on the Arduino platform designed from 3D printable materials is the Otto DIY + robot (Figure 4a) [45]. Its price is around EUR 45 and increases depending on the possibilities it provides. It is fully programmable with Blockly or Arduino. It is easy to build, scalable, and modular. It is suitable for beginners in the world of robotics and STEM. The Otto robot can walk, dance, make sounds, gesture, and avoid obstacles. It can be used to teach programming to students while completing other educational activities. Moreover, the programmed Otto robot can be easily stored and transported anywhere; each student could have their own robot and use it at home [46].
Figure 4. (a) Otto DIY+ Arduino Robot; (b) Otto robot programming software; (c) The FOSSbot.
Otto comes with a variety of applications and games (Figure 4b) [47][48]. Through his games, the children prepare for programming and learn to code while having fun. This way, programming becomes exciting and easy for everyone. The main game that accompanies the robot has Otto as its hero. It is an interactive, free, educational game, and suitable for anyone who wants to start programming with Blockly, Python, and JavaScript, as it is based on both block and text programming. A student can connect from any computer or tablet, as long as they have an Internet connection. The aim of the game is for students to program the robot so that it can face the challenges and adventures that take place around it.
Activities and games with the Otto robot promote computational thinking; that is, they support problem-solving and Mathematics, and develop critical thinking and basic concepts from computer science. They are based on scenarios, which motivate children, as they make the learning process fun and playful. Its integration into the curricula supports and guides the learning process. Finally, it enables teachers to monitor students’ progress at each level as they progress through the game [49].
Another printable robot is FOSSbot [50] (Free Open Source Software Bot—Figure 4c) [51], an educational robot that is suitable for kindergarten and primary school, although the creation of educational scenarios for all levels of education has begun. FOSSbot was built by the open technologies organization EELLAK in collaboration with Harokopio University and is a printable open-source robot, both in its construction and its software. Open source codes can be adapted and support even more teaching scenarios. Its codes and files are uploaded to the internet completely free of charge, so the cost is only for the supply of materials that will be used for its printing. It has a variety of sensors such as distance, line, accelerometer, gyroscope, IR, light sensor, a sensor for odometry, and battery sensor. It can also talk; it has a case on the front where a marker or pencil can be placed, and its surface is compatible with Lego bricks. Thus, it can be used in various ways in the classroom, as the various sensors and actuators can give to teachers the ability to create numerous lessons and activities that cover a wide range of scientific disciplines. The total cost for printing and supplying all materials is under EUR 200 [52]. This price, although considered high for the average family, is low based on the possibilities it offers.

5. Programming Languages

In the description of the above robots, the related programming languages were mentioned. Some of these languages are presented in more detail below. First, there are traditional scripting languages and visual programming languages. The first category includes Python [52][53][54], C, C++, Java, JavaScript [55], etc., and is the basis for the creation of the second, i.e., visual programming languages.
In primary school age or education in general, it would be easier to use a visual programming language. The term “visual programming language” means a programming language that is based on visual expressions and is suitable for beginners [56]. These expressions are either icons and blocks (puzzles), or diagrams and forms, which act as commands and conditions for the user to program the robot object he desires. These expressions are asked by the user to drag them and put them in the appropriate order to write the code that will command the robot to act. Some visual programming languages used in education are AgentSheets, App Inventor (for Android), Blocky, Bubble, Scratch, etc.
One of the most popular languages is Scratch. This is evidenced by the fact that it has been used in a variety of studies [57][58][59][60][61][62][63][64][65][66][67]. Scratch’s goal is for students to learn programming concepts by playing and creating videos and music. In other words, it enables teachers to use it as a means of teaching in their classrooms. Scratch is free and available online. Its shape makes it quite attractive to students of both primary and secondary education. Moreover, one of its advantages is that it is dynamic, as users can edit and modify its code while it is running. Behind the visual expressions, the executable code runs in the Squeak (Scratch 0. x, Scratch 1. x) or ActionScript (Scratch 2.0) written programming languages. According to the research in [68], 50% of the published work they found on STEAM education uses Scratch. Scratch can be an important lead in introducing advanced students to the Python programming language [69].
Google Blockly [52][70], is a language similar to Scratch and supports the logic of drag and drop, i.e., “drag and drop” (Figure 5). Its programming is based on traditional JavaScript, Python, PHP, Lua, or Dart languages and is available for free. Its commands are in the form of block puzzles, which are connected to create the respective scenario [71].
Figure 5. Instruction in the Blockly Programming Language.
Finally, Snap [72] is also a form of block programming language (Figure 7). One of the advantages of Snap is that it allows students to program for free directly on a website, without the need to install any software. It has all the basic functions of Scratch with the advantage that it gives the user the ability to create new block commands and share them in the Snap community. It is very simple to use. Instructions for its use are available on the website [73]. In general, it is observed that visual programming languages can increase students’ interest in mathematical concepts and robotics, advance their computational thinking and prepare them for more advanced programming languages and robotics designs [74].
Figure 7. Online Snap Programming Language.

References

  1. Pachidis, T.; Vrochidou, E.; Kaburlasos, V.G.; Kostova, S.; Bonkovic, M.; Papic, V. Social robotics in education: State-of-the-art and directions. In International Conference on Robotics in Alpe-Adria Danube Region; Aspragathos, N., Koustoumpardis, P., Moulianitis, V., Eds.; Springer: Cham, Germany, 2018; Volume 67, pp. 689–700.
  2. Alimisis, D. Educational robotics: Open questions and new challenges. Themes Sci. Technol. Educ. 2013, 6, 63–71.
  3. Atmatzidou, S.; Demetriadis, S. A Didactical Model for Educational Robotics Activities: A Study on Improving Skills through Strong or Minimal Guidance. In Educational Robotics in the Makers Era; Springer: Cham, Germany, 2016; pp. 58–72.
  4. Benitti, F.B.V. Exploring the educational potential of robotics in schools: A systematic review. Comput. Educ. 2012, 58, 978–988.
  5. Komis, V.; Romero, M.; Misirli, A. A Scenario-Based Approach for Designing Educational Robotics Activities for Co-Creative Problem Solving. In Educational Robotics in the Makers Era; Springer: Cham, Germany, 2016; pp. 158–169.
  6. Vygotsky, L.S. Mind in Society: The Development of Higher Psychological; Harvard University Press: Cambridge, MA, USA, 1978.
  7. Günbatar, M.S.; Bakırcı, H. STEM teaching intention and computational thinking skills of pre-service teachers. Educ. Inf. Technol. 2019, 24, 1615–1629.
  8. Román-Graván, P.; Hervás-Gómez, C.; Martín Padilla, A.H.; Fernández Márquez, E. Perceptions about the Use of Educational Robotics in the Initial Training of Future Teachers: A Study on STEAM Sustainability among Female Teachers. Sustainability 2020, 12, 4154.
  9. Karim, M.E.; Lemaignan, S.; Mondada, F. A review: Can robots reshape K-12 STEM education? In Proceedings of the IEEE International Workshop on Advanced Robotics and Its Social Impacts (ARSO 2015), Lyon, France, 1–3 July 2015; pp. 1–8.
  10. Miller, D.P.; Nourbakhsh, I. Robotics for Education. In Springer Handbook of Robotics; Siciliano, D., Khatib, O., Eds.; Springer Science & Business Media: Berlin, Germany, 2016; pp. 2115–2134.
  11. Bravo, F.; Hurtado, J.; González, E. Using Robots with Storytelling and Drama Activities in Science Education. Educ. Sci. 2021, 11, 329.
  12. Bellas, F.; Naya, M.; Varela, G.; Llamas, L.; Prieto, A.; Becerra, J.C.; Bautista, M.; Faina, A.; Duro, R. The Robobo Project: Bringing Educational Robotics Closer to Real-World Applications. In Robotics in Education. RiE 2017; Springer: Cham, Germany, 2018.
  13. Karkazis, P.; Balourdos, P.; Pitsiakos, G.; Asimakopoulos, K.; Saranteas, I.; Spiliou, T.; Roussou, D. To water or not to water: The Arduino approach for the irrigation of a field. Int. J. Smart Educ. Urban Soc. 2018, 9, 25–36.
  14. Moro, M.; Agatolio, F.; Menegatti, E. The development of robotic enhanced curricula for the RoboESL project: Overall evaluation and expected outcomes. Int. J. Smart Educ. Urban Soc. 2018, 9, 48–60.
  15. Altin, H.; Pedaste, M. Learning approaches to applying robotics in Science Education. J. Balt. Sci. Educ. 2013, 12, 365–377.
  16. Barnes, J.; FakhrHosseini, S.M.; Vasey, E.; Park, C.H.; Jeon, M. Child-Robot Theater: Engaging Elementary Students in Informal STEAM Education Using Robots. IEEE Pervasive Comput. 2020, 19, 22–31.
  17. Chatzopoulos, A.; Papoutsidakis, M.; Kalogiannakis, M.; Psycharis, S. Action Research Implementation in Developing an Open Source and Low Cost Robotic Platform for STEM Education. Int. J. Comput. Appl. 2019, 178, 33–46.
  18. Eguchi, A.; Okada, H. Learning with social robots—The World Robot Summit’s approach. In Proceedings of the IEEE Integrated STEM Education Conference (ISEC), Princeton, NJ, USA, 10 March 2018.
  19. Psycharis, S.; Kotzampasaki, E. The Impact of a STEM Inquiry Game Learning Scenario on Computational Thinking and Computer Self-Confidence. EURASIA J. Math. Sci. Technol. Educ. 2019, 15, em1689.
  20. Sullivan, A.; Strawhacker, A. Screen-Free STEAM: Low-Cost and Hands-on Approaches to Teaching Coding and Engineering to Young Children. In Embedding STEAM in Early Childhood Education and Care; Cohrssen, C., Garvis, S., Eds.; Palgrave Macmillan: Cham, Germany, 2021; pp. 87–113.
  21. Kazakoff, E.R.; Sullivan, A.; Bers, M.U. The effect of a classroom-based intensive robotics and programming workshop on sequencing ability in early childhood. J. Early Child. Educ. 2013, 41, 245–255.
  22. Kucuk, S.; Sisman, B. Behavioral patterns of elementary students and teachers in one-to-one robotics instruction. Comput. Educ. 2017, 111, 31–43.
  23. BrickEconomy Home Page. Available online: https://www.brickeconomy.com/set/31313-1/lego-mindstorms-ev3 (accessed on 19 November 2022).
  24. Alimisis, D.; Moro, M.; Arlegui, J.; Pina, A.; Frangou, S.; Papanikolaou, K. Robotics & Constructivism in Education: The TERECoP project. In EuroLogo 2007, 40 Years of Influence on Education, Proceedings of the 11th European Logo Conference, 19–24 August 2007; Kalas, I., Ed.; Comenius University: Bratislava, Slovakia, 2007.
  25. Edison Home Page. Available online: https://meetedison.com/wp-content/uploads/2016/09/Edison-V2.0-Educational-robot.jpg (accessed on 19 November 2022).
  26. Ververi, C.; Koufou, T.; Moutzouris, A.; Andreou, L.V. Introducing Robotics to an English for Academic Purposes Curriculum in Higher Education: The Student Experience. In Proceedings of the 2020 IEEE Global Engineering Education Conference (EDUCON), Porto, Portugal, 27–30 April 2020.
  27. Thymio Home Page. Available online: http://www.thymio.gr/ (accessed on 19 November 2022).
  28. Riedo, F.; Chevalier, M.; Magnenat, S.; Mondada, F. Thymio ii, a robot that grows wiser with children. In Proceedings of the 2013 IEEE Workshop on Advanced Robotics and Its Social Impacts (ARSO), Tokyo, Japan, 7–9 November 2013; IEEE: Piscataway, NJ, USA, 2013; pp. 187–193.
  29. Riedo, F.; Retornaz, P.; Bergeron, L.; Nyffeler, N.; Mondada, F. A Two Years Informal Learning Experience Using the Thymio Robot. In Advances in Autonomous Mini Robots; Springer: Berlin/Heidelberg, Germany, 2012; pp. 37–48.
  30. Aldebaran Home Page. Available online: https://www.aldebaran.com/en/pepper (accessed on 19 November 2022).
  31. Bots.co.uk Home Page. Available online: https://bots.co.uk/pepper-robot-price/ (accessed on 19 November 2022).
  32. Eguchi, A. Robotics as a Learning Tool for Educational Transformation. In Proceedings of the 4th International Workshop Teaching Robotics, Teaching with Robotics & 5th International Conference Robotics in Education, Padova, Italy, 18 July 2014; pp. 27–34.
  33. Lopez-Caudana, E.; Ramirez-Montoya, M.S.; Martínez-Pérez, S.; Rodríguez-Abitia, G. Using Robotics to Enhance Active Learning in Mathematics: A Multi-Scenario Study. Mathematics 2020, 8, 2163.
  34. STEM-Toys Home Page. Available online: https://stem-toys.gr/product/beebot-2/ (accessed on 19 November 2022).
  35. Messer, D.; Thomas, L.; Holliman, A.; Kucirkova, N. Evaluating the effectiveness of an educational programming intervention on children’s mathematics skills, spatial awareness, and working memory. Educ. Inf. Technol. 2018, 23, 2879–2888.
  36. Kwon, U.-J.; Nam, K.-W.; Lee, J.-H. Exploring the effects of unplugged play for children aged 3, 4, and 5: Based on Bee-bot. Int. J. Adv. Cult. Technol. 2020, 8, 239–245.
  37. González, J.; Morales, I.; Nielsen, M.; Muñoz, L.; Villarreal, V. Improving the Teaching of Mathematics through Robotics. Proceedings 2019, 31, 5.
  38. Di Lieto, M.C.; Inguaggiato, E.; Castro, E.; Cecchi, F.; Cioni, G.; Dell’Omo, M.; Laschi, C.; Pecini, C.; Santerini, G.; Sgandurra, G.; et al. Educational Robotics intervention on Executive Functions in preschool children: A pilot study. Comput. Hum. Behav. 2017, 71, 16–23.
  39. Makeblock Home Page. Available online: www.makeblock.com/STEM-kits/mbot (accessed on 19 November 2022).
  40. Bellas, F.; Salgado, M.; Blanco, T.F.; Duro, R.J. Robotics in Primary School: A Realistic Mathematics Approach. In Smart Learning with Educational Robotics: Using Robots to Scaffold Learning Outcomes; Linda, D., Ed.; Springer International Publishing: Cham, Germany, 2019; pp. 149–182.
  41. Makey Makey Home Page. Available online: http://bit.ly/placa-makey-makey (accessed on 19 November 2022).
  42. Tengler, K.; Sabitzer, B.; Kastner-Hauler, O. First Programming with Ozobots-A Creative Approach to Early Computer Science In Primary Education. In Proceedings of the INTED2020 Conference, Valencia, Spain, 2–4 March 2020; pp. 5156–5163.
  43. Tengler, K.; Sabitzer, B.; Kastner-Hauler, O. Enhancing Computational Thinking Skills using Robots and Digital Storytelling. In Proceedings of the 13th International Conference on Computer Supported Education (CSEDU 2021), Online, 23–25 April 2021; Volume 1, pp. 157–164.
  44. Özgür1, A.; Lemaignan, S.; Johal, W.; Beltran, M.; Briod, M.; Pereyre, L.; Mondada, F.; Dillenbourg, P. Cellulo: Versatile Handheld Robots for Education. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’17, Vienna, Austria, 6–9 March 2017; pp. 119–127.
  45. MakerBot Thingiverse Otto DIY+ Home Page. Available online: https://www.thingiverse.com/thing:2398231 (accessed on 19 November 2022).
  46. Meirinhos, C.; Fernandes, L. Tangible Objects in ESL Classroom: Impact in Learning at Primary School Level. In Hands-On Science: Education Activities—Challenges and Opportunities of Distant and Online Teaching and Learning; Costa, M.F., Dorrío, B.V., Eds.; Hands-On Science Network: Braga, Portugal, 2021; p. 232.
  47. Otto Builders Home Page. Available online: https://builders.ottodiy.com/ (accessed on 19 November 2022).
  48. Ottodiy Home Page. Available online: https://www.ottodiy.com/ (accessed on 19 November 2022).
  49. Ottodiy Games Home Page. Available online: https://www.ottodiy.com/games (accessed on 19 November 2022).
  50. GitHub Fossbot Home Page. Available online: https://github.com/eellak/fossbot (accessed on 19 November 2022).
  51. EELLAK Home Page. Available online: https://openhardware.ellak.gr/wp-content/uploads/sites/13/2022/04/front_unc.png (accessed on 19 November 2022).
  52. Chronis, C.; Varlamis, I. FOSSBot: An Open Source and Open Design Educational Robot. Electronics 2022, 11, 2606.
  53. Lee, Y.D.; Chung, J.I. The effects of middle school mathematical statistics area and Python programming STEAM instruction on problem solving ability and curriculum interest. J. Korea Acad.-Ind. Coop. Soc. 2019, 20, 336–344.
  54. Svistkov, A.I.; Sutchenkov, A.A.; Tikhonov, A.I. STEM and STEAM Technologies in Problem Solving with Python. In Proceedings of the 3rd International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE), Moscow, Russia, 1 April 2021; IEEE: Piscataway, NJ, USA, 2021.
  55. Iwamoto, T.; Matsumoto, S. Development of Web-Based Programming Learning Support System with Graph Drawing of Mathematics as a Learning Task. In Proceedings of the 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI), Toyama, Japan, 7–11 July 2019; pp. 302–305.
  56. Tumlin, N. Teacher Configurable Coding Challenges for Block Languages. In Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, SIGCSE ’17, Seattle, WA, USA, 8–11 March 2017; ACM Publications: New York, NY, USA; pp. 783–784.
  57. Scratch Home Page. Available online: https://scratch.mit.edu/ (accessed on 19 November 2022).
  58. De la Hoz Serrano, A.; Cañada Cañada, F.; Melo Niño, L.V.; Álvarez Murillo, A.; Cubero Juánez, J. Design of a robotic board for teaching the Water Cycle. In Proceedings of the 14th International Conference on Education and New Learning Technologies, Palma, Spain, 4–6 July 2022; pp. 2990–2993.
  59. Fidai, A.; Capraro, M.M.; Capraro, R.M. “Scratch”-ing computational thinking with Arduino: A meta-analysis. Think. Ski. Creat. 2020, 38, 100726.
  60. Lee, Y.D.; Kim, S.I.; Seo, Y.H.; Kang, J.J. A Study on the Robot Education Based on Scratch. J. Converg. Cult. Technol. 2016, 2, 29–35.
  61. Korkmaz, O. The Effect of Scratch- and Lego Mindstorms Ev3-Based Programming Activities on Academic Achievement, Problem-Solving Skills and Logical-Mathematical Thinking Skills of Students. Malays. Online J. Educ. Sci. 2016, 4, 73–88.
  62. Michalopoulos, P.; Mpania, S.; Karatrantou, A.; Panagiotakopoulos, C. Introducing STEM to primary education students with Arduino and S4A. In Innovating STEM Education: Increased Engagement and Best Practices; Koleza, E., Panagiotakopoulos, C., Skordoulis, C., Eds.; Common Ground Research Networks: Champaign, IL, USA, 2022; pp. 77–87.
  63. Pou, A.V.; Canaleta, X.; Fonseca, D. Computational Thinking and Educational Robotics Integrated into Project-Based Learning. Sensors 2022, 22, 3746.
  64. Xefteris, S. Developing STEAM Educational Scenarios in Pedagogical Studies using Robotics. Eng. Technol. Appl. Sci. Res. 2021, 11, 7358–7362.
  65. Maloney, J.; Resnick, M.; Rusk, N.; Silverman, B. The scratch programming language and environment. ACM Trans. Comput. Educ. 2010, 10, 1–15.
  66. Meerbaum-Salant, O.; Haberman, B.; Pollack, S. “Computer Science, Academia and Industry” as pedagogical model to enhance Computational thinking. In Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE ’15, Vilnius, Lithuania, 4–8 July 2015; p. 341.
  67. Monroy-Hernández, A. ScratchR: Sharing user-generated programmable media. In Proceedings of the 6th International Conference on Interaction Design and Children, IDC ’07, Aalborg, Denmark, 6–8 June 2007; pp. 167–168.
  68. Fernandes, E.; Fermé, E.; Oliveira, R. Using Robots to Learn Functions in Math Class. 2017. Available online: http://cee.uma.pt/people/faculty/elsa.fernandes/artigos/ICMI17.pdf (accessed on 2 December 2021).
  69. Anastasaki, E.; Vassilakis, K. Experimental commands development for LEGO WeDo 2.0 in Python language for STEAM robotics advanced classes. Adv. Mob. Learn. Educ. Res. 2022, 2, 443–454.
  70. GitHub Google Blockly Home Page. Available online: https://github.com/google/blockly (accessed on 19 November 2022).
  71. Shih, W.C. Mining Learners’ Behavioral Sequential Patterns in a Blockly Visual Programming Educational Game. In Proceedings of the 2017 International Conference on Industrial Engineering, Management Science and Applicationa (ICIMSA), Seoul, Republic of Korea, 13–15 June 2017; IEEE: Piscataway, NJ, USA, 2017; pp. 1–2.
  72. Snap Home Page. Available online: https://snap.berkeley.edu/snap/snap.html (accessed on 19 November 2022).
  73. Snap! Education Home Page. Available online: https://snapeducation.weebly.com/eta-pirhoomegataueta-epsilonpialphaphieta-muepsilon-tauomicron-snap.html (accessed on 19 November 2022).
  74. Newley, A.; Deniz, H.; Kaya, E.; Yesilyurt, E. Engaging Elementary and Middle School Students in Robotics through Hummingbird Kit with Snap! Visual Programming Language. J. Learn. Teach. Digit. Age 2016, 1, 20–26.
More
Information
Subjects: Robotics
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register : ,
View Times: 1.2K
Revisions: 4 times (View History)
Update Date: 06 Apr 2023
1000/1000