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
Pedro D. Gaspar
 -- 1540 2023-12-06 13:08:49 |
2 format correct
Catherine Yang
 + 6 word(s) 1546 2023-12-07 01:49:14 |

Video Upload Options

Do you have a full video?
Send video materials Upload full video

Confirm

Are you sure to Delete?
Yes No
Cite
If you have any further questions, please contact Encyclopedia Editorial Office.
Antunes, R.; Aguiar, M.L.; Gaspar, P.D. Mobile Robotics Enhancing Critical Thinking and Interdisciplinary Skills. Encyclopedia. Available online: https://encyclopedia.pub/entry/52442 (accessed on 05 July 2024).
Antunes R, Aguiar ML, Gaspar PD. Mobile Robotics Enhancing Critical Thinking and Interdisciplinary Skills. Encyclopedia. Available at: https://encyclopedia.pub/entry/52442. Accessed July 05, 2024.
Antunes, Rodrigo, Martim Lima Aguiar, Pedro Dinis Gaspar. "Mobile Robotics Enhancing Critical Thinking and Interdisciplinary Skills" Encyclopedia, https://encyclopedia.pub/entry/52442 (accessed July 05, 2024).
Antunes, R., Aguiar, M.L., & Gaspar, P.D. (2023, December 06). Mobile Robotics Enhancing Critical Thinking and Interdisciplinary Skills. In Encyclopedia. https://encyclopedia.pub/entry/52442
Antunes, Rodrigo, et al. "Mobile Robotics Enhancing Critical Thinking and Interdisciplinary Skills." Encyclopedia. Web. 06 December, 2023.
Mobile Robotics Enhancing Critical Thinking and Interdisciplinary Skills
Edit
This entry is adapted from the peer-reviewed paper 10.3390/technologies11060170

The integration of mobile robotics kits into a dynamic STEM (science, technology, engineering, and mathematics)-focused curriculum offers students an immersive and hands-on learning experience, fostering programming skills, advanced problem-solving, critical thinking, and spatial awareness. The motivation behind this research lies in improving the effectiveness of robotics education by addressing existing gaps in current strategies. 

integrated educational resources robotics mobile robotics kits Industry 4.0

1. Introduction

The term “robotics” first appeared in the short story “Runaround” by Isaac Asimov, published in 1942. Leonardo Da Vinci designed a knight that was supposed to move automatically, but the construction of an automaton with such characteristics only emerged in 1962 by Joseph Engelberger and George Devol, named “Ultimate” [1]. Robotics is defined as the set of techniques aimed at designing systems capable of replacing humans in their motor, sensory, and intellectual functions.
According to the World Robotics Report 2022 by the International Federation of Robotics, robotics is experiencing expansion, with a particular emphasis on industrial robotics. In 2021, a total of 517,385 industrial robots were installed in factories worldwide, representing a year-on-year growth rate of 31% and surpassing the previous peak in robot installations before the pandemic in 2018, which was around 11%. Currently, the global stock of operational robots has reached a new record of approximately 3.5 million units [2].
The increasing interest in robotics within the industry entails a need to prepare a qualified workforce to deal with technological innovations. Therefore, implementing robotics in education is imperative for the future of engineering.
Robotic educational resources are a powerful and flexible tool as they enable students to discover things on their own, learn new programming languages, and develop working methodologies and critical thinking. Students can apply theoretical concepts in practical robotics projects, which helps to solidify their knowledge and develop technical skills such as programming, mechanics, and electronics. Numerous researchers argue that activities involving robot programming increase participants’ interest in the fields of STEM (science, technology, engineering, and mathematics) [3].

2. Computational Thinking

Computational thinking (CT) is the systematic thinking process learners employ while “solving problems, designing systems, and understanding human behaviour by drawing on fundamental concepts of computer science (CS)”. Ideas involving CT emerged in the 1950s [4]. Papert [5] was the first to describe CT in his work related to programming in Logo and the Logo turtle, an educational robot. In the early 2000s, CT was revitalized by Wing (2006) as she refined the definition and emphasized the importance of CT as part of every child’s skill set. However, in the field of education, there is still no consensus on the definition of CT [6]. Some definitions of CT remain linked to disciplines in the field of computing, specifically computer science [7]. Other definitions have been created in the context of other non-CS curriculum units. For instance, Weintrop et al. [8] conducted a literature review on CT and interviewed experts in the fields of mathematics and science to develop a definition based on four categories: data essays, modelling and simulation essays, computational problem-solving essays, and systems thinking essays. Others relate computational thinking to engineering, and there are still those who define CT from a multidisciplinary approach. Shute et al. [9] assert that CT is a necessary conceptual foundation for solving problems effectively and efficiently.
The National Research Council (NRC) conducted a series of workshops focused on CT and subsequently released a report on its educational and cognitive implications. The participants in the NRC workshop agreed that it was necessary to take the next step in conducting similar activities with a greater focus on the pedagogical aspects of CT [10]. To implement CT activities in K-12 classrooms, the Computer Science Teachers Association (CSTA) and the International Society for Technology in Education (ISTE) formed a team of education and industry leaders to develop a framework that integrates computer science and computational thinking [11].
Various tools have been used to teach these components, some of which are related to the work carried out by Papert [5] in the field of educational programming language, including educational toys and applications designed for children. Currently, a wide range of robotic kits can be found on the market [7].

3. Strategies and Methodologies in Teaching Programming/Robotics

There are various teaching philosophies. The main recommendation that emerges from the literature is that teaching should focus not only on learning the characteristics of a particular programming language but also on combining them and particularly on the related problem of designing basic programs. One way to achieve this could be through the introduction of numerous examples as programs are developed, discussing the strategies used as part of this process [12].
According to Coll et al. [13], the teacher should: gradually present the content, with moments of recapitulation, summary, and synthesis; make analogies, using students’ prior knowledge; be explanatory regarding the proposed activities and what is to be taught; provide opportunities for students to execute procedures voluntarily, consciously, and innovatively; and make improvements. Students should be motivated to learn the procedures and be able to self-evaluate, knowing that the construction of knowledge depends on their effort.
Students should develop concrete and real projects, and it is necessary to make some simplifications through a method of gradual development [14].
Some authors emphasize the importance of a trial-and-error approach for students to find programming errors, using reflection, understanding, analysis, and hypothesis testing [15].
According to Roumani [16], the curriculum should be taught in an inverted manner, meaning that after students are comfortable with the behaviour and applications of the main data structures, they should learn how to implement them.
Teachers should adopt strategies and activities that motivate students to engage in their learning and allow them to develop autonomy. When engaging in challenges, an increasing level of complexity should be emphasized, encouraging the integration of knowledge from various disciplines, and students should cooperate in small groups to solve them [17].
An interesting field to be explored is robot football (soccer), since it can embrace a large number of disciplines such as computer vision, intelligence artificial, computer science, physics, mathematics, mechanical, and general engineering. Apart from being a field that connects different topics of engineering, it is attractive for all kinds of people due to football being one of the most popular sports and the idea of seeing robots playing soccer is fascinating for children, adolescents, and adults [18].

4. Educational Robotics

As mentioned earlier, there is a wide range of robots available for all levels of education, serving different purposes [7]. Several studies have shown that educational activities involving robotics can be highly effective in developing skills such as critical thinking, creativity, problem-solving, teamwork, and decision-making, among others [19].
Robotics has generally been applied in education for students ranging from 3 to 18 years old, from preschool to secondary education [20]. According to Xia and Zhong [20], the majority of applications are found in elementary school students (57%), followed by secondary school students (24%), and kindergarten children (19%). More than half of the studies conducted used samples with fewer than 80 participants and a duration of less than 2 months. The dominant type of robot used in the studies was the LEGO brand (67%).
Educational robots are programmed by their users to act based on specific information obtained from the environment in which they are placed. They are equipped with a set of sensors that enable them to measure various conditions and transmit this information to the robot’s controller. There is a wide range of sensors available, including light sensors, touch sensors, temperature sensors, humidity sensors, rotation sensors, sound sensors, colour sensors, and distance sensors. At the same time, the robot has actuators, which, as the name suggests, allow it to interact with the environment. Typically, these are motors that enable the addition of various mechanisms such as robotic arms, wheels, and transmission systems (gearboxes) [17]. Thus, through the analysis of scientific references and studies, it can be concluded that there is a wide range of educational robots available. Some options even allow for the construction of robots using low-cost or recyclable materials. Alongside the growth of this field of robotics, various block-based programming environments have emerged, designed for use by children. These environments facilitate programming and interaction, making initial encounters with programming more accessible and contributing to educational development. Given the diversity of educational robot offerings, this section will address some solutions available on the market and experimental studies that explore the influence of their use on learning (Table 1).
Table 1. Detailed overview of each educational robotics platform, emphasizing additional features and characteristics.
Platform Description Key Features Study/Reference
Bee-Bot Prominent floor robot in elementary education, controlled through physical buttons for directional programming.
  • Resembles a bee; Controlled via physical buttons for turning, and moving forward/backward; Supports the development of programming skills, cognitive abilities, and spatial awareness.
 Diago et al. [1]
Schina et al. [21]
Kazakoff et al. [22]
WeDo 2.0 Robotics kits by LEGO Education, designed for interactive teaching of basic concepts.
  • LEGO pieces, motors, sensors; Interactive programming software (WeDo 2.0); Widely used in classrooms and robotics clubs; Fosters hands-on learning of robotics and programming.
 Çakır et al. [23]
Lego Mindstorms NXT Versatile robotics kit using LEGO building blocks with touch, colour, and ultrasonic sensors.
  • Programmable NXT controller for precise control; Touch, colour, and ultrasonic sensors; Flexible building with LEGO blocks; Intuitive visual programming with blocks (similar to Scratch).
 Atmatzidou and Demetriadis [24]
mBot Educational robot by Makeblock, designed for computer science and STEM learning.
  • CyberPi processor, sensors, and motors; Supports Scratch (block-based programming) and Python; Versatile for add-ons like temperature sensors, gas sensors, and accelerometers.
 Voštinár [25]

References

  1. Diago, P.D.; González-Calero, J.A.; Yáñez, D.F. Exploring the development of mental rotation and computational skills in elementary students through educational robotics. Int. J. Child-Comput. Interact. 2022, 32, 100388.
  2. IFR. IFR Presents World Robotics Report 2022, Automation. 2022. Available online: https://www.automation.com/en-us/articles/october-2022/ifr-presents-world-robotics-report-2022 (accessed on 11 July 2023).
  3. Mead, R.A.; Thomas, S.L.; Weinberg, J.B. From grade school to grad school: An integrated STEM pipeline model through robotics. In Robots in K-12 Education: A New Technology for Learning; IGI Global: Hershey, PA, USA, 2012; pp. 302–325.
  4. Tedre, M.; Denning, P.J. The long quest for computational thinking. In Proceedings of the 16th Koli Calling International Conference on Computing Education Research, Koli, Finland, 24–27 November 2016; pp. 120–129.
  5. Papert, S. Mindstorms: Children, Learning and Powerful Ideas; Amazon: Bellevue, WA, USA, 1980.
  6. Denning, P.J. Remaining trouble spots with computational thinking. Commun. ACM 2017, 60, 33–39.
  7. Hamilton, M.; Clarke-Midura, J.; Shumway, J.F.; Lee, V.R. An emerging technology report on computational toys in early childhood. Technol. Knowl. Learn. 2020, 25, 213–224.
  8. Weintrop, D.; Beheshti, E.; Horn, M.; Orton, K.; Jona, K.; Trouille, L.; Wilensky, U. Defining computational thinking for mathematics and science classrooms. J. Sci. Educ. Technol. 2016, 25, 127–147.
  9. Shute, V.J.; Sun, C.; Asbell-Clarke, J. Demystifying computational thinking. Educ. Res. Rev. 2017, 22, 142–158.
  10. National Research Council. Report of a Workshop on the Scope and Nature of Computational Thinking; National Academies Press: Washington, DC, USA, 2010.
  11. Computer Science Teachers Association (CSTA) Standards Task Force. CSTA K-12 Computer Science Standards. 2011. Available online: http://c.ymcdn.com/sites/www.csteachers.org/resource/resmgr/Docs/Standards/CSTA_K-12_CSS.pdf (accessed on 11 July 2023).
  12. Robins, A.; Rountree, J.; Rountree, N. Learning and teaching programming: A review and discussion. Comput. Sci. Educ. 2003, 13, 137–172.
  13. Coll, C.; Solé, I. Os professores e a conceção construtivista. In O Construtivismo na Sala de Aula: Novas Perspetivas Para a Ação Pedagógica; Coll, C., Martín, E., Mauri, T., Miras, M., Onrubia, J., Solé, I., Zabala, A., Eds.; Edições Asa: Porto, Portugal, 2001; pp. 8–27.
  14. Pattis, R.E. A philosophy and example of CS-1 programming projects. ACM SIGCSE Bull. 1990, 22, 34–39.
  15. Janzen, D.S.; Saiedian, H. Test-driven learning: Intrinsic integration of testing into the CS/SE curriculum. ACM SIGCSE Bull. 2006, 38, 254–258.
  16. Roumani, H. Practice what you preach: Full separation of concerns in CS1/CS2. SIGCSE Bull. 2006, 38, 58–64.
  17. Rodrigues, A.M.G. Aplicação da Robótica na Resolução de Problemas: Reflexões Para a Aprendizagem Inicial de Programação no Ensino Básico. Ph.D. Thesis, Universidade de Lisboa, Lisboa, Portugal, 2020.
  18. Calderon, J.M.; Rojas, E.R.; Rodriguez, S.; Baez, H.R.; Lopez, J.A. A Robot soccer team as a strategy to develop educational initiatives. In Proceedings of the Latin American and Caribbean Conference for Engineering and Technology, Panama City, Panama, 23–25 July 2012.
  19. Benitti, F.B.V. Exploring the educational potential of robotics in schools: A systematic review. Comput. Educ. 2012, 58, 978–988.
  20. Xia, L.; Zhong, B. A systematic review on teaching and learning robotics content knowledge in K-12. Comput. Educ. 2018, 127, 267–282.
  21. Schina, D.; Esteve-Gonzalez, V.; Usart, M. Teachers’ perceptions of bee-bot robotic toy and their ability to integrate it in their teaching. In Robotics in Education: Methodologies and Technologies; Springer: Berlin/Heidelberg, Germany, 2021; pp. 121–132.
  22. 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. Early Child. Educ. J. 2013, 41, 245–255.
  23. Çakır, R.; Korkmaz, Ö.; İdil, Ö.; Erdoğmuş, F.U. The effect of robotic coding education on preschoolers’ problem solving and creative thinking skills. Think. Ski. Creat. 2021, 40, 100812.
  24. Atmatzidou, S.; Demetriadis, S. Advancing students’ computational thinking skills through educational robotics: A study on age and gender relevant differences. Robot. Auton. Syst. 2016, 75, 661–670.
  25. Voštinár, P. Using mBot robots for the motivation of studying computer science. In Proceedings of the 2020 43rd International Convention on Information, Communication and Electronic Technology (MIPRO), Opatija, Croatia, 28 September–2 October 2020; pp. 653–657.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
Upload a video for this entry
Information
Subjects: Engineering, Industrial
Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :
Rodrigo Antunes
,
Martim Lima Aguiar
,
Pedro Dinis Gaspar
View Times: 110
Revisions: 2 times (View History)
Update Date: 07 Dec 2023
Table of Contents
    1000/1000
    Hot Most Recent
    Video Production Service
    Feedback