Technological development has facilitated the use of robots to advance learning. According to Burbaite, Bespalova, Damasevicius, and Stuikys (2014), robots motivate students, encourage engagement, and enable them to acquire practical skills. Robots are effective in delivering large skill sets to learners. Burbaite et al. (2014) say, “The positive effect is gained from the “embodiment” and physical presence of robots, which make the outcomes of programming very vivid and immediately accessible” (p. 931).
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Today, many institutions are moving away from the conventional methods of teaching and adopting robotic activities to augment learning. Currently, the most significant development in the field of computer science is the inclusion of robots as teaching tools. Initially, most computer science departments used robots as a strategy to increase the number of learners in computer science courses. Nevertheless, with time, educators realized that robots could be important teaching instruments. That is when they decided to look for ways to integrate the technology into learning activities. This paper will discuss the strategy for using robots in teaching computer science.
Use of Robots
In the United States, many higher education institutions have realized the importance of collaborative learning and practical exercise in computer science. Most lecturers argue that engaging students in classes enable them to remember what they learn (Berenguel, Rodriguez, Moreno, Guzman, & Gonzalez, 2016). Collaborative learning and hands-on exercises allow learners to internalize what is being taught. Consequently, most institutions have implemented collaborative learning as a means to integrate robots into the field of computer science. Educational theorists agree that robots have enormous power to improve classroom teaching (Berenguel et al., 2016).
According to Berenguel et al. (2016), one of the significant values of robots in computer science is their concrete nature. The use of robots in teaching computer science has significantly helped to endow students with valuable skills in this field. In the past, it was difficult for learners to comprehend theoretical ideas. Toh, Causo, Tzuo, Chen, and Yeo (2016) assert, “Today, students can understand abstract concepts and gain a more functional level of understanding when they learn with robots” (p. 152).
Nonetheless, Toh et al. (2016) stress that teachers must regard robots as one of the teaching materials. The use of robots alone cannot help to boost learning amid computer science students. The educational theory that instructors apply plays a significant role in determining the success of robot application.
Robots enable educators to use activities that are helpful in teaching different disciplines including mathematics, technology, and computer science. In the field of computer science, instructors have formulated practical activities with essential experimentation aspects to aid in teaching (Shiomi, Kanda, Howley, Hayashi, & Hagita, 2015). These activities aid lecturers to apply robots to create a dynamic, collaborative learning atmosphere that encourages students’ participation. Indeed, integration of robotic technology into the field of computer science has augmented teaching practices. Teachers can now use inventive methods to meet diverse learning objectives (Shiomi et al., 2015).
Research shows that robots are connected to multiple disciplines. According to Shiomi et al. (2015), a robot comprises different components. They include software, sensors, and motors. Each of these components is manufactured using knowledge from disciplines such as computer science, electronics, and engineering. Therefore, using robots to teach computer science students has an added advantage. Learners get an opportunity to acquire skills in other disciplines that are connected to robotics.
Universities are coming up with frameworks to facilitate the use of robots to teach different subjects. For instance, in the United States, Carnegie Mellon University has developed an open source robot program dubbed Tekkotsu to facilitate teaching (Zaharija, Mladenovic, & Boljat, 2015). This application is developed based on C++ programming language (Zaharija et al., 2015). Zaharija et al. (2015) allege that Tekkotsu has been helpful in teaching mathematics topics like linear algebra, matrices, and vectors. In Brazil, some tertiary institutions use robots to teach physics (Zaharija et al., 2015).
The organizations have created model robots, which they use to teach electronics and electricity, especially showing learners how to assemble electrical circuits. In the field of computer science, robots have been useful, particularly in programming courses (Zaharija et al., 2015). For example, the University of Waterloo has a robot called Karel, which is used to teach Java programming (Zaharija et al., 2015). The university has developed an Introductory to Computer Science syllabus, which utilizes a robot to train learners in object-oriented programming.
Technological growth has enabled instructors to use robots to improve learning environment and encourage student participation. Today, robots are used to teach subjects like mathematics and physics. The field of computer science has greatly benefited from robots. Initially, computer science departments used robots as incentives to encourage many learners to register for their courses. Later, they realized that these tools were helpful in boosting learning.
Today, the field of computer science has devised mechanisms to facilitate the use of robots to equip learners with different skill sets. The use of practical exercises and collaborative learning has enabled computer science departments to include robot as an essential teaching instrument. Robots help students to comprehend abstract concepts. Moreover, interacting with robots gives learners a chance to gain skills in other disciplines.
Berenguel, M., Rodriguez, F., Moreno, J. C., Guzman, J. L., & Gonzalez, R. (2016). Tools and methodologies for teaching robotics in computer science & engineering studies. Computer Applications in Engineering Education, 24(2), 202-214.
Burbaite, R., Bespalova, K., Damasevicius, R., & Stuikys, V. (2014). Context-aware generative learning objects for teaching computer science. International Journal of Engineering Education, 30(4), 929-936.
Shiomi, M., Kanda, T., Howley, I., Hayashi, K., & Hagita, N. (2015). Can social robot stimulate science curiosity in classroom? International Journal of Social Robotics, 7(5), 641-652.
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Toh, L. P. E., Causo, A., Tzuo, P., Chen, I., & Yeo, S. H. (2016). A review of the use of robots in education and young children. Journal of Educational Technology & Society, 19(2), 148-163.
Zaharija, G., Mladenovic, S., & Boljat, I. (2015). Use of robots and tangible programming for informal computer science introduction. Procedia – Social and behavioral Sciences, 174(1), 3878-3884.