Fostering computational thinking through educational robotics: a model for creative computational problem solving

Abstract

Background: Educational robotics (ER) is increasingly used in classrooms to implement activities aimed at fostering the development of students' computational thinking (CT) skills. Though previous works have proposed different models and frameworks to describe the underlying concepts of CT, very few have discussed how ER activities should be implemented in classrooms to effectively foster CT skill development. Particularly, there is a lack of operational frameworks, supporting teachers in the design, implementation, and assessment of ER activities aimed at CT skill development. The current study therefore presents a model that allows teachers to identify relevant CT concepts for different phases of ER activities and aims at helping them to appropriately plan instructional interventions. As an experimental validation, the proposed model was used to design and analyze an ER activity aimed at overcoming a problem that is often observed in classrooms: the trial-and-error loop, i.e., an overinvestment in programming with respect to other tasks related to problem-solving. Results: Two groups of primary school students participated in an ER activity using the educational robot Thymio. While one group completed the task without any imposed constraints, the other was subjected to an instructional intervention developed based on the proposed model. The results suggest that (i) a non-instructional approach for educational robotics activities (i.e., unlimited access to the programming interface) promotes a trial-and-error behavior; (ii) a scheduled blocking of the programming interface fosters cognitive processes related to problem understanding, idea generation, and solution formulation; (iii) progressively adjusting the blocking of the programming interface can help students in building a well-settled strategy to approach educational robotics problems and may represent an effective way to provide scaffolding. Conclusions: The findings of this study provide initial evidence on the need for specific instructional interventions on ER activities, illustrating how teachers could use the proposed model to design ER activities aimed at CT skill development. However, future work should investigate whether teachers can effectively take advantage of the model for their teaching activities. Moreover, other intervention hypotheses have to be explored and tested in order to demonstrate a broader validity of the model.

On Computational Thinking and STEM Education

“…CT development should not be limited to acquiring programming skills, but more on problem solving through computational means. Thus, some researchers proposed alternative approaches to develop problem-solving-oriented CT such as, "systematic CT" (Michaelson 2018) and "creative computational problem solving" (Chevalier et al 2020). For example, Chevalier et al (2020) took the view of CT development using a robot as more about the problem-solving process than just programming the robot to solve the problem.…”

“…Thus, some researchers proposed alternative approaches to develop problem-solving-oriented CT such as, "systematic CT" (Michaelson 2018) and "creative computational problem solving" (Chevalier et al 2020). For example, Chevalier et al (2020) took the view of CT development using a robot as more about the problem-solving process than just programming the robot to solve the problem. They proposed a creative computational problem solving model for teaching CT. With this model, they conducted an experimental study with elementary school students using an educational robot and a programming interface.…”

Educational Robotics and Robot Creativity: An Interdisciplinary Dialogue

“…The process of a robot's design is followed by an iterative, trialand-error phase of programming the robot's moves, testing, and modifying its design and software code (Nemiro et al, 2017;Alves-Oliveira, 2020;Chevalier et al, 2020). In the later cycles of the process of creation of the robotic model, students move beyond a trial-and-error method and start developing their Frontiers in Robotics and AI | www.frontiersin.org own heuristic approach, which allows them to come up with original technical solutions (Hayes, 1978;Altshuller, 1988;Sullivan and Lin, 2012;Sullivan, 2017).…”

“…One may suppose that the practice of alternating between two different modes of cognition, generative and explorative, coupled with implicit and metacognitive processes that work in parallel, could result in better coordination between these components and promote student’s cognitive flexibility. Recent instructional models for teaching creativity via educational robotics also underscore the role of generative, explorative, and meta-components ( Chevalier et al, 2020 ; Yang et al, 2020 ). Another possible explanation that can account for the promotion of student’s creative potential by robotics programs is that the process of engaging in collaborative construction of robotic devices leads not only to novel physical artifacts but also to the emergence of new mental tools–implicit and meta ideational strategies.…”

Formation of computational thinking skills in the development of computer games for educational purposes

“…Вычислительное мышление, согласно Е. К. Хеннеру, включает умственную деятельность при формулировании проблемы для принятия вычислительного решения [4]. M. Chevalier, C. Giang, A. Piatti, F. Mondada развивают эту идею и дополняют, что решение при этом может быть выполнено человеком или машиной, или, в более общем смысле, комбинацией людей и машин [15].…”