Assessing a Didactic Sequence for Computational Thinking Development in Early Education Using Educational Robots

Question

1. What is computational thinking?

2. How does computational thinking impact mathematical thinking in kindergarten-aged children?

3. What is the connection between computational thinking (CT) and creativity in contemporary learners?

4. How does elaboration level affect success rate?

Accepted Answer

Computational thinking (CT) is a term that encompasses the notion of using programmatic or algorithmic thinking to produce an appropriate output to a given input. Originally introduced as algorithmic thinking in the 1950s, CT involves the application of decomposition strategies, algorithm design, abstraction, and logical reasoning, drawing upon the fundamental principles of computer science. In 2006, Wing expanded on the definition of CT, defining it as an approach to problem-solving. This definition has gained widespread acceptance, but its broad nature has also led to the demand for a more specific definition in the context of CT Education. CT has emerged as a significant educational milestone, encompassing a set of skills and competencies that are accessible to all individuals. Its importance has been further accentuated by the integrative perspective known as STEM, which emphasizes the integration of science, technology, engineering, and mathematics in teaching and learning processes at the international level. Within this context, computational thinking assumes a central role in various educational frameworks, particularly in preschool and primary school settings. For example, the Spanish preschool education curriculum has recently incorporated CT, acknowledging the need for sequential programming and instruction-based problem-solving in both analogue and digital tasks, thereby fostering the development of fundamental computational thinking skills.

Accepted Answer

The connection between computational thinking (CT) and mathematical thinking (MT) has been widely studied, but less attention has been given to the kindergarten ages of 4 and 5 years old. Previous studies have explored the integration of CT and MT in mathematics education research. Wan-Rou et al. found that CT helps to develop mathematical concepts using software or programming, while MT improves problem-solving skills in CT, with or without programming. The reciprocal relationship between CT and MT embeds CT into mathematics learning and enhances MT performance in debugging and reflection. Lockwood addressed challenges in counting problems and emphasized interventions to enhance understanding and problem type differentiation. Undergraduate students' comprehension of outcome sets improved through Python programming, reinforcing conceptual understanding of combinatorial problem types. Zhihao et al. used problem-based learning to design programming-based tasks for middle school students, co-developing CT and mathematical thinking across four mathematics domains. Tasks integrated various CT concepts and practices, promoting the application and generation of mathematical knowledge. De Chenne investigated challenges in counting problems and proposed interventions focusing on sets of outcomes. Tasks involving computer code enumeration fostered meaningful connections between counting processes and sets of outcomes, leveraging structure and connecting representations. Ye et al. reviewed the integration of CT in K-12 mathematics education, highlighting the need for clearer explanations of how CT supports mathematics learning. Geometry programming and student-centered instructional approaches were found to facilitate productive learning in CT and mathematics. CT-based mathematics learning involves a cyclical process of mathematical and computational reasoning, encompassing the construction of CT artefacts, interpretation of CT outputs, and generation of new mathematical knowledge. These studies contribute to understanding the integration of CT and MT in mathematics education, providing recommendations for effective task design and highlighting the cyclical nature of reasoning mathematically and computationally.

Accepted Answer

The research in [3] establishes a connection between CT and creativity as essential skills for contemporary learners. The findings indicate a geographic bias, with a dominance of research from the United States and a prominence of studies conducted in developed European countries. Additionally, there has been a focus on secondary education and STEM-related disciplines, which highlights the need to implement CT across other educational levels. The study emphasizes the benefits of bridging the gap between CT and creativity, as creativity is a cognitive ability that enables innovative problem-solving and the creation of original and valuable products. This connection between CT and creativity is crucial for developing well-rounded learners who can thrive in a rapidly evolving technological landscape.

Accepted Answer

The study aims to investigate the relationship between students' elaboration levels and their success rates in completing various activities. By analyzing this relationship, the researchers can determine if there is a correlation between the level of elaboration of the number sequence and the success rate in solving tasks with the CT-oriented didactic sequence. This understanding can help in designing more effective educational programs that cater to students' individual needs and learning styles. Additionally, it can provide insights into the effectiveness of different counting strategies, such as 'counting all' and 'counting on', in promoting mathematical problem-solving skills among young students. Overall, exploring the impact of elaboration level on success rates can contribute to the development of more targeted and efficient teaching methods in early education.

Accepted Answer

The acquisition of the number sequence consists of two overlapping phases. The first phase is the acquisition phase, where children learn to recite the sequence in the conventional order. The second phase, known as the elaboration phase, involves a deeper understanding of the sequence, including the construction of equivalence and order relations, as well as the ability to produce the sequence in more fluid and complex ways. This phase allows for a more comprehensive grasp of the number sequence beyond rote memorization. The acquisition phase itself can be divided into three milestones, with the first milestone being the memorization of number words that cannot be generated algorithmically. This initial phase sets the foundation for the subsequent elaboration phase, where children develop a more nuanced understanding of the number sequence.

Accepted Answer

The three parts in children's recitation of the sequence are an initial part, stable and correct, which adjusts to the conventional sequence; a second part, stable and incorrect, which does not follow the conventional order but is consistently repeated by the subject throughout different recitations; and a final part that is together incorrect and unstable. These parts are identified by Fuson [20] during the acquisition phase of learning the rules for generating new numbers by combining tens and units.

Accepted Answer

The five levels of elaboration of the number sequence are: 1. String Level: Students between 2-3 years old confuse number-words and numerals, see the sequence as a unidirectional whole structure, and are unable to count yet. 2. Unbreakable List Level: Students between 3-4 years old establish a one-to-one correspondence between objects and numbers, can recite the sequence forwards, but cannot recite it backwards. 3. Fragmentary Chain Level: Students between 3-5 years old can recite the sequence without starting at 1, count intervals, and tell which number comes before or after a given one. 4. Numerable Chain Level: Students between 6-7 years old understand that words can be converted into countable elements, recite fragments of the sequence, and perform cognitive operations like double counting. 5. Bidirectional Chain Level: Students from the beginning of primary education (6 years and above) can count correctly in increasing and decreasing order, showing flexibility and mastery of numerals. These levels represent the progression of a child's understanding and manipulation of the number sequence, leading to the development of counting skills and the ability to solve mathematical tasks in different contexts.

Accepted Answer

Phase 1 of acquisition of addition involves students solving simple additive problems using informal strategies for counting, without explicit instruction. This phase allows students to find solutions by counting, even without understanding written number representation. Students can use their fingers as an external tool to keep track of their count. This phase has limitations, such as representing large numbers or double counting, which can be circumvented by using fingers. The literature suggests that fingers play a functional role in numerical development and serve as a procedural tool for mathematical cognition. Teachers need to be aware of the different demands and requirements of counting strategies, such as 'counting all' and 'counting on', based on the level of elaboration of the number sequence.

Accepted Answer

The three types of paradigms in robotics-based learning are Learning robotics, Learning with robotics, and Learning by robotics. Learning robotics focuses on using a robot as a platform to learn robotics, emphasizing engineering components such as electronics and programming through hands-on and collaborative methods. Learning with robotics involves accepting robots as a complement and part of learning, encompassing physical, cultural, behavioral, functional, social, and representational domains. Learning by robotics utilizes robots as tools to achieve curricular objectives, work on student-robot projects, and explore real-world problems, with robotic kits made up of mechanical and electronic elements controlled by specific instructions. These paradigms aim to enhance mathematical problem-solving skills and develop CT abilities in preschool education.

Accepted Answer

Bee-Bot robots move with precision in 15 cm steps, rotate in 90 degrees turns, and can remember up to 200 steps. They are programmable through a button-based interface, allowing users to replicate sequences of movements. These robots serve as educational tools, enabling children to engage with and manipulate the robot to navigate a grid with different goals. The robots are used in activities that involve reaching objects and solving pre-operational strategies for sums, providing a hands-on learning experience.

Accepted Answer

The complexity of didactic sequence design plays a crucial role in enhancing learning outcomes. By gradually increasing the complexity of tasks, students are challenged to apply their knowledge and skills in a progressive manner. In the provided section, the study focuses on designing a didactic sequence with increasing complexity through three main challenges. The first challenge involves programming a robot to find objects in a grid, with the complexity measured by the number of objects, turns, and keys required. The subsequent challenges, activities 4 and 5, introduce counting strategies using marbles, with the complexity determined by the number of marbles and the counting strategy employed. This progressive increase in complexity allows students to build upon their previous knowledge and skills, promoting deeper understanding and mastery of the concepts. Additionally, the variation in the number of marbles provided to each student prevents them from relying on their peers' results, encouraging independent thinking and problem-solving. Overall, the carefully designed complexity in the didactic sequence design facilitates effective learning and skill development.

Accepted Answer

The study focused on children aged 4 to 5 years old. This age range was chosen to capture the developmental stage where children are typically immersed in the early education curriculum and actively engaged in the learning process. The selection aimed to ensure a diverse sample, although the gender representation was not balanced. A sample size of 16 participants was deemed suitable for the research scope, and convenience sampling was utilized as the selection criterion. The tutors in the classroom specifically chose students who had no prior experience with educational robots.

Accepted Answer

The study assessed the level of elaboration in the number sequence to understand its relationship with task success. Participants were evaluated individually, and their performance in the proposed activities was measured by reporting success or failure. The educational robot was operated by one student at a time, ensuring that the data collected was specific to each participant's actions and thought processes. This approach aimed to provide a detailed understanding of the participants' problem-solving abilities and their utilization of computational thinking skills in the context of the number sequence elaboration. By analyzing the correlation between elaboration level and task success, the study aimed to shed light on the effectiveness of different levels of elaboration in achieving successful outcomes in the designed tasks.

Accepted Answer

The success rate in object finding activities shows a decreasing trend as the activity number increases. Feminine students performed worse in more complex activities, specifically activity number three. The regular trend is observed in Figure 4, indicating a decrease in success along the activity number. This trend aligns with the expected difficulty level of the tasks and the students' ability to find objects in the regular grid. The results suggest that as the complexity of the tasks increases, students may face challenges in successfully completing them. This trend highlights the importance of considering the difficulty level and progression of tasks in educational settings to ensure optimal learning outcomes.

Assessing a Didactic Sequence for Computational Thinking Development in Early Education Using Educational Robots

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Most frequently asked questions

1. What is computational thinking?

2. How does computational thinking impact mathematical thinking in kindergarten-aged children?

3. What is the connection between computational thinking (CT) and creativity in contemporary learners?

4. How does elaboration level affect success rate?

5. What are the two distinct phases in the acquisition of the number sequence?

6. What are the three parts in children's recitation of the sequence?

7. What are the characteristics of the five levels of elaboration of the number sequence?

8. What is phase 1 of acquisition of addition?

9. What are the three types of paradigms in robotics-based learning?

10. How do Bee-Bot robots move?

11. How does the complexity of didactic sequence design impact learning?

12. What age range did the study focus on?

13. How does elaboration level relate to task success?

14. What is the success rate trend in object finding activities?

Citations

Habilidades del Pensamiento Computacional y la Robótica Educativa en Estudiantes de Educación Inicial y Básica: Una Revisión Sistemática Desde la Literatura

Synergizing Systems Thinking and Technology-Enhanced Learning for Sustainable Education Using the Flow Theory Framework

References

Computational thinking

Computational Thinking in K–12 A Review of the State of the Field

Children's Counting and Concepts of Number

The discrimination of visual number.

Advancing students' computational thinking skills through educational robotics

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