A Study on Software Education Using Physical Computing to Increase Computational Thinking in Elementary School Students

Ⅰ. Introduction

Today, we live in a knowledge and information society in which new technologies and digital environments are developing rapidly and rapidly changing. Terms such as artificial intelligence (AI), Internet of Things (IoT), big data, drones, 3D printers, autonomous vehicles, and virtual reality (VR), which are representative technologies of the 4th industrial revolution, have become part of our daily lives. In this era of the 4th industrial revolution, interest in cutting-edge science and technology and software education to cope with changes in future jobs and lives has increased. According to a study on software education teaching and learning model development, the knowledge information society is moving from the first IT revolution centered on infrastructure and hardware to the second IT revolution centered on software and content based on creative IT talent. To the extent that software is expressed as “Software is eating the world” and “Software is everywhere”, the impact on almost all industries such as the automobile industry, aviation industry, financial industry, and shopping industry is enormous [1].

As software becomes a software-centered society that determines the competitiveness of individuals, companies, and governments, major countries around the world are pursuing national strategies to actively respond to these changes[2]. In major developed countries, software education is provided from the lower grades of elementary school to develop learners' computational thinking(CT) skills, and the software is actively used to achieve sustainable growth of the national economy and solve social problems. Therefore, in Korea, it is required to prepare a foundation for a curriculum so that all students can be provided with software education opportunities that are suitable for their abilities and aptitudes[1]. It is necessary to think about what kind of education the learners who will live in the changing times should receive and what kind of education should be provided to nurture them into creative convergence talents demanded by our society. In this regard, the 2015 revised information department emphasized CT as a core competency pursued in software education. To understand and build a concrete and practical solution, it is necessary to devise an algorithm and make it a reality through programming[3].

In this study, by comparing elementary school A, which took coding classes using educational programming language(EPL) and physical computing, and elementary school B, which took coding classes using only EPL, for 3rd and 4th graders who applied for coding classes after school at elementary school, we studied whether it helps to improve the class patterns and CT. After-school education can design a software curriculum that meets the needs of students and their parents in a variety of subjects and methods without being bound by the curriculum[4]. Therefore, students' opinions were reflected or students decided on their own topics so that they could actively participate in the class. In addition, among SW education teaching and learning models for CT enhancement, we designed a software class using physical computing, focusing on the demonstration-centered model (DMM model) and the reconstruction-oriented model (UMC model), and examined the appearance in the class. The results of the analysis on the effect on the CT of elementary school students are presented after analyzing the Beaver challenge problem for the evaluation of CT before and after class, and the CT test of Codemos in the last session.

Ⅱ. Related Studies

2-2 Software education and physical computing

According to the official blog of the Ministry of Education, software education is defined as education that develops CT to solve various problems creatively and efficiently based on the basic concepts and principles of computer science. The purpose of software education is to expand the perspective of ICT literacy and utilization education performed in the existing ICT education, and it is defined as the purpose of cultivating the ability of learners to solve problems based on CT skills necessary for living in the future society and software education in elementary and middle schools focuses on solving real-life problems through CT based on information ethics awareness and attitude rather than program development competency[1].

In Korea, 17 hours were allocated for practical subjects in elementary school, and 34 hours were allocated to middle school students in grades 1 to 3. Since the grade in which software education started is relatively late compared to other countries, and 34 hours are operated in any grade for three years of middle school, there may be a disconnection between grades and school level[6]. As a result, it is a situation that is significantly lacking compared to other countries, and it is identified as a situation in which solutions and countermeasures need to be prepared.

Physical computing refers to downloading data in the real world to a digital device, processing it in the form of software, and outputting the result to a monitor, LED, or other devices. Physical computing, which has the characteristics of exchanging information between the virtual world and the real world, becomes the basis of the IOT field that recognizes the surrounding environment and processes necessary information. It is expected that it will play an important role in the software industry in the future thanks to being able to go. The use of physical computing tools can achieve the achievement standards of the curriculum, maintain learners' interest, improve CT, and provide experience and competency as a future maker, is expected to increase the likelihood that it will be used as a tool for learners' active attitude change[7]. The various tool types used in physical computing education are classified and analyzed into robot type, modular type, board type, and sensor type as in table 1[8].

Table 1.

Tools using for physical computing

2-3 Software education teaching and learning models to improve CT Skills

Studies related to teaching and learning design focusing on CT have been conducted in a variety of ways, and according to the SW education teaching and learning model development study[1], the model for enhancing CT has been suggested. The model was developed with a focus on functional areas among the learning target areas - knowledge, skills, and attitudes, in addition to functions, behaviorism, cognitivism, and constructivism were considered. Also, a new model was developed by focusing on a model frequently dealt with in various existing teaching methods such as problem-solving learning, and reconfiguration was made possible in consideration of the characteristics of the learner and the school environment.

The developed instructional model set the basic direction of including CT components (decomposition, pattern recognition, abstraction, algorithm, programming) within step-by-step activities to achieve the goal of increasing CT, and proposed all five models that are a demonstration-oriented(DMM) model, a reconstruction-oriented(UMC) model, a development-oriented(DDD) model, a design-oriented(NDIS) model, and a CT element-oriented(DPAAP) model in that the components of CT should be the goal and basis of all learning as shown in table 2.

Table 2.

SW teaching and learning models to improve CT

Ⅲ. Research Approach and Procedure

3-3 Test tools

1) Beaver challenge

In many previous studies, the Beaver challenge has been widely used as a tool for measuring software-related core competencies. Besides, the Beaver challenge was implemented in software education through a study on the development of a tool for measuring the effectiveness of software education in 2017 conducted by the KERIS[15]. Therefore, in this study, a pre-test was conducted with the Beaver challenge problem for grades 3 and 4 in 2017, and a post-test of primary CT was conducted with the Beaver challenge problem for grades 3 and 4 in 2020. The Beaver challenge was divided into 6 groups in consideration of the age of the participants, its difficulty level and questions were different and group 2 level (primary) problems were used for grades 3 and 4. The pre-test consists of 9 items and the post-test consists of 10 items. In the difficulty level the upper level is 12 points, the middle level is 9 points, and the lower level is 6 points. The pre-test is out of 81 points and the post-test is out of 90 points.

2) CT test of Codmos

For the secondary CT post-test, it was conducted using the CT test provided by Codemos free of charge at the 'Online Coding Party 2021' hosted by the Ministry of Science and Technology, the Ministry of Education, and the Korea Foundation for Science and Creativity. Logibrothers, which provides Codemos, an elementary coding education service, collaborates with representative educational institutions such as EBS, Woongjin, and Ice Cream Homerun, and provides educational programs to major private elementary and middle schools. It is evaluated as an online solution optimized to improve CT as well as learning essential coding concepts for elementary school students, out of the framework of programming education. Based on the learning data of 1 million people, the Codemos CT pre-diagnostic evaluation, which diagnoses the five areas of CT, automation, reasoning, generalization, abstraction, and data processing, consists of 5 questions, and there is no distinction based on grade level and difficulty level.

Fig. 1.

Micro:bit front and back view

3-5 Software curriculum development

The teaching and learning process consisted of 27 sessions centered on DMM model and UMC model. At the beginning of the class, it is mainly the basic stage of programming and the function of the command block is not well understood, so the teacher explains the function and demonstrates the function, and then the students follow along and ask questions. After that, the students organize the class with a DMM model that allows free project activities according to the teacher's explanation, and uses the UMC model according to the topic and content to motivate the students to explore the learning modules learned through play, and through the modification process of the module prepared in advance, the students were able to understand the functions and concepts. Finally, by expanding the play and modification activities, it is possible to design and produce their own programs. Table 3 shows the concept of learning content for each class.

Table 3.

Learning content for each class

Ⅳ. Research Results and Evaluation

Funboard was easy to handle for young learners who are new to physical computing because the sensors are already installed on the board and can be used just by connecting it to a computer USB port. In addition, for physical computing, only the functions of the blocks and sensors that can be used were briefly explained and the class was conducted, so the class went smoothly without any difficulties without providing additional time. However, as the class progressed, it was difficult to understand the sensor because it was not possible to see the installed sensor, and since it was not possible to use other sensors attached, the expandability to various activities was disappointing.

Micro:bit has various sensors installed on the board itself and has the advantage of being able to do various activities by attaching the necessary sensors, but it was difficult for 3rd and 4th graders of elementary school to connect directly to the sensor and the board. For this reason, an expansion board that can be easily connected to the sensor was purchased separately. In addition, in order for software education using physical computing to proceed smoothly, it is important to provide teaching tools suitable for the learner's level in stages, and changes according to the learning situation must be made appropriately.

Both groups said that after-school coding classes were opened for the first time, and in a preliminary survey, they were exposed to software education for the first time. It consisted of 7 3rd graders and 8 4th graders with similar grades, respectively.

This study investigated how software education using physical computing affects the improvement of CT of elementary school students and what differences it has with EPL-based software education. Table 4 shows the results of the independent sample t-test to check the prior homogeneity of the experimental group and the control group. In the pre-test, the two groups had a t-value of -0.164 and a significance P-value of 0.871 under the assumption of equal variance, which was greater than the significance level of 0.05 and the homogeneity of the two groups was confirmed.

Table 4.

Pre-test homogeneity test

Pre-test and post-test on CT were conducted using Beaver challenge problem for 15 students in 3rd~4th grades of elementary school B, who received EPL-based software education as a control group. As shown in table 5, as a result of CT, post-test score was 51.11, which was higher in post-test compared to pre-test. To check whether the corresponding sample t-test result is statistically significant, t-value was -3.937 under the assumption of equal variance, and the value of the probability P was 0.0005, which was less than the significance level of 0.05, which was analyzed to be significant. Therefore, it is evaluated that EPL-based software education is meaningful in improving CT of elementary school B learners.

Table 5.

Control group t-test results(B school EPL class)

Pre-test and post-test of CT were conducted using Beaver challenge problem for 15 students in 3rd~4th grades of elementary school A, who were trained in software using physical computing on experimental group. As shown in table 6, post-test scored 56 points, which was higher in post-test compared to pre-test. To find out whether the corresponding sample t-test result is statistically significant, t-value is -6.173 and probability P value is 0.00000115 under the assumption of equal variance, which is less than the significance level of 0.05. It was analyzed that it had a significant effect on the change of CT. Therefore, it is evaluated that software education using physical computing is meaningful in improving CT of elementary school A students.

Table 6.

Experimental group t-test results(A school physical computing class)

Table 7 shows 1st post-test results to confirm the effect on the improvement of CT of learners in experimental group A elementary school and control group B elementary school. One of the experimental group had a higher mean than one of the control group. To find out whether the independent sample t-test result is statistically significant, t-value was -2.117 and probability P-value was 0.0433 under the assumption of equal variance, which was less than the significance level of 0.05, which was analyzed to be significant. Therefore, it is evaluated that the effect of software education using physical computing on the improvement of learners' CT is significant.

Table 7.

1st post-test t-test results of two groups

Table 8.

2nd post-test t-test results of two groups

Also, in the results of 2nd post-test Codemos CT test of the two groups conducted at the 30th class, the average of the experimental group was 1232.2 points and the average of the control group was 977.81 points, indicating that the average of the experimental group was higher. To find out whether the independent sample t-test result is statistically significant, t- value was 3.269 and probability P-value was 0.0028 under the assumption of equal variance, which was less than the significance level of 0.05, which was analyzed to be significant. Therefore, it is evaluated that the effect of software education using physical computing on the improvement of learners' CT is significant.

The purpose of this study is to investigate the effect of software education using physical computing on CT of elementary school students. However, since there are no clear standards and questions for software education using physical computing, or a credible test tool that can evaluate CT, the effect on CT indirectly was verified by using the previous questions of the Beaver challenge and CT test of Codemos. Therefore, it was not possible to directly verify the results.

It is difficult to quantitatively measure the interest of the learners in the experimental group, but when the reaction was observed, it was found that they wanted to continue their activities without going home after class. Therefore, additional time was provided using the break time, and it was composed of individual activities and paired activities of two people so that they could solve problems together. They actively participated in classes, showed a high level of interest, and did not give up even if they felt difficulties during activities and developed the program.

Ⅴ. Conclusion

In this study, to investigate the effect of software education using physical computing on the improvement of CT in elementary school students, 27 class programs were developed and practiced. The 27 classes were applied to the experimental group and the control group, respectively. In 30 classes, the improvement of CT was tested using Beaver challenge problem for 3rd~4th graders in the 1st and 29th classes of the 30 classes, and Codemos CT test and interview were conducted at the 30th class and the conclusions obtained are as follows

First, it was analyzed that software education using physical computing had a positive effect on the improvement of CT of elementary school students.

Second, it was found that it is necessary to select a physical computing tool considering the age of the learner, and effective software education can be achieved when it is provided according to the educational environment and economic situation.

Third, it was observed that learners were more interested in software education using physical computing and tended to actively participate in class.

Taken together, it can be said that the improvement of elementary school students' CT is more effective when getting software education using physical computing than when doing it using only EPL.

As for the effectiveness verification, the study is conducted for a limited period of time with limited content, group, and so there are limitations to generalize the results of the study to elementary school students nationwide. In addition, there is a limit to generalizing the results of the study as an effect because various variables such as the study period, various teaching and learning methods, teacher variables, and environmental variables were not taken into account. Therefore, for follow-up studies, it is necessary to study the implementation of software education using physical computing in consideration of various variables, to select a more extensive research area and subject, and to follow up with a longer-term and systematic study.

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