[논문]The Study on Direction of the Software Education - focused on the freshman students of the College of Social Sciences -

Han, Oakyoung; Kim, Jaehyoun

doi:10.7472/jksii.2020.21.4.69

[국내논문] The Study on Direction of the Software Education - focused on the freshman students of the College of Social Sciences - 원문보기

Journal of Internet Computing and Services = 인터넷정보학회논문지, v.21 no.4, 2020년, pp.69 - 76

Han, Oakyoung (University College, Sungkyunkwan University) , Kim, Jaehyoun (Dept. of Computer Education, Sungkyunkwan University)

Abstract ▼ AI-Helper

This paper presents direction for efficient software education. Due to the impact of the Fourth Industrial Revolution, the whole world is interested in software education. However, simply teaching how to code is not software education. The thinking abilities used in coding for software implementation are even more important. Therefore, computational thinking is getting great attention. Several institutions suggest factors for computational thinking and encourage to teach in a relevant way based on the suggestion. In this study, the verification of the factors they suggested was conducted through a questionnaire. The total of 419 freshman students of the College of Social Sciences who were taking "Computational Thinking and Software Coding" class participated in the survey at the beginning and the end of the semester. We first analyzed Wing's proposal that summarized the concept of computational thinking, and reviewed the proposal of ISTE (International Society for Technology in Education) for defining computational thinking factors for coding education, also checked on the suggestion of Google for factors necessary for software coding. As a result of research analysis, this paper suggests a direction for efficient software education.

Keyword

표/그림 (10)

그림 (Figure 1) 5-point Likert Scale of CT
그림 (Figure 2) Heat map for Wing’s Suggestion
표 (Table 1) Ratio of Improvement
그림 (Figure 3) Cluster map for Wing's Suggestion
그림 (Figure 4) Heat map for ISTE's Suggestion
그림 (Figure 5) Cluster map for ISTE's Suggestion
그림 (Figure 6) Heat map for Google's Suggestion
그림 (Figure 7) Cluster map for Google's Suggestion
그림 (Figure 8) Heat map for Result
그림 (Figure 9) Cluster map for Result

AI 본문요약
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문제 정의

The questionnaire was conducted for the students of the social sciences college in order to analyze the level of computational thinking. The lowest score among 20 factors was the reformulating at the beginning of the semester, while the lowest score was the parallelism after the semester.
The purpose of this paper is to make a guideline how to provide efficient software education to educate students preparing for the 4^th industrial revolution.

제안 방법

For this study, a survey was conducted on 574 students at the beginning of the semester and 419 students at the end of the semester from the College of Social Sciences, freshman students of the University located in Seoul. To measure the improvement of computational thinking, the surveys were conducted twice, at the beginning of the semester and the end of the semester.
The questionnaire after the semester was divided into two and analyzed. The scores were analyzed by classifying students with positive cognition about the class and those who with negative cognition. The gray bar graph shows the computational thinking scores of students with positive cognition while the orange bar graph shows for negative cognition.
To analyze the result of this study, we applied computational thinking as an independent variable and classified three dependent variables which are CD, PS, and CR. CD stands for coding which is software development skill, PS stands for problem solving, and CR is creative thinking.
It is necessary to extend this research to analyze the characteristics of each major fields of students and suggest ways to strengthen the computational thinking for each case.

대상 데이터

For this study, a survey was conducted on 574 students at the beginning of the semester and 419 students at the end of the semester from the College of Social Sciences, freshman students of the University located in Seoul. To measure the improvement of computational thinking, the surveys were conducted twice, at the beginning of the semester and the end of the semester.

데이터처리

Ten factors of computational thinking from the survey factors were extracted from the study of Professor Wing. To analyze these factors, correlation analysis was applied to evaluate the strength of relationship among these factors. Python packages of pandas, matplotlib, and seaborn were used in jupyter lab.

참고문헌 (11)

K. Kim, "Domestic Research Trends and Cases of University Education and Operation in the Era of the Fourth Industrial Revolution", Journal of Digital Convergence, Vol. 17, No. 8, pp. 15-26, 2019. https://doi.org/10.14400/JDC.2019.17.8.015
J. Kim, "Effect of Computational Thinking on Problem Solving Process in SW Education for non-CS Major Student", Journal of Korea Multimedia Society, Vol. 22, No. 4, pp. 472-479, 2019. https://doi.org/10.9717/kmms.2019.22.4.472
O. Han and J. Kim, "Examining the relationship between educational effectiveness and computational thinking in smart learning environment", Journal of Internet Computing and Services, Vol. 19, No. 2, pp. 57-67, 2018. http://dx.doi.org/10.7472/jksii.2018.19.2.57

원문보기 상세보기
O. Han and J. Kim, "Correlation Analysis of Factors of Computational Thinking", The 14th Asia Pacific International Conference on Information Science and Technology, 2019. http://http://www.apicist.org/2019/
M. Chung and J. Kim, "The Internet Information and Technology Research Directions based on the Fourth Industrial Revolution", KSII Transactions on Internet and Information Systems, Vol. 10, No. 3, pp. 1311-1320, 2016. http://dx.doi.org/10.3837/tiis.2016.03.020

원문보기 상세보기
S. Ham, "Attitudes and Performance of Workers Preparing for the Fourth Industrial Revolution", KSII Transactions on Internet and Information Systems, Vol. 12, No. 8, pp. 4038-4056, 2018. http://dx.doi.org/10.3837/tiis.2018.08.027

원문보기 상세보기
O. Han and J. Kim, "The Study on Correlation of Cognition on Software Education with Improvement of Computational Thinking", Journal of Internet Computing and Services, Vol. 20, No. 3, pp. 93-100, 2019. http://dx.doi.org/10.7472/jksii.2019.20.3.93

원문보기 상세보기
J. Wing, "Computational thinking and thinking about computing", Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 366, No. 1881, pp. 3717-3725, 2008. https://doi.org/10.1098/rsta.2008.0118

상세보기
ISTE, "Computational Thinking: teacher resources second edition", The International Society for Technology in Education, pp. 1-69, 2011. https://id.iste.org/docs/ct-documents/ct-teacher-resources_2ed-pdf.pdf?sfvrsn2
Google, "What is computational thinking?". https://sites.google.com/site/ityear7bcc/home/computational-thinking/lesson-1-computational-thinking
J. Kwon and J. Kim, "A Study on the Design and Effect of Computational Thinking and Software Education", KSII Transactions on Internet and Information Systems, Vol. 12, No. 8, pp. 4057-4071, 2018. http://dx.doi.org/10.3837/tiis.2018.08.028

원문보기 상세보기

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