https://scholar.korea.ac.kr/handle/2021.sw.korea/921 2026-04-13T11:43:59Z https://scholar.korea.ac.kr/handle/2021.sw.korea/264824 Title: AI·Digital Literacy for EduTech Authors: JaMee KIM 2025-01-01T00:00:00Z https://scholar.korea.ac.kr/handle/2021.sw.korea/143369 Title: Development of CNN-Based Data Crawler to Support Learning Block Programming Authors: Park, HuiJae; Kim, JaMee; Lee, WonGyu Abstract: Along with the importance of digital literacy, the need for SW(Software) education is steadily emerging. Programming education in public education targets a variety of learners from elementary school to high school. This study was conducted for the purpose of judging the proficiency of low school-age learners in programming education. To achieve the goal, a tool to collect data on the entire programming learning process was developed, and a machine learning model was implemented to judge the proficiency of learners based on the collected data. As a result of determining the proficiency of 20 learners, the model developed through this study showed an average accuracy of approximately 75%. Through the development of programming-related data collection tools and programming proficiency judging models for low school-age learners, this study is meaningful in that it presents basic data for providing learner-tailored feedback. 2022-07-01T00:00:00Z https://scholar.korea.ac.kr/handle/2021.sw.korea/141769 Title: Impacts of Learning Orientation on the Modeling of Programming Using Feature Selection and XGBOOST: A Gender-Focused Analysis Authors: Woo, HoSung; Kim, Ja-Mee Abstract: In programming, modeling is a generalized explanatory system that organizes key characteristics of a specific matter or object of interest using computer science concepts. Modeling is integral for both automation design in programming education and communication in the collaborative process. This study investigates the effect of learning orientation on the modeling stage based on gender. The study includes 756 male and 688 female elementary-school students. We analyzed the results of XGBOOST by extracting the influential characteristics from feature selection along with the basic statistics. As a result of the study, it was confirmed that learners, regardless of gender, had the largest gap in modeling and that this was the stage at which differences occurred in programming education. For male students, the process of collecting data for modeling or devising a solution was found to be an important learning method. This shows that it is necessary to create an environment to focus on activities that derive solutions from the collected data along with strengthening information retrieval education. Although female students showed a similar tendency to male students, the process of cooperating with friends as a differentiating factor was found to be an important learning method. It seems necessary to apply teaching and learning methods that can strengthen team projects that can collaborate with friends. The findings could serve as a reference for teaching and learning design and operation for effective programming education. 2022-05-01T00:00:00Z https://scholar.korea.ac.kr/handle/2021.sw.korea/142419 Title: 인공지능 기술 딜레마를 기반으로 한 인공지능 윤리 교육에 대한 소고 Authors: 김자미; 김용 Abstract: 인공지능 기술이 사회 전반의 패러다임을 주도하는 가운데, 교육의 관점에서 인공지능에 대해 어느 수준까지 이해가 필요한 것인지에 대한 논의는 명확하지 않은 상황이다. 이에 본 연구는 인공지능 기술이나 기초지식이 부족한 상태에서도 인공지능 윤리에 대한 이해가 충분할 수 있는지를 확인하기 위한 목적으로 진행되었다. 목적 달성을 위해 인공지능 기초지식을 습득한 집단 18명과 기초지식이 부족한 집단 16명을 대상으로 인공지능 윤리와 관련된 다양한 딜레마를 중심으로 교육을 진행하였다. 연구 결과, 인공지능 기술에 대한 기초지식이 부족한 경우에는 인공지능 윤리와 관련된 다양한 논의를 이해하는 데 어려움이 있는 것으로 분석되었다. 또한, 인공지능 자체에 대한 이해가 미비한 상태에서는 인공지능과 관련하여 파생 가능한 문제에 대한 접근이나 이해가 부족한 것으로 나타났다. 본 연구는 인공지능 교육을 진행하는 데 있어서 우선되어야 하는 것은 기술에 대한 이해라는 점을 확인했다는 데 의의가 있다. 2022-01-01T00:00:00Z