AI교육을 위한 방향성에 대한 고찰

정영철,박종민,박병전 한국IT정책경영학회 2021 한국IT정책경영학회 논문지 Vol.13 No.4

As the era evolves into Digital Society, education requires to be prepared for future education. As the Ministry of Education suggests, the direction of future education requires and educational methodology in which AI education plays as core value. Accordingly, researchers and educators need to suggest approaches and altenatives for AI education. This means that SW education is on premise for research methodology. AI develops upon Big Data, and so does Big Data rely on SW developments. As such, AI has an organic correlation with interactivity. SW reveals elements or factors of typical fusion. The nature of convergence contains diversity, variableness, and multifaceted utility. In addition, convergence education is driving the birth of convergence-type talents. This study explores the corrleation between AI education and convergence education in order to suggest a AI Education methodology. Upon the research, the study approaches AI education based on inference from research hypothesis. The study emphasizes AI convergence of AI education with programming coding as study example demonstrating complementary theory of SW education. In the end, I expect AI education based on these arguments plays meaningful logical considerations for the direction of future education.

AI 융합 교육에 대한 초등교사의 인식 및 교육 요구도 분석

임은선,홍수민,임철일 한국컴퓨터교육학회 2025 컴퓨터교육학회 논문지 Vol.28 No.2

본 연구는 초등교사들이 AI 융합 교육에 대해 가지는 인식과 요구를 파악하는 것을 목적으로현직 초등교사 125명 대상의 설문조사를 실시하였다. 연구 결과, 설문에 참여한 대부분의 초등교사는 AI 융합 교육과 관련된 연수나 교육 경험은 있으나, AI 이해 교육과 활용 교육을 AI 융합 교육과 명확하게 구분하지 못함을 확인하였다. 또한 AI 융합 교육의 필요성에 대해서는대체로 동의하였으나, 교사의 역량 부족, 수업자료 제작 어려움과 같은 내적 및 기존 교과 수업의 진도 부담, 기자재 부족과 노후화와 같은 외적 방해 요인에 직면해 있는 것으로 나타났다. 또한 초등학교에서 효과적인 AI 융합 교육을 위해 AI 융합 교육에 대한 이해 향상, AI 기반 학습환경 조성 등의 요소를 고려해야 함을 확인하였다. 본 연구는 초등교사들의 AI 융합교육에 대한 인식과 요구를 기반으로 AI 융합 교육의 활성화를 위한 시사점을 논의한다. This study aims to explore elementary school teachers' perceptions and needs regarding AI-integrated education through a survey of 125 current elementary school teachers. The results show that while most teachers had experience with training or education related to AI-integrated education, many struggled to clearly distinguish between education about AI and education with AI While teachers generally agreed on the necessity of AI-integrated education, they faced internal barriers such as a lack of competence and difficulty in creating teaching materials, as well as external barriers such as the pressure to run the curriculum and outdated or insufficient equipment. Also, we identified key elements for effective AI-integrated education in elementary schools, such as improving understanding of AI-integrated education and creating an AI-based learning environment. Based on teachers' perceptions and needs, the study discusses implications for promoting AI-integrated education.

예비교원 대상 AI융합교육 교과목의 교육적 효과 분석 연구

이주영 한국정보교육학회 2024 정보교육학회논문지 Vol.28 No.4

본 연구의 목적은 예비교원의 AI융합교육 역량 향상을 위한 수업을 실행하여 그 교육적 효과를 분석하는 것이 다. AI융합교육 역량 함양을 위해 AI이해, AI교육 분류와 개념, 교과 기반 AI융합교육 사례 및 실습, AI융합교육 플랫폼 이해, AI융합교육 교수 학습 사례 구안 및 적용 등을 경험할 수 있도록 교육 내용 설계하였다. 교과목은 G 교육대학교 4학년 재학생 26명을 대상으로 11주 동안 이론과 실습을 통해 적용하고, 사전 사후 대응표본 t-test를 통해 예비교원의 AI융합교육 역량 변화와 만족도를 확인하였다. 수업에 참여한 초등 예비교원들의 AI융합교육 역 량 및 하위 요인에서 유의미한 차이를 확인하였고 만족도 또한 높은 수준으로 나타났다. 본 연구에서 설계·수행한 AI융합교육 교과목을 통해 예비교원의 AI융합교육 역량 향상이라는 교육적 효과를 확인하였다. 이를 기반으로 예 비교원의 AI융합교육 역량 향상을 위한 교육 커리큘럼, 교수 학습 내용 등에 대한 방향성을 제시하였다. The purpose of this study is to conduct a class to improve preservice teachers' competence in AI convergence education and analyse its educational effectiveness. In order to develop AI convergence education competence, the course content was designed to provide experience in understanding AI, understanding AI convergence education platforms, and designing and applying AI convergence education teaching and learning cases. The course was ap- plied through theory and practice to 26 fourth-year students of G Education University for 11 weeks. The changes in AI convergence education competence and satisfaction of the pre-service teachers were checked by t-test. The AI convergence education competence and sub-factors of the pre-service elementary teachers who participated in the course were improved to a statistically significant level, and their satisfaction was also high. Based on the results, the direction of the curriculum and teaching and learning contents to improve the AI con- vergence education competence of pre-service teachers was suggested.

특수교육과 AI 활용 교육의 융합 가능성 및 효율화 방안 탐색

김현집 한국인공지능교육학회 2025 인공지능연구 논문지 Vol.6 No.1

본 연구는 특수교육 현장에서의 AI 활용 교육 현황을 분석하고, 특수교육과 AI 활용 교육의 융합 가능성을 탐색하여 효율화 방안을 제시하는 것을 목적으로 한다. 이를 위해 C교육청의 AI 교육자료 개발에 참여한 특수교사 4명을 대상으로 심층 면담을 실시하고, 주제 분석을 통해 연구 결과를 도출하였다. 연구 결과, AI 활용 교육은 교과교육, 창의적 체험활동 등 특수교육의 다양한 영역에서 적용되고 있었다. 또한, 이는 개별화된 맞춤형 학습 지원, 즉각적인 피드백 제공, 반복 학습 기회 확대 등 특수교육이 지향하는 핵심 요소를 포함하고 있어 특수교육과의 높은 융합 가능성을 보여주었다. 하지만 AI 활용 교육의 효과적인 운영을 위해 AI 교육자료 제공, 특수교육 맞춤형 연수 실시, 최신 기기와 설비를 갖춘 AI 교육 인프라 구축, 인적·제도적 지원 강화, 교육자료 공유 체계 마련, 장애 유형을 고려한 AI 교육 콘텐츠 개발 등의 개선이 필요함이 확인되었다. 본 연구는 특수교육과 AI 활용 교육의 융합 가능성을 탐색하였다는 점에서 의의가 있으며, 향후 특수교육 현장에서 AI 활용 교육을 효과적으로 정착시키기 위한 기초자료로 활용될 수 있을 것으로 기대된다. This study aims to analyze the current status of AI-integrated education in special education settings, explore the potential for integrating AI into special education, and propose optimization strategies. To achieve this, in-depth interviews were conducted with four special education teachers who participated in the development of AI educational materials by the C Office of Education, and thematic analysis was employed to derive key research findings. The results revealed that AI-integrated education is applied across various domains of special education, including subject-based instruction, creative experiential activities, and field learning. Furthermore, AI-based education showed strong potential for integration with special education, as it encompasses core elements emphasized in special education, such as personalized learning support, immediate feedback, and opportunities for repeated learning. However, for the effective implementation of AI-integrated education, several improvements are required, including the provision of AI educational materials to reduce teachers' workload, specialized training tailored to special education, the development of AI-equipped educational infrastructure, reinforcement of human and institutional support, the development of an educational resource-sharing system, and the creation of AI content that considers various disability types. This study is significant as it empirically explores AI integration into special education and is expected to serve as a foundational resource for incorporating AI-based education into special education settings.

The impact of elementary school teachers' perceptions of AI convergence education on teaching competence and effectiveness

강단희,박선주 한국인터넷정보학회 2025 인터넷정보학회논문지 Vol.26 No.6

Artificial intelligence (AI) is causing huge paradigm shifts in society, culture, and economics beyond the realm of technology. These changes are also having a profound impact on the education sector, where teachers are learning about AI-infused education and reorganizing and implementing lessons in schools in a new educational paradigm. Researchhas shown that teacher understanding and attitudes are one of the key factors when introducing new teaching methods into the classroom. Having a clear understanding and positive attitude towards AI is an essential condition for the successful adoption of AI-integrated education. In this study, 193 elementary school teachers were surveyed to collect data, and SPSS Statistics 29 was used to analyze the frequency and descriptive statistics of the main variables, and hierarchical regression analysis was used to evaluate the relationship between awareness of AI convergence education, teaching competence, and teaching effectiveness. The results of the study showed that elementary school teachers' perceptions of AI convergence education had a significant positive effect on both teaching competence and teaching effectiveness, even when controlling for background and self-development variables. Furthermore, the more active the teachers' participation in AI convergence education and related self-development, the more their teaching competence and teaching effectiveness tended to improve. This suggests that positive perceptions of AI-integrated education and participation in continuous learning may be key factors in enhancing teaching competence and educational outcomes. This study provides theoretical evidence that elementary school teachers' perceptions of AI convergence education affect their teaching quality and activation. Beyond highlighting the importance of teacher training, the findings also call for more systematic institutional support—such as integrating AI convergence modules into pre-service teacher education, establishing continuous in-service AI learning programs, and creating collaborative school–university networks to share best practices. These strategies can enhance both the policy relevance and practical impact of AI convergence education by ensuring that teachers receive sustainable and structured support for AI integration in classrooms.

AI 시대 대학생의 진로 및 취업 교육에 영향을 미치는 외부 환경요인

임진혁 한국국제교육교류학회 2026 국제교류와 융합교육 Vol.6 No.2

본 연구는 AI 시대 대학생의 진로 및 취업 교육에 영향을 미치는 외부 환경요인을 분석하고, 이에 기반한 진로교육의 방향성을 제시하는 데 목적이 있다. 이를 위해 지방 소재 K대학의 2024년부터 2026년까지 3개년 진로·취업교육 외부환경 분석 자료와 AI 기반 진로교육 사례를 종합적으로 분석하였다. 연구의 결과 정책환경, 노동시장 구조, 산업구조 변화, 기업 선발구조, 기술환경, 사회문화적 환경, 대학-산업 연계환경이 대학 진로교육에 복합적으로 영향을 미치는 주요 외부 환경요인으로 도출되었다. 특히 AI 기술 확산과 직무 중심 채용의 확대는 대학 진로교육을 기존의 정보제공 중심에서 역량 기반 교육으로 전환시키는 핵심 요인으로 작용하였다. 또한 AI 기반 면접 및 취업지원 시스템의 도입은 진로교육의 방식과 학생의 취업 준비 행동을 변화시키는 중요한 변수로 확인되었다. 이를 바탕으로 본 연구는 AI 기반 초개인화 진로교육, 산학협력 강화, 심리·정서 지원 확대, 지역 기반 취업 생태계 구축 등의 정책적·실천적 시사점을 제시하였다. 본 연구는 AI 시대 진로교육을 외부 환경요인 중심으로 재구조화하였다는 점에서 학문적 의의를 가지며, 대학 진로교육 정책 및 실무 개선에 기초자료를 제공한다. This study aims to analyze the external environmental factors influencing career education and employment preparation for among university students in the era of artificial intelligence (AI), and to propose directions for future career education. To achieve this, the study examined three years (2024–2026) of external environment analysis data related to career and employment at a local university (K University), along with case studies of AI-based career education programs. The findings indicate that key external factors include policy environment, labor market structure, industrial transformation, corporate recruitment systems, technological environment, socio-cultural context, and university-industry linkage systems. These factors interactively shape both the content and methods of career education, as well as students’ career preparation behaviors. In particular, the expansion of AI technologies and job-based recruitment has accelerated the shift from traditional information-oriented career education to competency-based (and experience-driven) education. AI-driven tools such as automated interviews and career recommendation systems are also transforming the method of education and how students prepare for employment. Based on these findings, this study suggests the need for personalized AI-based career education systems, strengthened university-industry collaboration, enhanced psychological support systems, and the development of region-based employment ecosystems. This study contributes to the literature by structurally analyzing career education in the AI era from the perspective of external environmental factors and provides practical implications for higher education policy and career support systems.

초등학교 교육과정에서의 AI 교육 방향 탐색

유성열 한국초등교육학회 2024 초등교육연구 Vol.37 No.2

이 연구의 목적은 초등학교 교육과정에서의 AI 교육 방향을 분석하여 우리 교육에서 추구하는 AI 교육의 의미를 탐색적으로 이해하는 데 있다. 이를 위해 이 연구에서는 2022 개정 초등학교 교육과정 문서 전반을 질적 내용 분석 방법을 활용하여 분석하였다. 분석 결과 초등학교 교육과정에서의 AI 교육은 AI에 대한 교육과 AI를 활용하는 교육 모두를 지향하고 있었으며 이는 교육과정 구성의 중점, 목표, 내용, 방법, 평가 등 교육과정 전반에 거쳐 두루 나타났다. 이를 바탕으로 초등학교에서의 AI 교육은 첫째, 디지털 교육과의 깊은 관련 하에 이루어지고 있으며, 둘째, 총론과 각론, 교과별 특성에 따라 AI에 대한 교육과 AI를 활용하는 교육을 다루는 비중과 방식에 있어서 차이를 보이고, 셋째, AI를 활용하는 교육에서는 특히 학생을 위한 AI에 주목하는 특성을 보인다는 점을 논의하였다. 끝으로 초등학교 교육과정에서의 AI 교육은 교과와 밀접한 관련 하에 이루어질 필요가 있으며 국가 차원에서 AI 교육과 관련한 내용을 체계화하여 제시해야 할 필요가 있음을 제언하였다. The purpose of this study is to explore the direction of AI education in the elementary school curriculum and to exploratively understand the meaning of AI education pursued in our education. To this end, in this study, the entire 2022 revised elementary school curriculum document was analyzed using qualitative content analysis methods. As a result of the analysis, AI education in the elementary school curriculum was oriented toward both education about AI and education using AI, and this was shown throughout the curriculum, including the focus, goals, content, methods, and evaluation of the curriculum structure. This direction of AI education is, first, that discussions related to AI education are taking place in a deep relationship with digital education, and second, in terms of the proportion and method of handling education on AI and education using AI according to the general theory, specific theories, and characteristics of each subject. Thirdly, it was discussed that education using AI shows the characteristic of paying particular attention to AI for students. Finally, based on these results, it was suggested that AI education in the elementary school curriculum needs to be closely related to the subject and that there is a need to systematize and present content related to AI education at the national level.

Bibliometrix 패키지를 활용한 인공지능 융합 과학교육의 연구동향 분석: 국제저명학술지를 중심으로

김나현,최재혁,손연아 학습자중심교과교육학회 2025 학습자중심교과교육연구 Vol.25 No.13

목적 본 연구는 국제저명학술지에 게재된 인공지능 융합 과학교육 연구의 동향을 분석하여, 국내 AI 융합 과학교육 연구의 방향성에대한 시사점을 제시하는 것을 목적으로 한다. 방법 이를 위하여 WoS 데이터베이스에서 AI와 과학교육 관련 논문을 수집하고, 데이터 전처리 과정을 통해 55개의 문헌을 연구대상으로 설정하여 R의 bibliometrix 패키지를 활용해 상세서지분석을 실시하였다. 결과 AI 융합 과학교육 연구는 국내외 모두 2022년 이후 급격히 증가했으며, 주요 연구 주제로 생성형 AI, 머신러닝, 학습 평가, 교사교육 등이 부각되었다. 그러나 국내 연구는 실천적 연구가 중심인 반면 비판적 사고력과 같은 AI 윤리 및 데이터 분석 연구는미흡한 것으로 나타났다. 결론 국내 AI 융합 과학교육 연구는 데이터 기반 연구와 AI 윤리 연구를 강화하고, 교사 연수 및 AI 교육 환경 개선을 통해 보다 체계적이고 실천적이며 윤리적인 방향으로 발전해야 한다. Objectives This study aims to analyze the trends of artificial intelligence (AI)-integrated science education re search published in SCI and ESCI-indexed journals and to provide implications for the direction of AI-integrated science education research in South Korea. Methods For this purpose, research articles related to AI and science education were collected from the Web of Science (WoS) database. After a data preprocessing process, 55 studies were selected for analysis. A detailed bib liometric analysis was conducted using the bibliometrix package in R. Results The study found that AI-integrated science education research has surged globally and domestically since 2022. Key research topics include generative AI, machine learning, learning assessment, and teacher education. However, while domestic studies predominantly focus on practical research, they lack sufficient attention to AI ethics and data analysis, particularly in areas such as critical thinking. Conclusions To advance AI-integrated science education research in South Korea, it is necessary to strengthen data-driven research and AI ethics studies. Additionally, efforts should be made to enhance teacher training pro grams and improve AI education environments, ensuring a more systematic, practical, and ethical approach to AI-integrated science education.

교육대학원생의 AI 가치 인식과 AI 자기효능감 군집유형에 따른 AI 활용 교육 역량 분석

박성희 사단법인 한국융합기술연구학회 2023 아시아태평양융합연구교류논문지 Vol.9 No.6

In accordance with the 2022 curriculum revision, artificial intelligence (AI) basic knowledge was included in the school curriculum, and AI education began to be introduced in the school field. Accordingly, as the role of graduate schools of education in fostering pre-service teachers and teachers is emphasized, it is time for AI-related basic research. The purpose of this study was to identify the AI value perception and AI self-efficacy cluster types of education graduate students, and to analyze the difference in AI-based education competency according to these cluster types. To this end, the results were analyzed based on the data of 155 students who faithfully responded to the questionnaire among the students of A graduate school of education located in the metropolitan area. For data analysis, cluster analysis, one-way analysis of variance (ANOVA), and multivariate analysis of variance (MANOVA) were conducted with AI value perception and AI self-efficacy cluster type as independent variables, and AI using education competency and its sub-areas as dependent variables. As a result of the study, AI value perception and AI self-efficacy cluster types showed four clusters. According to these clusters, there were differences between groups in both the AI-based education competency and its sub-areas. In particular, the results commonly found in the difference showed that group 1 (AI value perception and AI self-efficacy high) had higher score of AI using education competency and its sub-areas than group 4 (AI value percpetion and AI self-efficacy low). Based on this, the direction and implications for improving future AI using educational competencies in graduate schools of education were proposed. 2022 교육과정 개정에 따라 인공지능(AI) 기초소양이 학교 교육 과정에 포함되었으며, 학교 현장에 AI 교육이 도입되기 시작하였다. 이에 따라 예비교사를 양성하고 현장교사를 재교육시키는 교육대학원의 역할이 강조되면서 AI 관련 기초연구가 필요한 시점이다. 이 연구의 목적은 교육대학원생들의 AI 가치 인식과 AI 자기효능감 군집유형을 파악하고, 이 군집유형에 따른 AI 활용 교육 역량 차이 분석을 실시하고자 하였다. 이를 위해서 수도권에 위치한 A교육대학원 재학생 중 설문에 성실하게 응답한 155명의 데이터를 바탕으로 결과를 분석하였다. 자료분석은 AI 가치 인식과 AI 자기효능감 군집유형을 독립변인으로 하고, AI 활용 교육 역량과 그 하위 영역을 종속변인으로 하여 군집분석과 일원분산분석(ANOVA) 및 다변량분산분석(MANOVA)을 실시하였다. 연구결과, AI 가치 인식과 AI 자기효능감 군집유형은 크게 4개 군집이 나타났다. 이와 같은 군집에 따라 AI 활용 교육 역량과 그 하위 영역에서 모두에서 그룹 간 차이가 있는 것으로 나타났다. 특히 그룹간 차이에서 공통으로 나타난 결과는 그룹 1(AI 가치 인식과 AI 자기효능감 상위)이 그룹4(AI 가치 인식과 AI 자기효능감 하위)보다 AI 활용 교육 역량과 그 하위 영역에서 높게 나타났다. 이를 기반으로 교육대학원에서의 향후 AI 활용 교육 역량을 향상하기 위한 방향 및 시사점을 제안하였다.

A study on Perceptions of Education Using AI in the Post-Corona Era

김성희,김규태 고려대학교 응용문화연구소 2021 에피스테메 Vol.- No.26

Due to the corona pandemic, interest in technology-based education such as AI-based education and edutech is in the spotlight, and the operation of a curriculum that meets the educational goals of learners is emerging as the key. In particular, Korea has been nurturing professional manpower through the operation of the Graduate School of Education from 2020 to nurture professional teachers for AI-using education. In this study, a survey on perceptions of AI-using education (curriculum) and education policy necessary to revive interest in AI education was conducted for 500 men and 500 women. They consist of 200 people each for each age group (20s to 60s). First, as an advantage of AI-based education, it was found that there is a high expectation for the possibility of individualized education using AI. I was able to confirm that it was recognized as Second, as a disadvantage of AI-using education, it was confirmed that both men and women expressed “concerns about the emergence of AI technology that replaces teachers” Disadvantages (concerns) of AI-using education by age group include “concerns about the emergence of AI technology instead of teachers”, “distrust of AI-based learner-tailored learning”, and “personal information leakage for AI-based careers (advancement)” has been displayed It can be seen that more attention and preparation are needed for the shortcomings of AI-based education. Lastly, in the survey on the perception of education (curriculum) and education policy required to conduct AI-using education, it was found that 1 to 8 items agreed with the detailed elements necessary for AI-using education. Moreover, the 60s actively expressed their opinions about ethics education, a dedicated teacher training system, new textbooks and appropriate teaching methods. Through this, it was confirmed that the higher the age group, the more concerns and rejection of AI-using education, and the need to establish a device for a safer educational environment, and the need for education (curriculum) and education policy for this purpose were confirmed. This study will be able to form a consensus on the need for education using AI, which is necessary in the recent post-corona era, and contribute to the design and substantiation of specific education (curriculum) and education policy necessary to specifically prepare AI-using education.