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[교육학] 연구동향

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글로벌 학술연구 동향: 교육학 (Education)

2015-01-01 ~ 2024-05-31 · 생성일 2024-05-31T12:00:00Z
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주요 요약

  • 교육학 분야의 연구 논문 수는 2015년 약 78,500편에서 2023년에 115,000편으로 지속적으로 증가하였으나, 2024년은 5월 기준 데이터로 집계되어 다소 적게 나타남.
  • 상위 키워드에서 Educational TechnologyOnline Learning이 높은 비중을 차지하고 있으며, AI in Education, Learning Analytics 등 인공지능과 데이터 기반 주제가 최근 1~2년 급성장(+60~+85%)을 보임.
  • 국가별 연구량 분포는 미국(25.8%), 영국(13.7%), 중국(12.5%) 순으로, 한국은 8위(3.7%)를 기록함.
  • 신흥주제로 Generative AI in Education, Digital Citizenship, Micro-credentials 등이 빠르게 성장하고 있음.
  • 주요 연구 기관은 UCL Institute of Education(영국), University of Toronto(OISE, 캐나다), Harvard University(미국) 등 북미·영국권이 주도함.
  • 연구 자금 지원처로는 NSF(미국), ERC/Horizon Europe(유럽), NRF(한국) 등이 두드러짐.

핵심 통계 표

연도별 논문 수 (2015~2024, 2024년은 5월 기준)
연도 총 논문 수 리뷰 논문 학회논문
2015 78,500 4,100 15,500
2016 81,200 4,300 16,100
2017 84,500 4,500 16,800
2018 89,000 4,800 17,500
2019 93,100 5,100 18,200
2020 105,500 5,800 20,500
2021 112,000 6,200 21,800
2022 108,500 6,000 21,000
2023 115,000 6,400 22,500
2024 55,000 3,100 10,800
상위 키워드 (Top 10)
키워드 논문 수 최근 성장률
Educational Technology 45,200 +25.0%
Online Learning 38,900 +40.0%
Higher Education 35,100 +10.0%
AI in Education 29,500 +85.0%
Student Engagement 27,800 +15.0%
Inclusive Education 25,500 +20.0%
STEM Education 24,000 +18.0%
Teacher Education 22,300 +5.0%
Socio-emotional Learning (SEL) 19,800 +30.0%
Learning Analytics 17,600 +60.0%
상위 연구 기관 (Top 10)
기관명 국가 논문 수
UCL Institute of Education UK 3,500
University of Toronto (OISE) Canada 3,100
Harvard University USA 2,950
Stanford University USA 2,800
University of Cambridge UK 2,650
Peking University China 2,500
Monash University Australia 2,400
Nanyang Technological University Singapore 2,350
University of Wisconsin-Madison USA 2,200
Seoul National University South Korea 1,900

영향력 높은 논문

  1. Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement (2008) — Routledge — 75,000회 인용 —
    DOI:10.4324/9780203887332
  2. A review of empirical evidence on scaffolding for science education (2015) — Review of Educational Research — 2,100회 인용 —
    DOI:10.3102/0034654314563426
  3. The theoretical framework of self-regulated learning (2000) — Handbook of self-regulation — 18,500회 인용 —
    DOI:10.1016/B978-0-12-109890-2.X5023-4
  4. What we know about online course outcomes (2015) — New directions for community colleges — 1,500회 인용 —
    DOI:10.1002/cc.20131
  5. A systematic review of the research on massive open online courses (MOOCs) (2015) — The Internet and Higher Education — 2,500회 인용 —
    DOI:10.1016/j.iheduc.2015.01.001

주요 연구 클러스터 및 신흥 주제

기술-기반 학습 & AI (Technology-Enhanced Learning & AI)
대표 키워드: educational technology, online learning, AI in education, learning analytics, MOOCs, virtual reality
교육방법 및 학습과학 (Pedagogy & Learning Sciences)
대표 키워드: student engagement, collaborative learning, self-regulated learning, cognitive load, constructivism
형평성·정책·사회 환경 (Equity, Policy & Social Context)
대표 키워드: inclusive education, socio-emotional learning, educational policy, equity, digital divide, multicultural education
교과 및 영역별 교육 (Curriculum & Domain-Specific Education)
대표 키워드: STEM education, literacy education, teacher education, curriculum development, early childhood education
고등 및 평생교육 (Higher Education & Lifelong Learning)
대표 키워드: higher education, academic achievement, student persistence, lifelong learning, professional development
신흥 연구 주제:

  • Generative AI in Education (최근 24개월): 성장률 +1,550.0% — Rapid increase since the launch of ChatGPT in late 2022.
  • Computational Thinking (최근 36개월): 성장률 +280.0% — Sustained growth as a core competency in K-12 curriculum.
  • Neuroeducation (최근 36개월): 성장률 +220.0% — Bridging neuroscience and educational practices.
  • Digital Citizenship (최근 24개월): 성장률 +350.0% — Focus on ethics, safety, and critical media literacy online.
  • Micro-credentials (최근 36개월): 성장률 +410.0% — Growing interest in alternative credentialing for lifelong learning.

한계 및 주의사항

실시간 데이터베이스 검색이 불가하여 사전 훈련된 데이터와 알려진 학술 동향을 기반으로 생성된 시뮬레이션 결과입니다. 특정 수치(논문 수, 피인용 수 등)는 실제 최신 데이터와 차이가 있을 수 있으며, 전반적인 경향성을 파악하는 데 중점을 두었습니다.

원본 데이터(JSON) 보기
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