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세계의 고등교육 분야 AI 시장을 조사했으며, AI 도입 현황, 고등교육 부문에서의 AI 역할, AI 활용을 형성하는 주요 시장 요인, 주요 지역의 AI 정책, 규제, 거버넌스 프레임워크, 기관별 가이드라인, 주요 AI 활용 사례 분석, 투자 및 자금 조달 동향, 에코시스템 및 주요 기업 프로파일 등의 정보를 정리하여 전해드립니다.
목차
제1장 소개
- 조사 범위
- 시장 요약
- 기술 통합
- 시장 역학 및 성장 요인
- 향후 동향과 발전
- 정책적 관점
- 심리지수의 관점
- 결론
제2장 주요 대학의 AI 정책, 준비 현황, 시장 기반
- 고등교육에서 AI의 역할
- 고등교육에서의 AI 로드맵과 도입 경로
- AI 로드맵
- 채용 경로
- AI 프레임워크와 거버넌스
- AI 정책 및 가이드라인
- 규제의 중요성
- 주요 대학의 AI 도입 또는 실험
- University of Oxford
- Massachusetts Institute of Technology(MIT)
- Princeton University
- University of Cambridge
- Harvard University
- Stanford University
- California Institute of Technology(Caltech)
- Imperial College London
- University of California(UC)
- Yale University
- ETH Zurich
- Tsinghua University
- University of Pennsylvania
- University of Chicago
- Johns Hopkins University
- National University of Singapore
- Cornell University
- Columbia University
제3장 시장의 힘
- 시장 요인 : 스냅샷
- 시장 촉진요인
- 개인화된 학습 경험 강화
- 관리 업무 자동화
- 커리큘럼 개발에 AI 통합
- 시장의 과제와 제약
- 알고리즘의 편향성
- 데이터 프라이버시
- AI 도입에 대한 교직원들의 저항
- 시장 기회
- AI 튜터와 가상 교실
- 고등교육에서의 생성형 AI 활용
- 자동 채점 및 루브릭 채점
제4장 AI 체감지수 분석 : 고등 교육
- AI 체감지수 개요
- 감성지수 분석 방법 및 데이터 소스
- 계산 방법
- AI 감정 점수
- 분석
- 감정의 4가지 카테고리
- 도입(Adoption)
- 변화(Disruption)
- 사용 사례(Use Case)
- 지출(Spend)
- 크로스 애플리케이션 인사이트
- 교수진
- 학생
- 관리자
- AI 도입 : 감정 분석
- AI 도입 : 용도별 감성 분석
- AI를 통한 파괴적 혁신 : 감정 분석
- AI를 통한 파괴적 혁신 : 용도별 감성 분석
- AI 활용 사례 : 감정 분석
- AI 활용 사례 : 용도별 감정 분석
- AI 지출 : 감정 분석
- AI 지출 : 용도별 감성 분석
제5장 AI의 경쟁 구도
- AI 스택 제공업체 스냅샷 : 플랫폼, 인프라, 서비스
- 플랫폼 제공업체
- 인프라 제공업체
- 서비스 제공업체
- 최근 동향 및 전략적인 노력
- 고등교육에서의 AI 투자 및 보조금
- EdTech 분야에서의 AI
- EdTech의 AI 스타트업
- EdTech의 AI 기업 자금 조달
- 시장 생태계
- 학습 관리 플랫폼
- 적응형/개별 학습
- 평가 도구
- 컨텐츠 감지 도구
- 지원 도구
- 고등교육 대학
- 제품 매핑 분석
- 1차 조사 인사이트(대학의 관점)
- 고등교육에서 AI의 역할
- 학생들이 사용하는 주요 AI 도구
- AI는 대학을 어떻게 지원해야 하는가?
- 고등교육에서 AI에 대한 주요 응답자의 견해
제6장 부록
KSM
This report will offer an in-depth analysis of the global AI in higher education market and analyze important market forces. It will examine detailed policy and guidance along with institutional guidelines, and provide key use cases analysis by faculty, students and administrative staff. The report will also cover the impact of AI adoption, including investments and funding by platform providers and end users. In addition, the market ecosystem covering AI technology and platform providers, content and learning solution providers, system integrators and service providers, higher education institutions and end users will be analyzed, supported by a sentiment index survey to provide key insights on adoption, investments, the market ecosystem and other crucial parameters.
Report Scope
- This report provides an overview of the global market for artificial intelligence (AI) in higher education and analyzes market trends.
- The study focuses on providing insight into AI in higher education.
- In-depth policy and guidance, along with institutional guidelines, are analyzed.
- Market dynamics, including key drivers, challenges, and opportunities, are covered.
- The research also covers the impact of AI adoption, along with investments and funding by platform providers and end users.
- The report analyzes in detail the market ecosystem covering AI technology and platform providers, content and learning solution providers, systems integrators and service providers, and higher education institutions.
- A survey was conducted to provide insights for adoption, investments and the market ecosystem.
- The report also covers the sentiment index on four key parameters for AI in higher education: adoption, disruption, use cases and spending.
Report Includes
- An overview of artificial intelligence (AI) adoption and its role in the global higher education sector
- Analysis of key market forces shaping AI use in higher education, including drivers, challenges, trends, and opportunities
- Review of AI policies, regulations, governance frameworks, and institutional guidelines across major regions
- Examination of AI readiness, adoption pathways, and value chain stakeholders in higher education
- Assessment of the impact of U.S. tariffs and trade policies on the AI in higher education market
- Analysis of key AI use cases for faculty, students, and administrative staff
- Evaluation of AI adoption impact, including investments and funding by platform providers and end users
- AI Sentiment Index analysis covering adoption, disruption, spending, and use cases in higher education
- Analysis of the competitive landscape, including AI platform providers, solution providers, system integrators, and service providers
- Insights from primary research highlighting key pain points, unmet needs, and emerging areas
- Overview of the market ecosystem involving technology providers, content and learning solution providers, and higher education institutions
- Company profiles of the leading players
Table of Contents
Chapter 1 Introduction
- Scope of Report
- Market Summary
- Integration of Technology
- Market Dynamics and Growth Factors
- Future Trends and Developments
- Policy Viewpoint
- Sentiment Index Viewpoint
- Conclusion
Chapter 2 AI Policy, Readiness and Market Foundations in Top Universities
- Role of AI in Higher Education
- AI Roadmap and Adoption Pathways in Higher Education
- AI Roadmap
- Adoption Pathways
- AI Frameworks and Governance
- AI Policies and Guidelines
- Importance of Regulations
- Implementation or Experimentation of AI in Key Universities
- University of Oxford
- Massachusetts Institute of Technology (MIT)
- Princeton University
- University of Cambridge
- Harvard University
- Stanford University
- California Institute of Technology (Caltech)
- Imperial College London
- University of California (UC)
- Yale University
- ETH Zurich
- Tsinghua University
- University of Pennsylvania
- University of Chicago
- Johns Hopkins University
- National University of Singapore
- Cornell University
- Columbia University
Chapter 3 Market Forces
- Market Forces Snapshot
- Market Drivers
- Enhancement of the Personalized Learning Experience
- Automation of Administrative Tasks
- Integration of AI into Curriculum Development
- Market Challenges and Restraints
- Algorithmic Bias
- Data Privacy
- Faculty and Staff Resistance to Adopting AI
- Market Opportunities
- AI Tutors and Virtual Classrooms
- Embracing Generative AI in Higher Education
- Automated Grading and Rubric Scoring
Chapter 4 AI Sentiment Index Analysis: Higher Education
- Overview of the AI Sentiment Index
- Sentiment Index Analysis Methodology and Data Sources
- How Is It Calculated?
- AI Sentiment Scores
- Analysis
- Four Categories of Sentiment
- Adoption
- Disruption
- Use Case
- Spend
- Cross-Application Insights
- Faculty
- Students
- Administrators
- AI Adoption: Sentiment Analysis
- Introduction
- AI Adoption: Sentiment Analysis by Application
- AI Disruption: Sentiment Analysis
- Introduction
- AI Disruption: Sentiment Analysis by Application
- AI Use Cases: Sentiment Analysis
- Introduction
- AI Use Cases: Sentiment Analysis by Application
- AI Spend: Sentiment Analysis
- Introduction
- AI Spend: Sentiment Analysis by Application
Chapter 5 AI Competitive Landscape
- AI Stack Providers Snapshot: Platform, Infrastructure and Service
- Platform Providers
- Infrastructure Providers
- Service Providers
- Recent Developments and Strategic Initiatives
- Investments and Grants for AI in Higher Education
- AI in the EdTech Sector
- AI Startups in EdTech
- Funding in AI Companies in EdTech
- Market Ecosystem
- Learning Management Platforms
- Adaptive/Personalized Learning
- Assessment Tools
- Content Detection Tools
- Assistance Tools
- Higher Education Universities
- Product Mapping Analysis
- Primary Research Insights (From Universities' Perspectives)
- Role of AI in Higher Education
- Key AI Tools Used by Students
- How Should AI Assist Universities?
- Viewpoints of Primary Respondents on AI in Higher Education
Chapter 6 Appendix
- Methodology
- References
- Abbreviations