About this Research Topic
AI is reshaping education, offering personalized support, inclusive learning opportunities, stronger teacher-student connections, and better recognition and evaluation of achievements. While promising, responsible adoption is crucial to ensure AI's potential is fulfilled and quality education becomes accessible to all. These developments, though exciting, challenge traditional educational models.
AI systems now surpass humans in specific activities, such as enhancing text-to-animation, voice-to-video synthesis, automatic video captioning, and translation. These technologies open avenues for innovative teaching and improved accessibility. However, deciding which tasks should be "delegated" to AI requires careful consideration.
AI has the potential to revolutionize analytics and evaluation in education. AI-powered assessments provide valuable insights, enabling teachers to identify patterns in student learning and assess non-standard exams. This facilitates faster feedback and promotes student engagement by identifying strengths and weaknesses in real time. By using AI, educators can develop tailored instructional strategies and enhance critical thinking, creativity, and problem-solving skills, all essential for preparing students for the future workforce.
The key emerging technologies that will impact education are discussed in this Research Topic, based on academic research and literature emerging out of non-academic domains engaging with AI. These technologies are expected to reshape education, with important societal implications. The discussion covers digital accessibility for students with disabilities, the effects of these innovations on developing countries, and how they intersect with issues such as climate change, mental health, and ecological balance.
Scholars from diverse fields are invited to contribute articles examining digital learning innovations. This Research Topic focuses on AI-driven personalized learning in higher education, exploring technological innovations, ethical concerns, and implementation challenges.
Key areas of focus include:
1. AI-Driven Technological Innovations and Pedagogical Perspectives
• AI’s Role in Enhancing Educator Efficiency
• AI-Driven Curriculum and Assessment Personalization
• AI for Digital Accessibility:
• Integrating Indigenous Knowledge through AI Technologies
• AI in Education for Developing Countries
• AI in Promoting Gender Equality and Sustainability
2. Ethical Considerations and Data Privacy
• Balancing personalization with data privacy in higher education.
• Algorithmic bias and fairness in AI-driven educational tools.
• Transparency and explainability of AI decision-making in educational contexts.
• Ethical frameworks for AI use in higher education.
3. Implementation Challenges and Institutional Readiness:
• Faculty training and development for AI-enhanced teaching.
• Institutional policies and governance for AI adoption in higher education.
• Cost-benefit analysis of implementing AI-driven personalized learning systems.
• Case studies of successful AI implementation in higher education institutions.
AI systems now surpass humans in specific activities, such as enhancing text-to-animation, voice-to-video synthesis, automatic video captioning, and translation. These technologies open avenues for innovative teaching and improved accessibility. However, deciding which tasks should be "delegated" to AI requires careful consideration.
AI has the potential to revolutionize analytics and evaluation in education. AI-powered assessments provide valuable insights, enabling teachers to identify patterns in student learning and assess non-standard exams. This facilitates faster feedback and promotes student engagement by identifying strengths and weaknesses in real time. By using AI, educators can develop tailored instructional strategies and enhance critical thinking, creativity, and problem-solving skills, all essential for preparing students for the future workforce.
The key emerging technologies that will impact education are discussed in this Research Topic, based on academic research and literature emerging out of non-academic domains engaging with AI. These technologies are expected to reshape education, with important societal implications. The discussion covers digital accessibility for students with disabilities, the effects of these innovations on developing countries, and how they intersect with issues such as climate change, mental health, and ecological balance.
Scholars from diverse fields are invited to contribute articles examining digital learning innovations. This Research Topic focuses on AI-driven personalized learning in higher education, exploring technological innovations, ethical concerns, and implementation challenges.
Key areas of focus include:
1. AI-Driven Technological Innovations and Pedagogical Perspectives
• AI’s Role in Enhancing Educator Efficiency
• AI-Driven Curriculum and Assessment Personalization
• AI for Digital Accessibility:
• Integrating Indigenous Knowledge through AI Technologies
• AI in Education for Developing Countries
• AI in Promoting Gender Equality and Sustainability
2. Ethical Considerations and Data Privacy
• Balancing personalization with data privacy in higher education.
• Algorithmic bias and fairness in AI-driven educational tools.
• Transparency and explainability of AI decision-making in educational contexts.
• Ethical frameworks for AI use in higher education.
3. Implementation Challenges and Institutional Readiness:
• Faculty training and development for AI-enhanced teaching.
• Institutional policies and governance for AI adoption in higher education.
• Cost-benefit analysis of implementing AI-driven personalized learning systems.
• Case studies of successful AI implementation in higher education institutions.
Keywords: Digital Learning Innovations, AI, Innovation, Pedagogical Perspectives, Institutional Readiness
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
