AI Literacy in K-12 and Higher Education in the Wake of Generative AI: An Integrative Review
Project Overview
The document outlines the critical role of generative AI in education, emphasizing the emergence of AI literacy as a key educational goal across K-12 and higher education. It identifies the lack of consensus on defining AI literacy, which encompasses varied educational interventions and perspectives, including technical details, tools, and sociocultural impacts. A proposed framework highlights different literacy perspectives—functional, critical, and indirectly beneficial—as essential for effective AI education. A review of 124 studies indicates a growing trend in AI literacy research and underscores the necessity for comprehensive approaches and clearer definitions to guide educational practices. The integration of generative AI in educational contexts is further examined, showcasing various studies designed to enhance AI literacy among students of all ages, particularly emphasizing the importance of critical engagement with AI technologies. Moreover, the document stresses the need to involve diverse student populations, including marginalized groups, in both understanding and designing AI systems, thus fostering an inclusive and well-informed approach to AI education. Overall, the findings advocate for a structured and inclusive framework to equip students with the necessary skills and knowledge to navigate and contribute to an AI-driven future.
Key Applications
AI Literacy and Ethics Education
Context: K-12 and post-secondary education, targeting students from early childhood through high school and undergraduate levels, focusing on AI literacy, ethics, and critical engagement with AI technologies.
Implementation: Implementing comprehensive AI literacy curricula that adapt machine learning concepts for younger learners, integrating discussions on the ethical implications of AI technologies, and providing hands-on experiences through projects like building AI-driven robots. This includes developing specific tools and curricula that help students engage critically with AI systems and understand socio-ethical ramifications.
Outcomes: ['Increased understanding of AI technologies among students', 'Improved critical thinking and ethical awareness', 'Enhanced attitudes towards STEM fields', 'Greater student engagement through hands-on projects']
Challenges: ['Variability in definitions and pedagogical approaches to AI literacy', 'Integrating ethical discussions into technical curricula', 'Difficulty in measuring long-term impacts', 'Resistance from stakeholders regarding the implementation of ethics in technology education', 'Potential accessibility issues for students with varying levels of prior knowledge']
Implementation Barriers
Conceptual Barrier
The lack of consensus on the definition of AI literacy leads to varying interpretations and implementations in education.
Proposed Solutions: Develop a unified framework that clearly delineates different components and objectives of AI literacy.
Implementation Barrier
Challenges in integrating AI literacy into existing curricula due to diverse pedagogical approaches and objectives.
Proposed Solutions: Encourage collaboration among educators to create standardized curricula and share best practices.
Access Barrier
Restrictions on the use of generative AI tools by younger students hinder the practical teaching of AI literacy. Additionally, lack of access to necessary technology and resources for implementing AI education presents another significant challenge.
Proposed Solutions: Explore alternative methods of introducing AI concepts that do not require direct interaction with tools, such as demonstration-based learning. Furthermore, develop open-source educational modules and tools to ensure wider accessibility.
Cultural Barrier
Diverse student backgrounds leading to varying levels of engagement and understanding of AI.
Proposed Solutions: Creating inclusive curricula that address the needs of marginalized groups and encourage participation.
Curriculum Barrier
Challenges in integrating AI literacy into existing educational frameworks.
Proposed Solutions: Developing comprehensive AI literacy frameworks that align with current educational standards.
Project Team
Xingjian Gu
Researcher
Barbara J. Ericson
Researcher
Contact Information
For information about the paper, please contact the authors.
Authors: Xingjian Gu, Barbara J. Ericson
Source Publication: View Original PaperLink opens in a new window
Project Contact: Dr. Jianhua Yang
LLM Model Version: gpt-4o-mini-2024-07-18