The main goal of the study is to review existing literature on AI learning tools, pedagogical strategies, assessment methods, and learning outcomes in K-12 education to inform educators about effective practices in AI literacy education.
Methods: The study conducted a scoping review of 46 studies from academic conferences and journals, analyzing pedagogical strategies, learning tools, assessment methods, and students' learning outcomes in AI literacy education within K-12 contexts.
Key Findings:
- Significant progress has been made in promoting AI literacy education over the past two decades.
- Intelligent agents like Google's Teachable Machine and Learning ML are effective, age-appropriate tools for K-12 AI literacy education.
- Pedagogical strategies such as project-based, human-computer collaborative, and play- and game-based learning are frequently applied.
- Positive cognitive, affective, and behavioral learning outcomes, along with course satisfaction and soft skills acquisition, have been reported.
Implications: The findings contribute to the field of AI in education by providing educators with insights into effective tools and strategies for teaching AI literacy, thus enhancing students' engagement and understanding of AI concepts.
Limitations: The study is limited by its focus on the literature available up to the time of review and may not encompass all existing or emerging tools and strategies in AI education.
Future Directions: Future research should explore the development of theoretical frameworks for AI literacy education, investigate the long-term impact of AI learning tools, and address the scalability of these tools in diverse educational settings.
Title and Authors: "Artificial intelligence (AI) learning tools in K-12 education: A scoping review" by Iris Heung Yue Yim and Jiahong Su.
Published On: October 25, 2023
Published By: Journal of Computers in Education