AI technologies in K-12 science education enhance learning outcomes through multiple approaches including robotics, chatbots, machine learning, and automated feedback systems.
Objective: To examine the pedagogical incorporation of AI technologies in K-12 science education from 2013 to 2023 through bibliometric mapping and systematic literature review.
Methods:
- Systematic literature review of 20 studies from Scopus database and 5 science education journals
- PRISMA guidelines for study selection
- Bibliometric mapping using VOSviewer 1.6.20
- Thematic analysis of studies using inductive and deductive coding
Key Findings:
- Robotics and chatbots significantly improve student motivation and scientific literacy
- AI technologies enhance personalized learning experiences
- Different pedagogical approaches (hands-on, inquiry-based, blended learning) effectively integrate AI
- High school settings show more AI integration compared to elementary levels
Implications:
- Demonstrates AI's potential to transform science education through personalized learning
- Provides evidence-based strategies for AI integration in classrooms
- Highlights need for professional development and infrastructure investment
Limitations:
- Limited to Scopus database and English-language publications
- Focused only on studies available in full text
- Literature collection limited to 2023
- Geographic representation gaps
Future Directions:
- Expand research to include other databases and non-English studies
- Conduct longitudinal studies on long-term impacts
- Investigate ethical implications of AI integration
- Explore qualitative and mixed-method research approaches
Title and Authors: "Pedagogical incorporation of artificial intelligence in K-12 science education: A decadal bibliometric mapping and systematic literature review (2013-2023)" by K. Kavitha and V. P. Joshith
Published On: December 4, 2024
Published By: Journal of Pedagogical Research