Artificial Intelligence education for young children: Why, what, and how in curriculum design and implementation

By Weipeng Yang. Computers and Education: Artificial Intelligence, 2022

361 citations recorded by the source corpus.

Subfields: Computer Science Applications, Developmental and Educational Psychology, Education

View Paper: https://www.semanticscholar.org/paper/7d3b7c8e60fd6e4e0e84fd72d717f4c86447a10c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Science Applications

1. Davy Tsz Kit Ng
2. S. K. Chu
3. J. Stephen Downie
4. Wattanapong Kurdthongmee
5. M. Lee
6. Xiao Hu
7. Arsanchai Sukkuea
8. Roy Jun Yi Tan

In Developmental and Educational Psychology

1. S. K. Chu
2. J. Stephen Downie
3. M. Lee
4. Xiao Hu
5. Davy Tsz Kit Ng
6. Roy Jun Yi Tan

In Education

1. S. K. Chu
2. J. Stephen Downie
3. M. Lee
4. Xiao Hu
5. Davy Tsz Kit Ng
6. Roy Jun Yi Tan

Citations in the corpus

• Leading teachers' perspective on teacher-AI collaboration in education (2023, neutral): “…users of AI, or even AI builders to solve different problems through problem-solving and collaborative project-based learning, particularly for younger students, who are not yet familiar with abstract explanations or the required mathematical foundations (Yang, 2022; Chootongchai et al., 2021).”
• Integration of IoT-Enabled Technologies and Artificial Intelligence (AI) for Smart City Scenario: Recent Advancements and Future Trends (2023, background): “[168] reviewed and aimed to comprehend the direction of smart home advancements and merchandise and the correlation between literature and AI-enabled products in smart homes.”
• A review of AI teaching and learning from 2000 to 2020 (2022, methodology): “2022b), experiencing AI through toys and robotics, (Yang, 2022) and visualization tools (García et al.”