Teaching AI to K-12 Learners: Lessons, Issues, and Guidance

Author:

Grover Shuchi1ORCID

Affiliation:

1. Looking Glass Ventures (Edfinity), Austin, TX, USA

Funder

National Science Foundation

Publisher

ACM

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Unpacking Approaches to Learning and Teaching Machine Learning in K-12 Education: Transparency, Ethics, and Design Activities;Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research;2024-09-16

2. Evidence-based advancement of teaching AI in K-12: an action research approach;Proceedings of the 19th WiPSCE Conference on Primary and Secondary Computing Education Research;2024-09-16

3. Learning an Explanatory Model of Data-Driven Technologies can Lead to Empowered Behavior: A Mixed-Methods Study in K-12 Computing Education;Proceedings of the 2024 ACM Conference on International Computing Education Research - Volume 1;2024-08-12

4. A No-Code AI Education Tool for Learning AI in K-12 by Making Machine Learning-Driven Apps;2024 IEEE International Conference on Advanced Learning Technologies (ICALT);2024-07-01

5. Enduring Lessons from 'Computer Science for All' for AI Education in Schools;Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2;2024-03-14

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