K-9 Artificial Intelligence Education in Qingdao: Issues, Challenges and Suggestions

Teaching challenges for AI literacy include insufficient funding, immature AI curricula, tools and evaluation methods, and technical concerns about whether schools' internet infrastructure is ready for students to compile AI-enabled algorithms and applications.

“They also need to consider various teaching challenges such as insufficient funding, immature AI curricula, tools and evaluation methods (Gong et al., 2020), as well as technical concerns that whether their schools' internet infrastructure is ready for students to compile AI-enabled algorithms and applications (Vazhayil et al., 2019).”

Researchers introduced children to AI concepts in playful and inquiry approaches via high-order thinking activities such as creating digital stories, performing Turing Test with intelligent agents, creating chatbot and inference algorithms, and building applications through blockly-based programming.

“For example, researchers introduced children to AI concepts in playful and inquiry approaches via high-order thinking activities such as creating digital stories (Kandlhofer et al., 2016), performing Turing Test with intelligent agents, creating chatbot and inference algorithms (Wong et al., 2020), and building applications through blockly-based programming (Gong et al., 2020).”

Gong et al. found that students pay little attention to ethical concerns such as bias in AI and legal responsibility, and intellectual property.

“Gong et al. (2020) found that students pay little attention to ethical concerns such as bias in AI and legal responsibility, and intellectual property.”

Gong et al. (2020) found that students pay little attention to ethical concerns such as bias in AI and legal responsibility (8%), and intellectual property (9%).

“Gong et al. (2020) found that students pay little attention to ethical concerns such as bias in AI and legal responsibility (8%), and intellectual property (9%).”