Family Learning Talk in AI Literacy Learning Activities

要旨

The unique role that AI plays in making decisions that affect humans creates a need for public understanding of AI. Informal learning spaces are important contexts for fostering AI literacy, as they can reach a broader audience and provide spaces for children and parents to learn together. This paper explores 1) what types of dialogue familes engage in when learning about AI in an at-home learning environment to inform our understanding of 2) how to design AI literacy activities for informal learning contexts. We present an analysis of family dialogue surrounding three AI education activities and use our findings to update existing principles for designing AI literacy educational interventions. Our findings indicate that embodied interaction, collaboration, and lowering barriers to entry were effective at fostering learning talk. Our results also reveal emergent areas for future research on how to support parents and design visualizations and datasets for AI learning.

著者
Duri Long
Georgia Institute of Technology, Atlanta, Georgia, United States
Anthony Teachey
Georgia Institute of Technology, Atlanta, Georgia, United States
Brian Magerko
Georgia Institute of Technology, Atlanta, Georgia, United States
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3502091

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Interactive Learning Support Systems

291
4 件の発表
2022-05-02 23:15:00
2022-05-03 00:30:00