AI literacy in K-16 Classrooms

Dr. Feng-Kuang Chiang

Professor, Shanghai Jiao Tong University, China

Education and work experience

江豐光博士目前是上海交通大學教育學院長聘教軌教授和未來教育中心主任，研究主要關注資訊科技運用在創新的教與學中，研究興趣包含: STEAM 教育、學習空間、資訊科技與創新教學、教育機器人、跨學科研究，以及技術對正式和非正式學習環境（大學課程、專業發展和 K12 學校課堂等）的影響。透過教學設計與研究的干預措施，以減少學生的成績差距。

他於2009年畢業於國立高雄師範大學工業科技教育系（教育科技組），2011年完成臺灣大學博士後研究。2011年至2017年在北京師範大學任講師/副教授。2017年至2022年在上海師範大學擔任了特聘教授與教育技術系的系主任。2019年為美國麻省理工學院客座研究員。

目前已發表學術論文110多篇，其中SSCI/SCI期刊論文約50篇。目前在四個期刊擔任編輯委員和 35 個國際期刊(SSCI、SCI 和 EI)的論文評審委員。 連續兩年被愛思唯爾ELSEVIER提名為教育領域的“2021/2022中國高被引科學家獎”。

Feng-Kuang Chiang is now a professor of School of Education and the founding director of the Center for Future Education (CFE) at Shanghai Jiao Tong University (SJTU), who specialises in the innovative use of technology for teaching and learning purposes. His research interests include STEAM education, learning space, ICT in innovative instruction, robotics in education, some cross-disciplinary topics, and the impact of technology in formal and informal learning environments (college classes, professional development, and K12 school classrooms etc.) and scalable interventions to broaden participation and reduce students’ achievement gaps.

He received his Ph.D. degree in the Department of Industrial Technology Education (Majored in Educational Technology) from National Kaohsiung Normal University in 2009. He completed his postdoctoral fellowship at National Taiwan University in 2011. From 2011 to 2017 he worked as a lecturer/ associate professor at Beijing Normal University. Before joining SJTU, he spent five years as a Distinguished Professor at Shanghai Normal University (SHNU) and as a director of the Department of Educational Technology at SHNU from 2017 to 2022. He was a visiting scientist at MIT in 2019

He has published more than 110 academic papers, including about 50 SSCI/SCI journal papers. He is also an active participant in international journals and serves on four journals' Editorial boards and 35 international journal reviewer boards, including SSCI, SCI, and EI journals. His productivity and scholarship have been recognized by Elsevier, being nominated two years in a row for an “2021/2022 Highly Cited Chinese Researchers Award” , as well as several other national and institutional teaching awards.

Research Specialty

STEAM教育/STEAM Education
學習空間/ Learning Space
資訊科技創新教學/ Innovation in Instruction with Information Technology

Topic: Research and Practice of Artificial Intelligence Education in the Chinese

Abstract:

本次論壇主要介紹在大陸中小學開展的人工智能教育教學實踐案例。研究團隊分別從四個部分進行分享：第一部分為兒童早期STEM素養指標體系構建，通過運用德爾菲法及層次分析法(AHP)，構建了一套針對幼稚園兒童的STEM素養指標體系；第二部分以無人機課程為例，介紹小學人工智能課堂教學實踐，以探究小學生的AI的學習態度和學習效果；第三部分介紹初中智能蔬菜種植STEM課程，以促進學生對開源硬體、感測器和物聯網工具等智能技術的概念理解和學習動機；第四部分介紹上海交通大學為高中生舉辦的線上營隊活動“AI for Youth Camp”，希望可以提升高中生的AI素養和AI職業認同感。研究團隊通過對以上實踐案例與研究成果進行反思與對話，進一步探討人工智能教育對學生認知和非認知的影響，並希望從人工智能教育實踐中提出未來開展相關AI教學研究的指導建議。

This forum focuses on the practical cases of AI education and teaching carried out in primary and secondary schools in the mainland. The research team shared four parts: In the first part, a framework of age-appropriate STEM literacy for kindergartener was developed by using the Delphi method and hierarchical analysis (AHP). The second part introduces the teaching practice of AI curriculum in elementary schools, taking the smart drone curriculum as an example, in order to explore the learning attitude and effect of elementary school students towards AI. The third section presents a middle school smart vegetable gardening STEM curriculum to promote students' conceptual understanding and motivation to learn smart technologies such as open source hardware, sensors, and IoT tools. The fourth section will discuss "AI for Youth Camp", an online camp organized by Shanghai Jiao Tong University for high school students, hoping to enhance their AI literacy and AI career identity. By reflecting and dialoguing on the above practical cases and research results, the research team further explores the impact of AI education on students' cognition and non-cognition, and hopes to propose guidance suggestions for future AI teaching and learning research from AI education practices.