Abstract

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Contributions:</i> The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created the first pretertiary AI curriculum at the secondary school level for Hong Kong and evaluated its efficacy. This study added to the AI education community by introducing a new AI curriculum framework. The preposttest multifactors evaluation about students’ perceptions of AI learning confirmed that the curriculum is effective in promoting AI learning. The teachers also confirmed the co-creation process enhanced their capacity to implement AI education. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Background:</i> AI4Future is a cross-sector project that engages five major partners—CUHK’s Faculty of Engineering and Faculty of Education, secondary schools, Hong Kong government, and AI industry. A team of 14 professors collaborated with 17 principals and teachers from six secondary schools to co-create the curriculum. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Research Questions:</i> Would the curriculum significantly improve the student perceived competence, attitude, and motivation toward AI learning? How does the co-creation process benefit the implementation of the curriculum? <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Methodology:</i> The participants were 335 students and eight teachers from the secondary schools. This study adopted a mix-method with quantitative data measures at pre- and post-questionnaires and qualitative data emphasizes teachers’ perspectives on the co-creation process. Paired <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${t}$ </tex-math></inline-formula> -tests and ANCOVAs, and thematic analysis were used to analyze the data. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Findings:</i> 1) students perceived greater competence and developed a more positive attitude to learn AI and 2) the co-creation process enhanced teachers’ knowledge in AI, as well as fostered teachers’ autonomy in bringing the subject matter into their classrooms.

Highlights

  • T HE EXPLOSIVE growth of artificial intelligence (AI) is increasingly transforming the way we live, learn, and work

  • This study presented two empirical findings and discussed its two major practical contributions to pretertiary AI education

  • The first finding is the proposed curriculum has significantly enhanced perceived competence in (AIKG, AI readiness (AIRD)), attitude (AICF, AIRE), and intrinsic motivation toward AI (AIIM)— please refer to RQ1. This result supports those of related studies that suggest how the K–12 engineering curriculum should be designed, such as those by Delaine et al [38], Moore et al [19], and Locke [39]. This finding further confirmed that the developed content and activities were appropriate for school students, and covered what students should master for AI technologies

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Summary

Background

There are two stages: 1) curriculum development and 2) implementation in AI4future. In the curriculum development stage, a designed-based research method was adopted since the method aims to design and develop educational technology innovations [27]–[29]. The selected schools have demonstrated that they have placed high emphasis in STEM education and expressed that they have placed AI education in high priority for their students This team formation bridges the gap between research on engineering and AI education. The teachers taught the AI topics in blended environments—both online and face-to-face modes, over a period of approximately three months. They considered their school culture, teaching environments, and resources, and selected the relevant content, as well as fine-tune the content to create learning activities that are most fitting for their students’ needs and interests.

INTRODUCTION
AI Education in K–12 Schools
Drawing Reference to K–12 Engineering Education
School Curriculum and Teacher Autonomy
THIS STUDY
Method
Measures
CURRICULUM DEVELOPMENT
Overview of the Co-Created Curriculum
Curriculum Framework
Curriculum Content That Fosters Local and Global Understanding
Curriculum Activities Designed for Flexibility
Student Enhancement
DISCUSSION
Two Empirical Findings
Two Major Practical Contributions
Findings
LIMITATIONS AND FUTURE
Full Text
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