Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI) Curriculum
Not on the map. Why?
Abstract (arXiv)
Contributions: The Chinese University of Hong Kong (CUHK)-Jockey Club AI for the Future Project (AI4Future) co-created an AI curriculum for pre-tertiary education and evaluated its efficacy. While AI is conventionally taught in tertiary level education, our co-creation process successfully developed the curriculum that has been used in secondary school teaching in Hong Kong and received positive feedback. Background: AI4Future is a cross-sector project that engages five major partners - CUHK Faculty of Engineering and Faculty of Education, Hong Kong secondary schools, the government and the AI industry. A team of 14 professors with expertise in engineering and education collaborated with 17 principals and teachers from 6 secondary schools to co-create the curriculum. This team formation bridges the gap between researchers in engineering and education, together with practitioners in education context. Research Questions: What are the main features of the curriculum content developed through the co-creation process? Would the curriculum significantly improve the students perceived competence in, as well as attitude and motivation towards AI? What are the teachers perceptions of the co-creation process that aims to accommodate and foster teacher autonomy? Methodology: This study adopted a mix of quantitative and qualitative methods and involved 335 student participants. Findings: 1) two main features of learning resources, 2) the students perceived greater competence, and developed more positive attitude to learn AI, and 3) the co-creation process generated a variety of resources which enhanced the teachers knowledge in AI, as well as fostered teachers autonomy in bringing the subject matter into their classrooms.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). Builds on 0 of its 29 references that are in the map. First posted on arXiv 19 Jan 2021.
Builds on
0 of 29 references.
No references here yet.
Built on by
Citing papers per year: 2022: 1; 2023: 2; 2024: 0; 2025: 1; 2026: 2.
6 papers.
- 2023Interpretable Unified Language Checkingcited by 26
- 2023Exploring AI-Generated Text in Student Writing: How Does AI Help?cited by 4
- 2022AI-Assisted Authentication: State of the Art, Taxonomy and Future Roadmapcited by 0
- 2025Scaffolding Creativity: Integrating Generative AI Tools and Real-world Experiences in Business Educationcited by 0
- 2026Analyzing Middle School Students' Dialogue and Behaviors during Collaborative AI Chatbot Development Using Ordered Network Analysiscited by 0
- 2026Bridging Artificial Intelligence and Power Systems Education Using a Hands-On Executable Frameworkcited by 0
- 2026Bridging Artificial Intelligence and Power Systems Education Using a Hands-On Executable Framework3 Aug 2026
- 2026Analyzing Middle School Students' Dialogue and Behaviors during Collaborative AI Chatbot Development Using Ordered Network Analysis15 May 2026
- 2025Scaffolding Creativity: Integrating Generative AI Tools and Real-world Experiences in Business Education11 Jan 2025
- 2023Interpretable Unified Language Checking7 Apr 2023
- 2023Exploring AI-Generated Text in Student Writing: How Does AI Help?10 Mar 2023
- 2022AI-Assisted Authentication: State of the Art, Taxonomy and Future Roadmap25 Apr 2022