# Creation and Evaluation of a Pre-tertiary Artificial Intelligence (AI) Curriculum

arXiv: https://arxiv.org/abs/2101.07570 · HTML: https://mlsanity.com/paper/2101.07570/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 29 references that are in the map.
- First posted on arXiv 19 Jan 2021.

## Built on by (most cited first, 6 of 6)

- [Interpretable Unified Language Checking](https://mlsanity.com/paper/2304.03728/) (2023)
- [Exploring AI-Generated Text in Student Writing: How Does AI Help?](https://mlsanity.com/paper/2304.02478/) (2023)
- [AI-Assisted Authentication: State of the Art, Taxonomy and Future Roadmap](https://mlsanity.com/paper/2204.12492/) (2022)
- [Scaffolding Creativity: Integrating Generative AI Tools and Real-world Experiences in Business Education](https://mlsanity.com/paper/2501.06527/) (2025)
- [Analyzing Middle School Students' Dialogue and Behaviors during Collaborative AI Chatbot Development Using Ordered Network Analysis](https://mlsanity.com/paper/2607.21603/) (2026)
- [Bridging Artificial Intelligence and Power Systems Education Using a Hands-On Executable Framework](https://mlsanity.com/paper/2608.02599/) (2026)

## 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.