Sustainable Curriculum Planning for Artificial Intelligence Education: A Self-Determination Theory Perspective

By Thomas K. F. Chiu, Ching Sing Chai. 2020

373 citations recorded by the source corpus.

The teaching of artificial intelligence (AI) topics in school curricula is an important global strategic initiative in educating the next generation. As AI technologies are new to K-12 schools, there is a lack of studies that inform schools’ teachers about AI curriculum design. How to prepare and engage teachers, and which approaches are suitable for planning the curriculum for sustainable development, are unclear. Therefore, this case study aimed to explore the views of teachers with and without AI teaching experience on key considerations for the preparation, implementation and continuous refinement of a formal AI curriculum for K-12 schools. It drew on the self-determination theory (SDT) and four basic curriculum planning approaches—content, product, process and praxis—as theoretical frameworks to explain the research problems and findings. We conducted semi-structured interviews with 24 teachers—twelve with and twelve without experience in teaching AI—and used thematic analysis to analyze the interview data. Our findings revealed that genuine curriculum creation should encompass all four forms of curriculum design approach that are coordinated by teachers’ self-determination to be orchestrators of student learning experiences. This study also proposed a curriculum development cycle for teachers and curriculum officers.

Subfields: Computer Science Applications, Social Psychology

View Paper: https://www.semanticscholar.org/paper/e7ed51a40d82931b657a4b364c832761cda21e21

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Citations in the corpus

Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy (2023, methodology): “In 2018, AI was officially introduced into the curriculum by the Education Ministry, and the first AI textbook was utilized (Chiu & Chai, 2020; Dai et al., 2020; Su et al., 2022).”
Digital support for student engagement in blended learning based on self-determination theory (2021, background): “…learning environment, e.g., levels 1 and 5 indicate basic and most advanced exercises (Hong Kong public examination results use five levels); apply multimedia learning principles to the design of digital materials (Chiu et al., 2020; Chiu & & Churchill, 2015; Chiu & Chai, 2020) (see Fig.”
The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney (2023, positive): “Although AI education in schools has become a global initiative, it is not seen as a traditional core subject, such as language, mathematics, and science (Chiu & Chai, 2020).”
A review of AI teaching and learning from 2000 to 2020 (2022, background): “Educators have started to engage non-computer science undergraduates, and even K-12 students in learning about AI (Chai et al., 2021; Chiu & Chai, 2020; Xia et al., 2022).”
A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education (2022, background): “Due to the breadth of topics and wide range of skills in the AI field, it is challenging to design and implement a coherent AI curriculum for K–12 without deliberate research and planning (Chiu & Chai, 2020).”
Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world (2023, background): “Teachers need to upgrade their skills and knowledge, and connect the tools to content knowledge and pedagogy through continuous professional training (Kim et al., 2021) such as technical support, guidelines, and teacher education programs (Chiu & Chai, 2020; Luan et al., 2020).”