Abstract

This study aimed to (1) synthesize the components of the AI-A-thon Learning Ecosystem, (2) synthesize the components of AI Pre-service Teacher Competency, and (3) develop an AI-A-thon Learning Ecosystem to promote AI Pre-service Teacher Competency. A Research and Development (R&D) design was employed, comprising four steps: (1) synthesis of the AI-A-thon Learning Ecosystem components, (2) synthesis of AI Pre-service Teacher Competency components, (3) development of the AI-A-thon Learning Ecosystem, and (4) expert evaluation of the developed system. The AI-A-thon Learning Ecosystem consists of five components: Learners and Learning Community; Content, Resources and AI Tools; Learning Activities and Interaction; Mentorship and Support System; and Assessment and Feedback. AI Pre-service Teacher Competency comprises four dimensions: AI Knowledge, AI Skills, AI Ethics, and AI Character (K–S–E–C). The AI-A-thon learning process consists of five steps: Problem and Objective Identification; Idea Generation and AI Exploration; Prototype Development and Testing; Evaluation and Reflection; and Implementation and Presentation. The developed system was evaluated by 15 experts, with an overall suitability rating of 4.55 (SD = 0.68), corresponding to the highest suitability level under the study’s evaluation criteria. Focus group discussions provided recommendations for clarifying relationships among system components, strengthening mentoring and reflection throughout the learning process, and preparing adequate resources and implementation guidelines. This study establishes a foundation for subsequent implementation and empirical investigation of the AI-A-thon Learning Ecosystem for promoting AI Pre-service Teacher Competency.

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