Content area
The growing integration of artificial intelligence (AI) into educational tools and practices has made AI literacy an increasingly critical competency in teacher education. Pre-service teachers must be equipped to use AI both comprehensively and effectively. This study aimed (1) to explore pre-service teachers' experiences and needs related to AI in education and (2) to design and develop an AI-integrated instructional design (ID) model to enhance AI literacy. A quantitative survey was conducted using a questionnaire administered to 1,673 pre-service teachers in Thailand. A pilot test was first conducted with 30 students, and the reliability of the instrument was assessed using Cronbach's alpha. The results indicated high reliability across all items, including perceptions of AI, perceived impacts of AI, motivation to use AI, and the current learning ecosystems. No significant differences were found between STEM and non-STEM groups across these dimensions, suggesting a common need for AI training. Key training needs included (1) learning activities such as information searching, brainstorming, and discussion; (2) resources such as selected websites/blogs and online MOOC platforms; and (3) preferred instructional media, including interactive quizzes, gamified platforms, and learning management systems. Based on these findings, an ID research approach was employed to develop the AI-integrated ID framework. The initial framework was validated through an expert review by five specialists in educational technology. Grounded in design-based learning principles, the resulting framework comprises seven components: (1) Acquiring Key Contents, (2) Requirements Focus, (3) Trial Initiatives, (4) Embedding Co-Creation, (5) Manufacturing the Artifact, (6) Inspecting Results, and (7) Synthesizing Reflection. The findings provide an adaptable framework for embedding AI literacy in the teacher education curriculum and redesigning courses accordingly. The framework also highlights co-creation and design thinking as effective strategies for AI-integrated pedagogy, offering valuable insights for educators and curriculum designers seeking to enhance AI-related teaching competencies.
Details
Competence;
Educational Resources;
Intelligent Tutoring Systems;
Influence of Technology;
Curriculum Design;
Active Learning;
Learning Strategies;
Educational Technology;
Interviews;
Cooperative Learning;
Ethics;
Communities of Practice;
Student Needs;
Educational Objectives;
Instructional Design;
Artificial Intelligence;
Classrooms;
Formative Evaluation;
Internet;
Computer Use;
Learner Engagement;
Educational Media;
Educational Needs;
Educational Strategies