Document Type : Original Article
Researchers
1 Department of Educational Technology, Faculty of Psychology and Educational Sciences, Allameh Tabatabaei University, Tehran, Iran
2 Department of Curriculum Studies, Faculty of Psychology and Educational Sciences, Allameh Tabatabaei University, Tehran, Iran
3 Department of Computer Science, Faculty of Statistics, Mathematics and Computer Science, Allameh Tabatabaei University, Tehran, Iran
4 Department of Measurement and Evaluation, Faculty of Psychology and Educational Sciences, Allameh Tabatabaei University, Tehran, Iran
Ministerial Ethics Committee
Rapid twenty-first-century transformations and emerging technologies have rendered traditional curricula increasingly inadequate for contemporary learners and societies. The gap between existing curricula and twenty-first-century skills necessitates flexible, adaptive, and continuously updated curriculum models. In Iran, limited empirical research has examined dynamic curricula, the role of artificial intelligence in curriculum design, and its effects on the professional development of student teachers, highlighting a clear research gap.This study aims to design and validate an AI-based dynamic curriculum model and investigate its effect on the professional development of elementary education student teachers at Farhangian University of Birjand. Additionally, it seeks to develop a web-based system for continuous curriculum updating and to evaluate AI chatbots as virtual design assistants. Following a developmental paradigm, the study employs an exploratory mixed-methods design implemented in three phases: (1) analysis and design using inductive content analysis and expert interviews to identify model components; (2) development and prototyping involving chatbot interaction and focus groups to refine the model and produce a web-based prototype; (3) pilot implementation using an experimental design with intervention and control groups to assess impact. Data collection tools include semi-structured interviews, researcher-developed questionnaires, the System Usability Scale (Brooke), and Fernandes et al.’s Professional Development Questionnaire. Qualitative data will be analyzed via inductive content analysis; quantitative data will be subjected to reliability tests (Cronbach’s alpha, test–retest), factor analysis, descriptive statistics, and MANCOVA using SPSS. Findings will inform curriculum policy and teacher education practice.