<![CDATA[Creativity-oriented chemistry learning requires instructional designs that enable students to generate, refine, transform, and evaluate ideas through meaningful scientific inquiry. However, the success of such learning depends not only on the availability of innovative models and digital tools but also on teachers’ ability to facilitate creativity-supportive classroom practices. This study aimed to evaluate the pedagogical feasibility of an Artificial Intelligence-assisted C-R-E-A-T-E learning model in a chemistry project-based learning activity on natural paint production. The study employed a descriptive-evaluative design with a design-based research orientation. Participants included 16 Grade XI students, three trained observers, three chemistry teachers as validators, and two expert lecturers. Data were collected using the Teaching for Creativity Observation Form (TCOF), which evaluates four dimensions of creativity-supportive teaching: questioning techniques, teacher responses to students’ ideas, classroom activities that foster creativity, and whole-lesson methods that support creative learning. The data were analyzed using descriptive percentages and interpretive categories. The results showed that questioning techniques and creativity-oriented classroom activities reached full implementation, each scoring 100%. Teacher responses to students’ ideas reached a high level of implementation at 82%, whereas whole-lesson implementation of the creative learning model remained moderate at 50%. These findings indicate that the AI-assisted C-R-E-A-T-E model is pedagogically feasible for supporting creativity-oriented chemistry instruction, particularly in strengthening questioning strategies and project-based creative activities. However, deeper scaffolding is still required in imagination-building, reflective evaluation, and metacognitive guidance. The study contributes to chemistry education by demonstrating how AI can be positioned as a cognitive support tool within a structured creative learning model, while emphasizing that teacher mediation remains central to meaningful and responsible AI integration.]]>
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