This study explores the potential of ChatGPT, a generative artificial intelligence tool, to assist in designing instructional units based on Bloom’s Taxonomy of cognitive objectives. It specifically investigates how teacher experience influences the quality of AI-generated content and examines the extent to which these units represent varying cognitive levels. Employing a qualitative, multiple case study design, the research involved three physics teachers—novice, intermediate, and expert—who independently used ChatGPT to develop a unit using objectives from the Palestinian 10th-grade physics curriculum. Data were collected through semi-structured interviews and a custom log documenting teacher-AI interaction. Analysis combined thematic analysis and deductive content analysis aligned with Bloom’s Taxonomy. Findings revealed that experienced teachers generated more balanced units across cognitive levels, while the novice teacher’s unit focused mainly on lower-order thinking skills. Five key themes emerged: initial enthusiasm, the need for repeated prompts, doubts about quality, AI dominance in dialogue, and overall satisfaction. The study concludes that while ChatGPT can support instructional design, it requires skillful guidance and pedagogical awareness. It recommends teacher training in AI use, policy development for curricular integration, and further research comparing AI-generated and official curricular content through cognitive frameworks like Bloom’s Taxonomy.

العنوان

Social Sciences & Humanities Open

الناشر

Elsevier

بلد الناشر

هولندا

Indexing

Scopus

معامل التأثير

4,6

نوع المنشور

Both (Printed and Online)

المجلد

13

السنة

2026

الصفحات

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