Reimagining instructional design: ChatGPT, Bloom's taxonomy, and the role of teacher expertise

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. • This study compares human-designed and ChatGPT-generated instructional units to explore variations in design outcomes. • The study integrates unit analyses with teacher interviews to reveal how AI tools shape instructional design practices. • Findings show that teacher expertise influences the quality and structure of AI-assisted instructional units. • The proposed analytical model provides practical indicators for improving curriculum design using AI tools.

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Publication Details

Journal
Social Sciences & Humanities Open
Published
2025-12-19
DOI
https://doi.org/10.1016/j.ssaho.2025.102325
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Reimagining instructional design: ChatGPT, Bloom's taxonomy, and the role of teacher expertise

Social Sciences & Humanities Open
Artificial Intelligence in Healthcare and Education
article

Reimagining instructional design: ChatGPT, Bloom's taxonomy, and the role of teacher expertise

article en

Abstract

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. • This study compares human-designed and ChatGPT-generated instructional units to explore variations in design outcomes. • The study integrates unit analyses with teacher interviews to reveal how AI tools shape instructional design practices. • Findings show that teacher expertise influences the quality and structure of AI-assisted instructional units. • The proposed analytical model provides practical indicators for improving curriculum design using AI tools.

Social Sciences & Humanities OpenVol. 13
An-Najah National University (PS)
Quality Education
Openalex Percentile: Top 42%
Artificial Intelligence in Healthcare and Education
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