Developing Prompt Engineering Competence Framework: Comparing China, EU, and U.S. Educators’ Digital Literacy Standards (Stage 2, 10:08 AM)

• In Event: e-Lightning Ed-Talk Session 2 - Stage 2

Abstract

This study conducts a comparative coding analysis of three national educator digital competence frameworks—China’s Digital Competence Standards for Teachers (2022), the EU’s DigCompEdu, and the U.S. ISTE Standards for Educators—to develop a universal framework of Prompt Engineering Competence (PEC) essential for educators in AI-enhanced education. By applying explicit (AI-related) and implicit (task-aligned) coding logic, the framework includes four standard PEC dimensions: Technical Operation and Tool Adaptation; Need-to-Prompt Transformation Design; Generative Content Evaluation and Optimization, and Intelligent Instructional Leadership. These dimensions highlight international consensus on the essential competencies for responsible and effective teacher–AI interaction. The findings provide theoretical grounding evidence for addressing fragmented AI literacy standards and constructing just, future-oriented teacher capacity models.

Authors

• Wei Wang, University of Tennessee

• Wen Yi Hu, AnHui Normal University

• Jialu Zhao, Stanford University

• Qi Sun, University at Albany - SUNY

• Zhongxin Zheng, The George Washington University

• Yuexin Duan, University of Tennessee