Measuring Preservice Teachers’ Efficacy with the Responsible Use of Human-Centered Artificial Intelligence in Education

• In Event: Preparing Future Educators in the Age of AI

Abstract

In this study, we developed the Responsible Human-Centered Artificial Intelligence in Education (AIED) Self-Efficacy Scale. Grounded in the self-efficacy theory, this scale assesses preservice teachers’ beliefs about their capabilities in using AI responsibly within educational settings. Following established guidelines for scale development, the study proceeded through five stages: scale generation, expert review, pilot testing, exploratory factor analysis, and instrument refinement. While this study represents an initial effort in scale development, it contributes a much-needed tool for measuring preservice teachers’ self-efficacy regarding the responsible use of human-centered AI in PreK-12 education. Our study also offers implications for advancing the responsible integration of AIED into teacher preparation programs and guiding future research in this emerging field.

Authors

• Yao Fu, University of Wisconsin - Whitewater

• Crystal Machado, Indiana University of Pennsylvania

• Jiaxi Wang, University of Wisconsin-Stevens Point