Author ORCID Identifier
Document Type
Dissertation
Date of Award
2026
Degree Name
Doctor of Education (EdD)
Department
Education
Additional Department
Curriculum & Instruction
First Advisor
John M Williams
Abstract
With evolving workforce needs, global challenges, and national science education initiatives calling for STEM instruction with purposeful connections between the four domains, there is a need for methods to support educators facing the challenges this pedagogical approach presents. Challenges may weaken teachers' self-efficacy, potentially reducing the probability that an integrated STEM (I-STEM) pedagogy would be sustained in the classroom. There is limited research addressing how generative artificial intelligence (GAI) has been used for I-STEM lesson development, combined with its effects on I-STEM teaching self-efficacy (SE) grounded in social cognitive theory. This study investigated how GAI influences I-STEM teaching SE, when used as a collaborative tool to create I-STEM lessons. A self-reported, retrospective survey assessed personal, material, and social factors related to I-STEM teaching SE after an intervention consisting of instruction on GAI prompting and the I-STEM framework, culminating in participants completing an I-STEM lesson. Possible influences of prior experiences on SE factors were investigated using a Wilcoxon signed-rank test, a Welch’s independent samples t-test, and Spearman’s correlation coefficient to analyze changes in I-STEM teaching SE retrospectively. Results indicated significant positive changes in personal, material, and social SE soon after completing the intervention. No significant correlations were found between participant-reported previous use of GAI for lesson planning, knowledge level of I-STEM, previous use of GAI for educational purposes, or STEM content coursework on changes in SE factors. These findings suggest that a self-directed intervention integrating GAI within an I-STEM framework instructional sequence may increase elementary preservice teachers’ personal, material, and social SE shortly after the intervention and potentially sustain I-STEM instruction in the classroom. Results indicate professional development or coursework could be designed to help preservice teachers build confidence and SE for sustained meaningful I-STEM implementation. Levels of I-STEM pedagogical knowledge and more specific prior uses of GAI could be assessed prior to the intervention. Further research should also explore a controlled design with and without GAI, interwoven into I-STEM lesson development intervention as well as analyzing the I-STEM lessons for coherence and scientific accuracy, and expanding the scope of participants to secondary preservice and elementary and secondary in-service educators.
Subject Categories
Education
Keywords
Generative Artificial Intelligence, integrated STEM, Self-efficacy, STEM
Number of Pages
194
Publisher
University of South Dakota
Recommended Citation
Olson, Julie Ann, "The Efficaciousness of Generative AI for Integrated STEM Planning and Its Impact on STEM Teacher Self-Efficacy" (2026). Dissertations and Theses. 412.
https://red.library.usd.edu/diss-thesis/412